CN102508269A - Satellite navigation pilot signal acquisition method, pseudo random sequence stripping method and device - Google Patents

Abstract

The invention discloses a satellite navigation pilot signal acquisition method, a pseudo random sequence stripping method and a device. The satellite navigation pilot signal acquisition method includes realizing coherent integration for received satellite navigation pilot signals with integration interval length equal to the period of a first pseudo random sequence, and obtaining coherent integral values; adding coherent integral values corresponding to the same code elements in the period of a second pseudo random sequence, and obtaining same-phase accumulated results and orthogonal accumulated results of various code elements in the period of the second pseudo random sequence; processing each code element in the period of the second pseudo random sequence in the following way of adding square of the same-phase accumulated results of the code element to square of the orthogonal accumulated results of the code element to obtain an addition result of the code element; accumulating the addition results or square root of the addition results of the various code elements in the period of the second pseudo random sequence after all the code elements are processed, and obtaining an accumulated value; and realizing peak search for the accumulated value, comparing the accumulated value with a set threshold, and completing acquisition of the signals.

Description

Satellite navigation pilot signal capturing method, pseudo-random sequence stripping method and device

Technical Field

The invention relates to the field of navigation, in particular to a satellite navigation pilot signal capturing method, a pseudo-random sequence stripping method and a device.

Background

With the integration of GNSS (Global Navigation Satellite System) technology and mobile communication technology, GNSS gradually enters an indoor application stage. Because of the increased signal attenuation in the indoor environment, the signal strength reaching the receiver antenna is greatly reduced, and the radio frequency interference such as multipath and cross-correlation is more serious than that in the outdoor environment. The rapid development of indoor applications puts higher demands on the sensitivity of the receiver (acquisition sensitivity and tracking sensitivity). Whether the acquisition or tracking sensitivity is limited by the length of coherent accumulation, the GPS-LlC/A signal receiver adopts a complex A-GPS technology and needs to complete high-sensitivity tracking of signals under the support of an additional communication link and an A-GPS server. To avoid relying on the complex a-GPS techniques described above, a pilot channel without modulated navigation messages is added to a number of new system signals, such as GPS-L5 and galileo signals.

The new system GNSS signals usually include two channels, namely a data channel (data channel) modulated with navigation messages and a pilot channel (pilot channel) without modulation messages. In order to effectively suppress cross-correlation interference, two pseudorandom noise (PRN) sequences are modulated on both the data and pilot channels of the new system signal. Thus, the mathematical model of the received pilot signal is as follows:

<math> <mrow> <mi>r</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <msqrt> <mn>2</mn> <mi>P</mi> </msqrt> <msub> <mi>c</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>T</mi> <mo>)</mo> </mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>T</mi> <mo>)</mo> </mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mi>f</mi> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mi>&theta;</mi> <mo>)</mo> </mrow> <mo>+</mo> <mi>n</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </math>

where P is the pilot signal power, c₁(t) is a first heavy pseudorandom sequence, c₂(t) is the second heavy pseudorandom sequence (NH code for GPS-L5 signal), f_sIs the signal frequency, N (t) is zero mean, single-sided power spectral density is N₀White gaussian noise of (1); t is the signal propagation group delay, and theta is the carrier phase; the first heavy pseudorandom sequence has a period of T_P＝NT_cThe second pseudorandom sequence has a period LT_P。T_cThe chip width of the first pseudorandom sequence is the inverse of the code rate. The GPS-L5Q signal has a first heavy pseudorandom sequence period of 1 millisecond and a second heavy pseudorandom sequence (NH code) period of 20 milliseconds.

According to the optimal filtering theory, the acquisition part of the GNSS receiver usually first performs coherent integration on the received pilot signal:

<math> <mrow> <msub> <mi>Z</mi> <mi>m</mi> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <msub> <mi>T</mi> <mi>P</mi> </msub> </mfrac> <msubsup> <mo>&Integral;</mo> <mrow> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> <mrow> <mi>m</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </msubsup> <mi>r</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mover> <mi>T</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <msup> <mi>e</mi> <mrow> <mo>-</mo> <mi>i</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mover> <mi>f</mi> <mo>^</mo> </mover> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> </mrow> </msup> <mi>dt</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow> </math>

wherein,is a local code, which is an estimate of the signal delay;

is a local complex carrier wave that is,

and

are estimates of the frequency and phase of the signal, respectively, i being the unit of an imaginary number, i.e.

Therefore, the temperature of the molten metal is controlled,

Z_m＝Z_mI+iZ_mQ (3)

wherein

Z_mI＝s_I(m)+n_I(m)

<math> <mrow> <msub> <mi>s</mi> <mi>I</mi> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <msqrt> <mn>2</mn> <mi>P</mi> </msqrt> <msub> <mi>T</mi> <mi>P</mi> </msub> </mfrac> <msubsup> <mo>&Integral;</mo> <mrow> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> <mrow> <mi>m</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </msubsup> <msub> <mi>c</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>T</mi> <mo>)</mo> </mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>T</mi> <mo>)</mo> </mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mover> <mi>T</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mi>f</mi> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mi>&theta;</mi> <mo>)</mo> </mrow> <mi>cos</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mover> <mi>f</mi> <mo>^</mo> </mover> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>dt</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow> </math>

<math> <mrow> <msub> <mi>n</mi> <mi>I</mi> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>1</mn> <msub> <mi>T</mi> <mi>P</mi> </msub> </mfrac> <msubsup> <mo>&Integral;</mo> <mrow> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> <mrow> <mi>m</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </msubsup> <mi>n</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mover> <mi>T</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>cos</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mover> <mi>f</mi> <mo>^</mo> </mover> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>dt</mi> </mrow> </math>

In the same way

Z_mQ＝s_Q(m)+n_Q(m)

<math> <mrow> <msub> <mi>s</mi> <mi>Q</mi> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <mo>-</mo> <mfrac> <msqrt> <mn>2</mn> <mi>P</mi> </msqrt> <msub> <mi>T</mi> <mi>P</mi> </msub> </mfrac> <msub> <mi>c</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <msubsup> <mo>&Integral;</mo> <mrow> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> <mrow> <mi>m</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </msubsup> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>T</mi> <mo>)</mo> </mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mover> <mi>T</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mi>f</mi> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mi>&theta;</mi> <mo>)</mo> </mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mover> <mi>f</mi> <mo>^</mo> </mover> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>dt</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow> </math>

<math> <mrow> <msub> <mi>n</mi> <mi>Q</mi> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <mo>-</mo> <mfrac> <mn>1</mn> <msub> <mi>T</mi> <mi>P</mi> </msub> </mfrac> <msubsup> <mo>&Integral;</mo> <mrow> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> <mrow> <mi>m</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </msubsup> <mi>n</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mover> <mi>T</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mover> <mi>f</mi> <mo>^</mo> </mover> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>dt</mi> </mrow> </math>

Since the chip width of the second repetition code is equal to the integration time T_PIt can be approximated as a constant +1 or-1 over the integration interval, so

<math> <mrow> <msub> <mi>s</mi> <mi>I</mi> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <msqrt> <mn>2</mn> <mi>P</mi> </msqrt> <msub> <mi>T</mi> <mi>P</mi> </msub> </mfrac> <msub> <mi>c</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <msubsup> <mo>&Integral;</mo> <mrow> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> <mrow> <mi>m</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </msubsup> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>T</mi> <mo>)</mo> </mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mover> <mi>T</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mi>f</mi> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mi>&theta;</mi> <mo>)</mo> </mrow> <mi>cos</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <msub> <mover> <mi>f</mi> <mo>^</mo> </mover> <mi>s</mi> </msub> <mi>t</mi> <mo>+</mo> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mo>)</mo> </mrow> <mi>dt</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow> </math>

Derived from trigonometric transformations and Fourier analysis

<math> <mrow> <msub> <mi>s</mi> <mi>I</mi> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <mo>-</mo> <mfrac> <msqrt> <mn>2</mn> <mi>P</mi> </msqrt> <mn>2</mn> </mfrac> <msub> <mi>c</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <msub> <mi>K</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <mi>&tau;</mi> <mo>)</mo> </mrow> <mfrac> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </mfrac> <mi>sin</mi> <mo>[</mo> <mi>&pi;&Delta;f</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>m</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>+</mo> <msub> <mi>&epsiv;</mi> <mi>&theta;</mi> </msub> <mo>]</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow> </math>

In the same way

<math> <mrow> <msub> <mi>s</mi> <mi>Q</mi> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <mo>-</mo> <mfrac> <msqrt> <mn>2</mn> <mi>P</mi> </msqrt> <mn>2</mn> </mfrac> <msub> <mi>c</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <msub> <mi>K</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <mi>&tau;</mi> <mo>)</mo> </mrow> <mfrac> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </mfrac> <mi>cos</mi> <mo>[</mo> <mi>&pi;&Delta;f</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>m</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>+</mo> <msub> <mi>&epsiv;</mi> <mi>&theta;</mi> </msub> <mo>]</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>8</mn> <mo>)</mo> </mrow> </mrow> </math>

To achieve signal acquisition, the second pseudorandom sequence must be stripped.

The conventional non-coherent accumulation algorithm strips off the second pseudorandom sequence or the navigation message by a squaring operation, and a block diagram of a capture system adopting the conventional non-coherent accumulation algorithm is shown in fig. 1 and comprises:

a carrier NCO (numerically controlled oscillator), a PRN code generator, an adder, a first averaging module, a second averaging module, a first squaring module, a second squaring module and an accumulator;

multiplying the input coherent integral value by a sinusoidal signal output by a carrier NCO, multiplying the result by a local code output by a PRN code generator, averaging by the first averaging module, and outputting an in-phase component s_I(m) the square of the square is output to the first square module and then is sent to the adder;

multiplying the input coherent integral value by the cosine signal output by the carrier NCO, multiplying the result by the local code output by the PRN code generator, averaging by the second averaging module, and outputting the orthogonal component s_Q(m), the square of the output to the second square module is also sent to the adder;

the output of the adder is connected to the accumulator, which accumulates to Y.

The non-coherent algorithm is shown as follows:

<math> <mrow> <mi>Y</mi> <mo>=</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>JL</mi> </munderover> <msup> <mrow> <mo>|</mo> <msub> <mi>Z</mi> <mi>k</mi> </msub> <mo>|</mo> </mrow> <mn>2</mn> </msup> <mo>)</mo> </mrow> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> </msup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>9</mn> <mo>)</mo> </mrow> </mrow> </math>

obviously, the elements of the vector are independent of each other and satisfy the gaussian distribution. The detection statistic Y satisfies a Rayleigh (Rayleigh) distribution, the Probability Density Function (PDF) of which in the absence of a signal:

<math> <mrow> <msub> <mi>f</mi> <mi>Y</mi> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mn>2</mn> <msup> <mi>y</mi> <mrow> <mn>2</mn> <mi>JL</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> <mrow> <msup> <mrow> <mo>(</mo> <msup> <msub> <mrow> <mn>2</mn> <mi>&sigma;</mi> </mrow> <mi>n</mi> </msub> <mn>2</mn> </msup> <mo>)</mo> </mrow> <mi>JL</mi> </msup> <mrow> <mo>(</mo> <mi>JL</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>!</mo> </mrow> </mfrac> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <mfrac> <msup> <mi>y</mi> <mn>2</mn> </msup> <mrow> <mn>2</mn> <msup> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> <mi>y</mi> <mo>></mo> <mn>0</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>10</mn> <mo>)</mo> </mrow> </mrow> </math>

probability distribution function (CDF)

<math> <mrow> <msub> <mi>F</mi> <mi>Y</mi> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mn>1</mn> <mo>-</mo> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <mfrac> <msup> <mi>y</mi> <mn>2</mn> </msup> <mrow> <mn>2</mn> <msup> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>JL</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <mfrac> <mn>1</mn> <mrow> <mi>k</mi> <mo>!</mo> </mrow> </mfrac> <msup> <mrow> <mo>(</mo> <mfrac> <msup> <mi>y</mi> <mn>2</mn> </msup> <mrow> <mn>2</mn> <msup> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <mi>k</mi> </msup> <mo>,</mo> <mi>y</mi> <mo>></mo> <mn>0</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>11</mn> <mo>)</mo> </mrow> </mrow> </math>

<math> <mrow> <msup> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> <mn>2</mn> </msup> <mo>=</mo> <mfrac> <msub> <mi>N</mi> <mn>0</mn> </msub> <mrow> <mn>2</mn> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>12</mn> <mo>)</mo> </mrow> </mrow> </math>

The detection statistic Y satisfies a rice (Rician) distribution in the presence of a signal, whose probability density function:

<math> <mrow> <msub> <mi>f</mi> <mi>Y</mi> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <msup> <mi>y</mi> <mi>JL</mi> </msup> <mrow> <msup> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> <mn>2</mn> </msup> <msup> <msub> <mi>a</mi> <mrow> <mi>n</mi> <mn>1</mn> </mrow> </msub> <mrow> <mi>JL</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <mfrac> <mrow> <msup> <mi>y</mi> <mn>2</mn> </msup> <mo>+</mo> <msup> <msub> <mi>a</mi> <mrow> <mi>n</mi> <mn>1</mn> </mrow> </msub> <mn>2</mn> </msup> </mrow> <mrow> <mn>2</mn> <msup> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <msub> <mi>I</mi> <mrow> <mi>JL</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>a</mi> <mrow> <mi>n</mi> <mn>1</mn> </mrow> </msub> <mi>y</mi> </mrow> <msup> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> <mn>2</mn> </msup> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> <mi>y</mi> <mo>></mo> <mn>0</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>13</mn> <mo>)</mo> </mrow> </mrow> </math>

probability distribution function

<math> <mrow> <msub> <mi>F</mi> <mi>Y</mi> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mn>1</mn> <mo>-</mo> <msub> <mi>Q</mi> <mi>JL</mi> </msub> <mrow> <mo>(</mo> <mfrac> <msub> <mi>a</mi> <mrow> <mi>n</mi> <mn>1</mn> </mrow> </msub> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> </mfrac> <mo>,</mo> <mfrac> <mi>y</mi> <msub> <mi>&sigma;</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> <mi>y</mi> <mo>></mo> <mn>0</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>14</mn> <mo>)</mo> </mrow> </mrow> </math>

<math> <mrow> <msub> <mi>a</mi> <mrow> <mi>n</mi> <mn>1</mn> </mrow> </msub> <mo>=</mo> <mo>|</mo> <mo>|</mo> <mi>E</mi> <mo>[</mo> <mi>Z</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>]</mo> <mo>|</mo> <mo>|</mo> <mo>=</mo> <msqrt> <mfrac> <mi>JLP</mi> <mn>2</mn> </mfrac> </msqrt> <msub> <mi>K</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <mi>&tau;</mi> <mo>)</mo> </mrow> <mo>|</mo> <mfrac> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> </mrow> </mfrac> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>15</mn> <mo>)</mo> </mrow> </mrow> </math>

Adopting a traditional non-coherent accumulation algorithm, J is 4, L is 20, T_P＝lms，C/N₀The probability density function of the detection statistic under pure noise and signal plus noise conditions at 30dB-Hz is shown in fig. 2, solid line H₀Is under the condition of pure noiseThe probability density function of the detection statistic, dot-dash line H₁Is a probability density function of the detection statistic under signal plus noise conditions.

The presence of the second despreading code limits the length of the coherent accumulation during the acquisition phase. Usually, the receiver captures the coherent accumulation and the non-coherent accumulation with the length of the first pseudo-random sequence period, or regards the two pseudo-random sequences as a complete long code to perform coherent accumulation.

Disclosure of Invention

The invention aims to solve the technical problem of how to improve the signal-to-noise ratio and the detection probability when capturing the satellite navigation pilot signal modulated with the double pseudorandom sequences.

In order to solve the above problem, the present invention provides a method for capturing a satellite navigation pilot signal, comprising:

carrying out coherent integration with the integration interval length being the first pseudorandom sequence period on the received satellite navigation pilot signal to obtain a coherent integration value;

accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in the second pseudo-random sequence period;

and respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element;

after all code elements are processed, accumulating the addition result or the square root of each addition result of each code element in the second pseudo-random sequence period to obtain an accumulated value;

and performing peak value search on the accumulated value and comparing the accumulated value with a set threshold to finish signal acquisition.

Further, accumulating coherent integration values corresponding to the same symbol in the second pseudorandom sequence means:

and adding coherent integration values corresponding to the code elements positioned at the same position in a plurality of different periods of the second pseudo-random sequence.

The invention also provides a method for stripping the second pseudo-random sequence in the satellite navigation pilot signal, which comprises the following steps:

accumulating coherent integral values corresponding to the same code element in a second pseudo-random sequence in coherent integral values obtained by performing coherent integration on satellite navigation pilot signals with the integration interval length being the period of the first pseudo-random sequence to obtain in-phase accumulation results and quadrature accumulation results of each code element in the second pseudo-random sequence period;

and respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element;

and after all the code elements are processed, accumulating the addition result of the code elements in the second pseudo-random sequence period or the square root of the addition result.

Further, accumulating coherent integration values corresponding to the same symbol in the second pseudorandom sequence means:

and adding coherent integration values corresponding to the code elements positioned at the same position in a plurality of different periods of the second pseudo-random sequence.

The invention also provides a device for capturing the satellite navigation pilot signal, which comprises:

a non-coherent accumulation module;

the matched filter is used for carrying out coherent integration with the integration interval length being the first repeated pseudorandom sequence period on the received satellite navigation pilot signal to obtain a coherent integration value;

the peak value detection module is used for searching the peak value of the accumulated value output by the non-coherent accumulation module and comparing the accumulated value with a set threshold to finish signal capture;

further comprising:

the quasi-coherent accumulation module is used for accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence in the obtained coherent integration values to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in a second pseudo-random sequence period;

the non-coherent accumulation module is used for respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element; after all the code elements are processed, the addition result or the square root of each code element in the second pseudo-random sequence period is accumulated, and an accumulated value is output.

Further, the capturing device further comprises:

a first memory for storing the obtained coherent integration value;

and the second memory is used for storing the in-phase accumulation result and the quadrature accumulation result of each code element.

Further, the coherent-like accumulation module comprises:

l accumulators, L is the number of code elements in a second pseudo-random sequence period;

the distributor is used for reading the coherent integration values from the first memory in sequence and sending the coherent integration values corresponding to the code elements at the same position in a plurality of different periods of the second pseudorandom sequence to the same accumulator;

each accumulator is used for obtaining the inphase accumulation result and the orthogonal accumulation result of the sent coherent integration value respectively;

and the serializer is used for sequentially sending the in-phase accumulation result and the quadrature accumulation result obtained by each accumulator to the second memory after each accumulator obtains the in-phase accumulation result and the quadrature accumulation result.

The invention also provides a stripping device for the second pseudo-random sequence in the satellite navigation pilot signal, which comprises:

non-coherent accumulation module

Further comprising:

the quasi-coherent accumulation module is used for accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence in a coherent integration value obtained by performing coherent integration on the satellite navigation pilot signal, wherein the integration interval length of the coherent integration value is the period of the first pseudo-random sequence, so as to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in the second pseudo-random sequence period;

the non-coherent accumulation module is used for respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element; after each code element is processed, the addition result of each code element in the second pseudo-random sequence period or the square root of the addition result is accumulated.

Further, the coherent-like accumulation module comprises:

l accumulators, L is the number of code elements in a second pseudo-random sequence period;

the distributor is used for sequentially reading coherent integration values obtained by performing coherent integration on the satellite navigation pilot signals, wherein the length of the coherent integration interval is the period of the first repeated pseudorandom sequence, and sending the coherent integration values corresponding to code elements positioned at the same position in a plurality of different periods of the second repeated pseudorandom sequence to the same accumulator;

each accumulator is used for obtaining the inphase accumulation result and the orthogonal accumulation result of the sent coherent integration value respectively;

and the serializer is used for sequentially outputting the in-phase accumulation result and the quadrature accumulation result obtained by each accumulator after each accumulator obtains the in-phase accumulation result and the quadrature accumulation result.

Compared with the traditional non-coherent accumulation algorithm, the technical scheme of the invention has the advantages that the output signal-to-noise ratio is larger when the accumulation time is the same; under the same false alarm probability condition, the detection probability is higher.

Drawings

FIG. 1 is a block diagram of a capture system employing a conventional non-coherent accumulation algorithm;

FIG. 2 is a schematic diagram of a probability density function of detection statistics under pure noise and signal plus noise conditions using a conventional non-coherent accumulation algorithm;

fig. 3 is a flowchart illustrating a method for acquiring a satellite navigation pilot signal according to a first embodiment;

FIG. 4 is a schematic diagram of a probability density function of detection statistics under pure noise and signal plus noise conditions when the coherent-like accumulation algorithm of embodiment one is used;

FIG. 5A is a graph comparing the detection statistic performance of a non-coherent accumulation algorithm and a coherent-like accumulation algorithm when J is 2;

FIG. 5B is a graph comparing the detection statistic performance of the non-coherent accumulation algorithm and the coherent-like accumulation algorithm when J is 4;

FIG. 6 is a graph showing the relationship between the square loss and the pre-square signal-to-noise ratio;

FIG. 7 is a schematic block diagram of a satellite navigation pilot signal acquisition apparatus according to an example of the third embodiment;

fig. 8 is a schematic block diagram of a coherent accumulation-like module in the satellite navigation pilot signal acquisition apparatus shown in fig. 7.

Detailed Description

The technical solution of the present invention will be described in more detail with reference to the accompanying drawings and examples.

It should be noted that, if not conflicting, the embodiments of the present invention and the features of the embodiments may be combined with each other within the scope of protection of the present invention.

In an embodiment, a method for acquiring a satellite navigation pilot signal, as shown in fig. 3, includes:

carrying out coherent integration on the received satellite navigation pilot signals to obtain coherent integration values; the length of the integration interval of the coherent integration is the period of the first repeated pseudorandom sequence, namely the width of the code element of the second repeated sequence;

accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in the second pseudo-random sequence period;

and respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element;

after all code elements are processed, accumulating the addition result or the square root of each addition result of each code element in the second pseudo-random sequence period to obtain an accumulated value;

and performing peak value search on the accumulated value and comparing the accumulated value with a set threshold to finish signal acquisition.

For how to perform coherent integration on the received satellite navigation pilot signal, how to perform peak search and compare with a predetermined threshold to complete signal acquisition, reference may be made to the prior art.

In this embodiment, the accumulating coherent integration values corresponding to the same symbol in the second pseudorandom sequence may specifically refer to:

and adding coherent integration values corresponding to the code elements positioned at the same position in a plurality of different periods of the second pseudo-random sequence.

In this embodiment, a plurality of different periods of the second pseudo random sequence may be adjacent to each other, or may not be adjacent to each other.

For example, the coherent integration value of the mth symbol (M is a positive integer) in the nth (N is a positive integer) second pseudorandom sequence period may be added to the coherent integration value of the mth symbol in the nth + D (D is a positive integer or a negative integer having an absolute value less than N) second pseudorandom sequence period. For another example, assuming that the second pseudorandom sequence has a period of 20ms, 20ms symbols may be selected, and then the coherent integration values of the symbols may be added to coherent integration values separated by one or more 20 ms.

In accumulating coherent integration values, two or more coherent integration values may be accumulated (i.e., D may have one or more values in one accumulation). In practical application, how many coherent integration values are accumulated for the same code element can be determined according to an experiment or simulation result; for example, the accumulated number with the best experimental or simulation result or the accumulated number which best meets the requirement is selected.

The embodiment provides the above-mentioned capturing method based on the periodicity of the pilot signal, and improves the signal-to-noise ratio as much as possible before the non-coherent accumulation to reduce the square loss; the method is similar to but different from the coherent accumulation algorithm, and can be called as a coherent accumulation algorithm.

Now, the theory and performance of the similar coherent accumulation algorithm of this embodiment are analyzed theoretically as follows, and the detection statistics of the algorithm:

<math> <mrow> <mi>X</mi> <mo>=</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>L</mi> </munderover> <msup> <mrow> <mo>|</mo> <mfrac> <mn>1</mn> <mi>J</mi> </mfrac> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>J</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msub> <mi>Z</mi> <mrow> <mi>k</mi> <mo>+</mo> <mi>jL</mi> </mrow> </msub> <mo>|</mo> </mrow> <mn>2</mn> </msup> <mo>)</mo> </mrow> <mi>v</mi> </msup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>16</mn> <mo>)</mo> </mrow> </mrow> </math>

definition of

<math> <mrow> <msub> <mi>W</mi> <mi>kI</mi> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <mi>J</mi> </mfrac> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>J</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msub> <mi>Z</mi> <mrow> <mrow> <mo>(</mo> <mi>k</mi> <mo>+</mo> <mi>jL</mi> <mo>)</mo> </mrow> <mi>I</mi> </mrow> </msub> </mrow> </math> <math> <mrow> <msub> <mi>W</mi> <mi>kQ</mi> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <mi>J</mi> </mfrac> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>J</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msub> <mi>Z</mi> <mrow> <mrow> <mo>(</mo> <mi>k</mi> <mo>+</mo> <mi>jL</mi> <mo>)</mo> </mrow> <mi>Q</mi> </mrow> </msub> <mo>,</mo> <mi>k</mi> <mo>=</mo> <mn>1,2,3</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>L</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>17</mn> <mo>)</mo> </mrow> </mrow> </math>

Then

<math> <mrow> <mi>X</mi> <mo>=</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>L</mi> </munderover> <mrow> <mo>(</mo> <msup> <msub> <mi>W</mi> <mi>kI</mi> </msub> <mn>2</mn> </msup> <mo>+</mo> <msup> <msub> <mi>W</mi> <mi>kQ</mi> </msub> <mn>2</mn> </msup> <mo>)</mo> </mrow> <mo>)</mo> </mrow> <mi>v</mi> </msup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>18</mn> <mo>)</mo> </mrow> </mrow> </math>

Obviously, W_kIAnd W_kQAre all GaussRandom variables and independent of each other. Definition of

W＝[W_1I，W_2I，W_3I，...，W_LI，W_1Q，W_2Q，W_3Q，...，W_LQ]^T (19)

Absence of signal (H)₀) When the temperature of the water is higher than the set temperature,

$E\left[{{\mathrm{<figure-callout\; id="2"\; label="W\; kI"\; filenames="HDA0000095277840000012.png,HDA0000095277840000021.png"\; state="\{\{state\}\}">W</figure-callout>}}_{\mathrm{kI}}}^2\right|H_0]=E[{{\mathrm{<figure-callout\; id="2"\; label="W\; kQ"\; filenames="HDA0000095277840000012.png,HDA0000095277840000021.png"\; state="\{\{state\}\}">W</figure-callout>}}_{\mathrm{kQ}}}^2\left|H_0\right]=\frac{1}{\mathrm{<figure-callout\; id="0"\; label="J\; N"\; filenames="HDA0000095277840000021.png,HDA0000095277840000023.png"\; state="\{\{state\}\}">J</figure-callout>}}\frac{N_{}}{}\frac{{}_0}{2T_P}---\left(20\right)$

operated on by trigonometric functions

<math> <mrow> <mi>E</mi> <mo>[</mo> <msub> <mi>W</mi> <mi>kI</mi> </msub> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>]</mo> <mo>=</mo> <mo>-</mo> <mfrac> <msqrt> <mn>2</mn> <mi>P</mi> </msqrt> <mn>2</mn> </mfrac> <mfrac> <mn>1</mn> <mi>J</mi> </mfrac> <msub> <mi>c</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <msub> <mi>K</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <mi>&tau;</mi> <mo>)</mo> </mrow> <mi>sin</mi> <mi>c</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> <mfrac> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;fJL</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;fL</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>21</mn> <mo>)</mo> </mrow> </mrow> </math>

<math> <mrow> <mo>&times;</mo> <mi>sin</mi> <mo>[</mo> <mi>&pi;&Delta;f</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>+</mo> <mi>JL</mi> <mo>-</mo> <mi>L</mi> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>+</mo> <msub> <mi>&epsiv;</mi> <mi>&theta;</mi> </msub> <mo>]</mo> </mrow> </math>

In the same way

<math> <mrow> <mi>E</mi> <mo>[</mo> <msub> <mi>W</mi> <mi>kQ</mi> </msub> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>]</mo> <mo>=</mo> <mo>-</mo> <mfrac> <msqrt> <mn>2</mn> <mi>P</mi> </msqrt> <mn>2</mn> </mfrac> <mfrac> <mn>1</mn> <mi>J</mi> </mfrac> <msub> <mi>c</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <msub> <mi>K</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <mi>&tau;</mi> <mo>)</mo> </mrow> <mi>sin</mi> <mi>c</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> <mfrac> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;fJL</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;fL</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>22</mn> <mo>)</mo> </mrow> </mrow> </math>

<math> <mrow> <mo>&times;</mo> <mi>cos</mi> <mo>[</mo> <mi>&pi;&Delta;f</mi> <mrow> <mo>(</mo> <mn>2</mn> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>+</mo> <mi>JL</mi> <mo>-</mo> <mi>L</mi> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>+</mo> <msub> <mi>&epsiv;</mi> <mi>&theta;</mi> </msub> <mo>]</mo> </mrow> </math>

Mean square error thereof

$E\left[{(W_{\mathrm{kI}}-E[W_{\mathrm{kI}}\left]\right)}^2\right|H_1]=E[{(W_{\mathrm{kQ}}-E[W_{\mathrm{kQ}}\left]\right)}^2\left|H_1\right]=\frac{1}{\mathrm{<figure-callout\; id="0"\; label="J\; N"\; filenames="HDA0000095277840000021.png,HDA0000095277840000023.png"\; state="\{\{state\}\}">J</figure-callout>}}\frac{N_{}}{}\frac{{}_0}{2T_P}---\left(23\right)$

Definition of

<math> <mrow> <msub> <mi>a</mi> <mrow> <mi>qc</mi> <mn>1</mn> </mrow> </msub> <mo>=</mo> <mo>|</mo> <mo>|</mo> <mi>E</mi> <mo>[</mo> <mi>W</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>]</mo> <mo>|</mo> <mo>|</mo> <mo>=</mo> <msqrt> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>L</mi> </munderover> <mo>{</mo> <msup> <mrow> <mo>(</mo> <mi>E</mi> <mo>[</mo> <msub> <mi>W</mi> <mi>kI</mi> </msub> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>]</mo> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>+</mo> <msup> <mrow> <mo>(</mo> <mi>E</mi> <mo>[</mo> <msub> <mi>W</mi> <mi>kQ</mi> </msub> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>]</mo> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>}</mo> </msqrt> </mrow> </math> (24)

<math> <mrow> <mo>=</mo> <mfrac> <msqrt> <mn>2</mn> <mi>PL</mi> </msqrt> <mn>2</mn> </mfrac> <mfrac> <mn>1</mn> <mi>J</mi> </mfrac> <msub> <mi>K</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <mi>&tau;</mi> <mo>)</mo> </mrow> <mo>|</mo> <mi>sin</mi> <mi>c</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;f</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> <mfrac> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;fJL</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mi>sin</mi> <mrow> <mo>(</mo> <mi>&pi;&Delta;fL</mi> <msub> <mi>T</mi> <mi>P</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> </mrow> </math>

<math> <mrow> <msup> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> <mn>2</mn> </msup> <mo>=</mo> <mi>E</mi> <mo>[</mo> <msup> <mrow> <mo>(</mo> <msub> <mi>W</mi> <mi>kI</mi> </msub> <mo>-</mo> <mi>E</mi> <mo>[</mo> <msub> <mi>W</mi> <mi>kI</mi> </msub> <mo>]</mo> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>]</mo> <mo>=</mo> <mi>E</mi> <mo>[</mo> <msup> <mrow> <mo>(</mo> <msub> <mi>W</mi> <mi>kQ</mi> </msub> <mo>-</mo> <mi>E</mi> <mo>[</mo> <msub> <mi>W</mi> <mi>kQ</mi> </msub> <mo>]</mo> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>]</mo> </mrow> </math>

$=E\left[{(W_{\mathrm{kI}}-E[W_{\mathrm{kI}}\left]\right)}^2\right|H_0]=E[{(W_{\mathrm{kQ}}-E[W_{\mathrm{kQ}}\left]\right)}^2\left|H_0\right]---\left(25\right)$

$=\frac{1}{\mathrm{<figure-callout\; id="0"\; label="J\; N"\; filenames="HDA0000095277840000021.png,HDA0000095277840000023.png"\; state="\{\{state\}\}">J</figure-callout>}}\frac{N_{}}{}\frac{{}_0}{2T_P}$

When v is 0.5 and the detection statistic X obeys Rayleigh (Rayleigh) distribution, its Probability Density Function (PDF)

<math> <mrow> <msub> <mi>f</mi> <mi>X</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mn>2</mn> <msup> <mi>x</mi> <mrow> <mn>2</mn> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> <mrow> <msup> <mrow> <mo>(</mo> <msup> <msub> <mrow> <mn>2</mn> <mi>&sigma;</mi> </mrow> <mi>qc</mi> </msub> <mn>2</mn> </msup> <mo>)</mo> </mrow> <mi>L</mi> </msup> <mrow> <mo>(</mo> <mi>L</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>!</mo> </mrow> </mfrac> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <mfrac> <msup> <mi>x</mi> <mn>2</mn> </msup> <mrow> <mn>2</mn> <msup> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> <mi>x</mi> <mo>></mo> <mn>0</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>26</mn> <mo>)</mo> </mrow> </mrow> </math>

Probability distribution function (CDF)

<math> <mrow> <msub> <mi>F</mi> <mi>X</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mn>1</mn> <mo>-</mo> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <mfrac> <msup> <mi>x</mi> <mn>2</mn> </msup> <mrow> <mn>2</mn> <msup> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <mfrac> <mn>1</mn> <mrow> <mi>k</mi> <mo>!</mo> </mrow> </mfrac> <msup> <mrow> <mo>(</mo> <mfrac> <msup> <mi>x</mi> <mn>2</mn> </msup> <mrow> <mn>2</mn> <msup> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <mi>k</mi> </msup> <mo>,</mo> <mi>x</mi> <mo>></mo> <mn>0</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>27</mn> <mo>)</mo> </mrow> </mrow> </math>

The detection statistic X satisfies a rice (Rician) distribution in the presence of the useful signal, whose probability density function:

<math> <mrow> <msub> <mi>f</mi> <mi>X</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <msup> <mi>x</mi> <mi>L</mi> </msup> <mrow> <msup> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> <mn>2</mn> </msup> <msup> <msub> <mi>a</mi> <mrow> <mi>qc</mi> <mn>1</mn> </mrow> </msub> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <mfrac> <mrow> <msup> <mi>x</mi> <mn>2</mn> </msup> <mo>+</mo> <msup> <msub> <mi>a</mi> <mrow> <mi>qc</mi> <mn>1</mn> </mrow> </msub> <mn>2</mn> </msup> </mrow> <mrow> <mn>2</mn> <msup> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <msub> <mi>I</mi> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>a</mi> <mrow> <mi>qc</mi> <mn>1</mn> </mrow> </msub> <mi>x</mi> </mrow> <msup> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> <mn>2</mn> </msup> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> <mi>x</mi> <mo>></mo> <mn>0</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>28</mn> <mo>)</mo> </mrow> </mrow> </math>

probability distribution function

<math> <mrow> <msub> <mi>F</mi> <mi>X</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>|</mo> <msub> <mi>H</mi> <mn>1</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mn>1</mn> <mo>-</mo> <msub> <mi>Q</mi> <mi>L</mi> </msub> <mrow> <mo>(</mo> <mfrac> <msub> <mi>a</mi> <mrow> <mi>qc</mi> <mn>1</mn> </mrow> </msub> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> </mfrac> <mo>,</mo> <mfrac> <mi>x</mi> <msub> <mi>&sigma;</mi> <mi>qc</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> <mi>x</mi> <mo>></mo> <mn>0</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>29</mn> <mo>)</mo> </mrow> </mrow> </math>

Using the coherent-like accumulation algorithm of the present embodiment, v is 0.5, J is 4, L is 20, T is under pure noise and signal plus noise conditions_P＝1ms，C/N₀The probability density function of the detection statistic at 30dB-Hz is shown in FIG. 4, with solid line H₀Dot-dash line H as a probability density function of the detection statistic under pure noise conditions₁Is a probability density function of the detection statistic under signal plus noise conditions.

The evaluation of detection performance is based on false alarm probability:

P_FA＝P_DS(DS＞Th|H₀)＝1-F_DS(Th|H₀)(30)

and a detection probability:

P_D＝P_DS(DS＞Th|H₁)＝1-F_DS(Th|H₁)(31)

where Th is a decision threshold for determining the presence of a signal. The following section will illustrate the detection performance of the coherent-like cumulative acquisition algorithm proposed herein, as exemplified by the GPS-L5Q signal, the frame of reference being a conventional non-coherent acquisition algorithm.

FIG. 5A shows the detection systems described above with the parameter J equal to 2The measured detection performance. Wherein the Mizi symbol corresponds to the detection probability theoretically estimated by the non-coherent accumulative capture algorithm, the circle corresponds to the detection probability obtained by the non-coherent accumulative capture algorithm through a computer simulation experiment, the dotted line corresponds to the detection probability theoretically estimated by the similar coherent accumulative capture algorithm, the solid line corresponds to the detection probability obtained by the similar coherent accumulative capture algorithm through the computer simulation experiment, and the false alarm probability is kept at a constant value of 10^-3. As can be seen from the figure, the detection probability of the coherent-like accumulation method under the same carrier-to-noise ratio condition is higher than that of the non-coherent accumulation acquisition algorithm. As can be seen from fig. 5B, the advantage of the coherent-like algorithm is more obvious as the parameter J increases, i.e., as the accumulation time increases.

Since the pilot channel does not modulate the pilot message, the correlator or matched filter outputs a periodic signal (see equations 7 and 8 above) with only the second pseudorandom sequence and the carrier residual remaining, the period of which is determined by the second pseudorandom sequence. The mathematical analysis and the computer simulation prove that the similar coherent accumulation algorithm is superior to the traditional non-coherent accumulation algorithm in detection performance. The fundamental reasons are that: although both are the first heavy pseudorandom sequence stripped by coherent integration and the second heavy pseudorandom sequence removed by squaring, the coherent integration results are accumulated again by the coherent-like algorithm before squaring, i.e., the coherent integration results corresponding to the same symbol of the second heavy chip are added again, which has a similar effect to coherent integration, except that coherent integration is the ratio of the integral over a continuous interval to the interval length, and the coherent-like accumulation algorithm is spaced by the second heavy pseudorandom sequence period (LT)_P) The ratio of the integrated result over the subinterval to the total length of the interval. Fig. 6 shows the relationship between the squaring loss and the signal-to-noise ratio before squaring, the higher the signal-to-noise ratio before squaring, the smaller the signal power loss caused by squaring. Therefore, the coherent accumulation method improves the signal-to-noise ratio of the signal before the square, thereby reducing the square loss.

The second embodiment is a method for stripping a second pseudo-random sequence from a satellite navigation pilot signal, including:

accumulating coherent integral values corresponding to the same code element in a second pseudo-random sequence in coherent integral values obtained by performing coherent integration on satellite navigation pilot signals with the integration interval length being the period of the first pseudo-random sequence to obtain in-phase accumulation results and quadrature accumulation results of each code element in the second pseudo-random sequence period;

and respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element;

after each code element is processed, the addition result of each code element in the second pseudo-random sequence period or the square root of the addition result is accumulated.

In this embodiment, the accumulating coherent integration values corresponding to the same symbol in the second pseudorandom sequence may specifically refer to:

and adding coherent integration values corresponding to the code elements positioned at the same position in a plurality of different periods of the second pseudo-random sequence.

In this embodiment, a plurality of different periods of the second pseudo random sequence may be adjacent to each other, or may not be adjacent to each other.

In accumulating the coherent integration values, two or more coherent integration values may be accumulated. In practical application, how many coherent integration values are accumulated for the same code element can be determined according to an experiment or simulation result; for example, the accumulated number with the best experimental or simulation result or the accumulated number which best meets the requirement is selected.

In a third embodiment, an apparatus for acquiring a satellite navigation pilot signal includes:

the matched filter is used for carrying out coherent integration with the integration interval length being the first repeated pseudorandom sequence period on the received satellite navigation pilot signal to obtain a coherent integration value;

the quasi-coherent accumulation module is used for accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence in the obtained coherent integration values to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in a second pseudo-random sequence period;

a non-coherent accumulation module, configured to perform the following processing on each symbol in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element; after all code elements are processed, accumulating the addition result of each code element in the second pseudo-random sequence period or the square root of the addition result, and outputting an accumulated value;

and the peak value detection module is used for searching the peak value of the accumulated value output by the non-coherent accumulation module and comparing the accumulated value with a set threshold to finish signal capture.

In this embodiment, the capturing apparatus may further include:

a first memory for storing the obtained coherent integration value;

and the second memory is used for storing the in-phase accumulation result and the quadrature accumulation result of each code element.

In this embodiment, the coherent-like accumulation module may specifically include:

l accumulators, L is the number of code elements in the second pseudo-random sequence period (namely the length of the second pseudo-random sequence);

the distributor is used for reading the coherent integration values from the first memory in sequence and sending the coherent integration values corresponding to the code elements at the same position in a plurality of different periods of the second pseudorandom sequence to the same accumulator; for each accumulator to feed several cycles of coherent integration values (i.e., to sum up several coherent integration values), it can be decided according to the first embodiment;

each accumulator is used for obtaining the inphase accumulation result and the orthogonal accumulation result of the sent coherent integration value respectively;

and a serializer, configured to send the in-phase accumulation result and the quadrature accumulation result obtained by each accumulator to the second memory sequentially (which may be, but is not limited to, according to an order of symbols corresponding to the accumulator in the second pseudorandom sequence) after each accumulator obtains the in-phase accumulation result and the quadrature accumulation result.

In this embodiment, the second pseudorandom sequence periods to which the plurality of coherent integration values sent to each accumulator by the distributor belong may be adjacent or non-adjacent.

As shown in fig. 7, a specific example of this embodiment is that, after an intermediate frequency digital signal from the FIFO is multiplied by an output signal of the NCO, the multiplied intermediate frequency digital signal is down-converted by the down-converter and enters a beat Delay Line in a matched filter shown by a dashed box, and the multiplied intermediate frequency digital signal is multiplied by a local Code generated by the Code Generator and buffered in the Code Buffer, and the multiplied local Code is accumulated by the I/Q Correlator to obtain Coherent-integrated in-phase (I) and quadrature (Q) components, which are temporarily stored in the continuous first memory, Code RAM 1. The similar coherent accumulation module reads data from the first memory in sequence, and the similar coherent accumulation module stores the data in a continuous second memory, namely a coherent RAM 2. And in-phase (I) and quadrature (Q) accumulation results of the similar Coherent accumulation module are subjected to Non-Coherent accumulation, namely accumulation after square, and are stored in a discontinuous third memory Non-Coherent RAM. And finally, a search engine serving as a peak detection module carries out peak search and compares the peak search with a set threshold to finish signal acquisition.

The Coherent-like accumulation module in this specific example is shown in fig. 8, a distributor paralleling in the Coherent-like accumulation module sequentially reads in Coherent Integration values Coherent Integration I/Q from a first memory Coherent RAM 1, sends Coherent Integration corresponding to the same code element of a second pseudo random sequence (with length L) to the same Accumulator (Accumulator I/Q), the Coherent-like accumulation module includes L accumulators from Accumulator 1 to Accumulator L, each Accumulator respectively obtains an Coherent-quadrature Coherent-like accumulation result Quasi-Coherent Integration I/Q including two in-phase and quadrature accumulation results, and outputs all the results to the second memory Coherent RAM 2 sequentially through a serializer relating in the Coherent-like accumulation module after all the results are generated.

In another embodiment, an apparatus for stripping a second pseudorandom sequence from a satellite navigation pilot signal includes:

the quasi-coherent accumulation module is used for accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence in a coherent integration value obtained by performing coherent integration on the satellite navigation pilot signal, wherein the integration interval length of the coherent integration value is the period of the first pseudo-random sequence, so as to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in the second pseudo-random sequence period;

a non-coherent accumulation module, configured to perform the following processing on each symbol in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element; after each code element is processed, the addition result of each code element in the second pseudo-random sequence period or the square root of the addition result is accumulated.

In this embodiment, the coherent-like accumulation module may specifically include:

l accumulators, L is the number of code elements in the second pseudo-random sequence period (namely the length of the second pseudo-random sequence);

the distributor is used for sequentially reading coherent integration values obtained by performing coherent integration on the satellite navigation pilot signals and sending the coherent integration values corresponding to code elements positioned at the same position in a plurality of different periods of the second pseudo-random sequence to the same accumulator; for each accumulator to feed several cycles of coherent integration values (i.e., to sum up several coherent integration values), it can be decided according to the first embodiment;

each accumulator is used for obtaining the inphase accumulation result and the orthogonal accumulation result of the sent coherent integration value respectively;

and a serializer, configured to output the in-phase accumulation result and the quadrature accumulation result obtained by each accumulator sequentially (which may be, but is not limited to, in an order of symbols corresponding to the accumulator in the second pseudorandom sequence) after each accumulator obtains the in-phase accumulation result and the quadrature accumulation result.

In this embodiment, the second pseudorandom sequence periods to which the plurality of coherent integration values sent to each accumulator by the distributor belong may be adjacent or non-adjacent.

It will be understood by those skilled in the art that all or part of the steps of the above methods may be implemented by instructing the relevant hardware through a program, and the program may be stored in a computer readable storage medium, such as a read-only memory, a magnetic or optical disk, and the like. Alternatively, all or part of the steps of the above embodiments may be implemented using one or more integrated circuits. Accordingly, each module/unit in the above embodiments may be implemented in the form of hardware, and may also be implemented in the form of a software functional module. The present invention is not limited to any specific form of combination of hardware and software.

The present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it should be understood that various changes and modifications can be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (9)

1. A method for satellite navigation pilot signal acquisition, comprising:

carrying out coherent integration with the integration interval length being the first pseudorandom sequence period on the received satellite navigation pilot signal to obtain a coherent integration value;

accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in the second pseudo-random sequence period;

and respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element;

after all code elements are processed, accumulating the addition result or the square root of each addition result of each code element in the second pseudo-random sequence period to obtain an accumulated value;

and performing peak value search on the accumulated value and comparing the accumulated value with a set threshold to finish signal acquisition.

2. The method of claim 1, wherein accumulating coherent integration values corresponding to a same symbol in the second pseudorandom sequence is by:

and adding coherent integration values corresponding to the code elements positioned at the same position in a plurality of different periods of the second pseudo-random sequence.

3. A method for stripping a second pseudo-random sequence in a satellite navigation pilot signal comprises the following steps:

accumulating coherent integral values corresponding to the same code element in a second pseudo-random sequence in coherent integral values obtained by performing coherent integration on satellite navigation pilot signals with the integration interval length being the period of the first pseudo-random sequence to obtain in-phase accumulation results and quadrature accumulation results of each code element in the second pseudo-random sequence period;

and respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element;

and after all the code elements are processed, accumulating the addition result of the code elements in the second pseudo-random sequence period or the square root of the addition result.

4. The method of claim 3, wherein accumulating coherent integration values corresponding to a same symbol in the second pseudorandom sequence is by:

and adding coherent integration values corresponding to the code elements positioned at the same position in a plurality of different periods of the second pseudo-random sequence.

5. An apparatus for acquiring a satellite navigation pilot signal, comprising:

a non-coherent accumulation module;

the matched filter is used for carrying out coherent integration with the integration interval length being the first repeated pseudorandom sequence period on the received satellite navigation pilot signal to obtain a coherent integration value;

the peak value detection module is used for searching the peak value of the accumulated value output by the non-coherent accumulation module and comparing the accumulated value with a set threshold to finish signal capture;

it is characterized by also comprising:

the quasi-coherent accumulation module is used for accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence in the obtained coherent integration values to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in a second pseudo-random sequence period;

the non-coherent accumulation module is used for respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element; after all the code elements are processed, the addition result or the square root of each code element in the second pseudo-random sequence period is accumulated, and an accumulated value is output.

6. The apparatus of claim 5, further comprising:

a first memory for storing the obtained coherent integration value;

and the second memory is used for storing the in-phase accumulation result and the quadrature accumulation result of each code element.

7. The apparatus of claim 6, wherein the coherent-like accumulation module comprises:

l accumulators, L is the number of code elements in a second pseudo-random sequence period;

the distributor is used for reading the coherent integration values from the first memory in sequence and sending the coherent integration values corresponding to the code elements at the same position in a plurality of different periods of the second pseudorandom sequence to the same accumulator;

each accumulator is used for obtaining the inphase accumulation result and the orthogonal accumulation result of the sent coherent integration value respectively;

and the serializer is used for sequentially sending the in-phase accumulation result and the quadrature accumulation result obtained by each accumulator to the second memory after each accumulator obtains the in-phase accumulation result and the quadrature accumulation result.

8. A device for stripping a second pseudo-random sequence from a satellite navigation pilot signal, comprising:

non-coherent accumulation module

It is characterized by also comprising:

the quasi-coherent accumulation module is used for accumulating coherent integration values corresponding to the same code element in the second pseudo-random sequence in a coherent integration value obtained by performing coherent integration on the satellite navigation pilot signal, wherein the integration interval length of the coherent integration value is the period of the first pseudo-random sequence, so as to obtain an in-phase accumulation result and an orthogonal accumulation result of each code element in the second pseudo-random sequence period;

the non-coherent accumulation module is used for respectively carrying out the following processing on each code element in the second pseudo-random sequence period: adding the square of the in-phase accumulation result and the square of the quadrature accumulation result of the code element to obtain an addition result of the code element; after each code element is processed, the addition result of each code element in the second pseudo-random sequence period or the square root of the addition result is accumulated.

9. The apparatus of claim 8, wherein the coherent-like accumulation module comprises:

l accumulators, L is the number of code elements in a second pseudo-random sequence period;

the distributor is used for sequentially reading coherent integration values obtained by performing coherent integration on the satellite navigation pilot signals, wherein the length of the coherent integration interval is the period of the first repeated pseudorandom sequence, and sending the coherent integration values corresponding to code elements positioned at the same position in a plurality of different periods of the second repeated pseudorandom sequence to the same accumulator;

each accumulator is used for obtaining the inphase accumulation result and the orthogonal accumulation result of the sent coherent integration value respectively;

and the serializer is used for sequentially outputting the in-phase accumulation result and the quadrature accumulation result obtained by each accumulator after each accumulator obtains the in-phase accumulation result and the quadrature accumulation result.

Images