JP4928114B2 - Carrier phase relative positioning device - Google Patents

Description

The present invention relates to an apparatus for performing relative positioning using the phase of a carrier wave from a positioning satellite, and more particularly to a technique for estimating and removing an ionospheric delay amount.

Conventionally, there has been a method of performing relative positioning by receiving radio waves transmitted from positioning satellites such as GPS satellites (hereinafter referred to as “positioning satellites”) by a plurality of receivers and measuring their carrier phases. For example, it is applied to an apparatus for performing relative positioning of a moving body such as a ship.

In such a positioning device, relative positioning is performed by the following method.

Radio waves transmitted from two positioning satellites are received by a plurality of receivers, and the respective carrier phases are measured. And, as a pair of two antennas, the single phase difference of the two antennas based on the radio wave from one positioning satellite, and the single phase difference of the two antennas based on the radio wave from the other positioning satellite Is obtained as a double phase difference. Note that the phase difference between the antennas is taken to remove the error caused by the satellite. Therefore, when the error caused by the satellite can be removed by an external means, the zero-fold phase difference (the phase difference is taken). And a single phase difference between satellites may be used.

The double phase difference calculated in this way is decomposed into an integer part and a decimal part when converted into wave number units. Of these, the decimal part can be measured directly by the positioning device, but the integer part cannot be measured directly, leaving indefiniteness. This integer part that cannot be directly measured is called an integer bias, and an accurate phase difference can be obtained by obtaining this integer bias. Since the integer bias cannot be directly measured as described above, it is usually determined by various estimation methods and tests. Thereafter, a base line vector connecting the reference antenna and another antenna (for example, an antenna provided in the moving body) is calculated, and relative positioning is performed (for example, refer to Patent Documents 1 and 2).
JP 2002-40124 A JP 2005-69866 A

As described above, in the positioning device, how accurately the integer bias is determined greatly affects the positioning accuracy. When the base line length is short (short base line), that is, when the position of the moving body to be measured (the position of the antenna provided in the moving body) is close to the reference position (the position of the reference antenna), each known technique The integer bias is determined with high accuracy.

However, when the base line length is long (long base line), that is, the position of the mobile body to be measured (may be a fixed point) (the position of the antenna provided in the mobile body) is far from the reference position (the position of the reference antenna). In this case, for example, when the ship position is measured by a ship existing in the ocean, it is affected by ionospheric delay and tropospheric delay of the radio wave transmitted from the positioning satellite. In particular, the influence of the ionospheric delay amount is large, and it is possible to improve the integer bias estimation accuracy in the long baseline by suppressing the influence of the ionospheric delay amount on the integer bias estimation as much as possible.

The present invention has been made in view of the above problems, and can determine an integer bias with high accuracy and high speed regardless of the baseline length by enabling calculation of an integer bias float solution that eliminates the influence of ionospheric delay. It is an object of the present invention to provide a carrier phase relative positioning device that can be used.

In order to solve the above problems, the present invention provides a plurality of antennas, at least one of which is fixed on a moving body, for receiving radio waves of a first frequency and a second frequency transmitted from a positioning satellite, and the plurality of antennas A receiver that obtains satellite information superimposed on the positioning signal together with the carrier phase from the positioning signal received at, a phase difference observation amount for the radio wave of the first frequency from the carrier phase, and the first frequency and the second frequency A phase difference calculation unit that calculates at least a phase difference observation amount of a wide lane signal obtained by differential synthesis of radio waves , an integer bias and a baseline vector are obtained from the phase difference observation amount and the satellite information, and based on the obtained baseline vector and a positioning computation portion that performs positioning calculation Te, the positioning calculation unit, integer ambiguity for the first frequency, baseline vector, and the estimation calculation of the ionospheric delay, A phase difference observables for radio waves of first frequency, and the phase difference observables wide-lane signal, the phase difference baseline vector and ionospheric delay generated from the amount of change in ionospheric error per unit time obtained from the observation amount time update And at least used. As an estimation calculation technique, for example, there is a technique using a Kalman filter. Thereby, an integer bias and a base line vector from which the influence of the ionospheric delay amount is removed can be obtained.

The wavelength of the wide lane signal is long, for example, the wavelength of the L1-L2 wave is 0.862 m, the wavelength of the L1-L5 wave is 0.751 m, the wavelength of the L2-L5 wave is 5.865 m, and the wavelength of the L1 wave is 0.190. m, L2 wave wavelength is 0.244 m, and L5 wave wavelength is 0.255 m. Therefore, even in the case of the long baseline, the integer bias of the wide lane signal can be obtained relatively easily. Further, by using the Melbourne-Bubena linear combination formula, the integer bias of the wide lane signal from which the influence of the ionospheric delay amount is removed can be easily obtained. Therefore, as another embodiment of the present invention, the positioning calculation unit first determines an integer bias of a wide lane signal from the phase difference observation amount and the satellite information, and determines the integer bias of the determined wide lane signal and the time From the update, the phase difference observation amount, and the satellite information, it is also possible to estimate an integer bias, a base line vector, and an ionospheric delay with respect to a reference frequency using, for example, a Kalman filter.

According to the present invention, the base line vector and the ionosphere delay amount time update are generated from the phase difference observation amount, and the generated time update, the phase difference observation amount, and the satellite information are used to integer bias with respect to a reference frequency, By estimating the integer bias, the baseline vector, and the ionospheric delay for the wide lane signal, the integer bias and the baseline vector from which the influence of the ionospheric delay error is removed can be obtained.

The wavelength of the wide lane signal is approximately 0.86 m when using the L1 and L2 waves. For example, the integer bias of the wide lane signal can be easily determined using DGPS positioning results or Melbourne-Buvener linear combination. Can do. Therefore, first, the integer bias of the wide lane signal is determined, and the integer bias, baseline vector, and ionospheric delay with respect to the reference frequency are determined using the determined integer bias, time update, phase difference observation amount, and satellite information of the wide lane signal. It is also possible to determine the integer bias and the baseline vector more accurately by estimating.

Thereby, even in the case of a long baseline, positioning calculation can be performed without the influence of the ionospheric delay amount, which contributes to improvement of positioning accuracy.

In addition, it is possible to further improve the positioning accuracy by continuously estimating the ionospheric delay amount after determining the integer bias with respect to the reference frequency and correcting the ionospheric delay amount with respect to the observed amount.

(Embodiment 1)
Hereinafter, a carrier phase relative positioning apparatus according to Embodiment 1 of the present invention will be described with reference to the drawings.

FIG. 1 is a schematic diagram showing a positioning environment according to the present embodiment, and FIG. 2 is a schematic block diagram showing a main part of a positioning device of a mobile receiver.

In FIG. 1, 100 is a GPS antenna provided in a fixed station (reference station), 101 is a GPS antenna provided in a ship (moving body), and sat1 to satN are positioning satellites. Further, the ship provided with the GPS antenna 101 includes a GPS receiver 201 and a relative positioning calculation processing unit 301 as shown in FIG. The relative positioning calculation processing unit 301 includes a phase difference calculation unit 31 and a positioning calculation unit 32.

The positioning satellites sat1 to satN transmit radio waves having a plurality of frequencies. In the present embodiment, among the L1 wave (f _L1 = 1575.42 MHz), L2 wave (f _L2 = 1227.60 MHz), and L5 wave (1176.45 MHz) used in the GPS system as this radio wave, the L1 wave The processing contents using the L1 wave as a reference signal will be described on the receiver side. These radio waves are composed of a carrier wave on which several positioning codes called codes are superimposed. The L1 wave includes a C / A code and a P code, and also includes information on ephemeris information, ionospheric delay and tropospheric delay. Navigation message is superimposed.

The GPS antenna 101 is an antenna fixed on a moving body, receives radio waves from predetermined positioning satellites of the positioning satellites sat1 to satN, converts them into intermediate frequency signals, amplifies them with an amplifier, and receives a GPS receiver. To 201. The radio waves received by the GPS antenna 101 at this time are radio waves having a plurality of frequencies (here, L1 waves and L2 waves) transmitted from the positioning satellite.

The GPS receiver 201 transmits each satellite information superimposed on the radio wave together with carrier phases obtained from radio waves of a plurality of frequencies received by the GPS antenna 101 to the relative positioning calculation processing unit 301 at a predetermined interval. Here, the carrier phase is transmitted to the phase difference calculation unit 31, and the satellite information is transmitted to the positioning calculation unit 32.

The phase difference calculation unit 31 uses a carrier phase signal received from the GPS receiver 201 and an observation amount of a double phase difference (hereinafter, referred to as a similar signal obtained by analyzing the signal received by the reference antenna with the reference receiver). The phase difference observation amount is calculated and given to the positioning calculation unit 32. There are two types of phase difference observation surveys generated by the phase difference calculation unit 31. The phase difference calculation unit 31 performs phase difference observation for one reference frequency radio wave (L1) based on carrier phases obtained from radio waves of a plurality of frequencies. And a phase difference observation amount of a wide lane signal formed by differentially combining a radio wave (L2) having a different frequency with respect to a radio wave (L1) having a single reference frequency.

The positioning calculation unit 32 performs time update of the satellite information given from the GPS receiver 201, the phase difference observation amount given from the phase difference calculation unit 31, and the baseline vector / ionosphere delay amount generated from the phase difference observation amount. And an integer bias for the reference frequency (hereinafter referred to as L1 band bias as appropriate), an integer bias for the wide lane signal (hereinafter referred to as WL bias as appropriate), a baseline vector, and an ionospheric delay amount. As a technique for performing this estimation calculation, for example, there is a technique using a Kalman filter. Thereafter, the positioning calculation unit 32 performs an estimated integer bias test process and the like to determine the integer bias, calculates a baseline vector, and then performs a positioning calculation based on the obtained baseline vector.

FIG. 3 is a flowchart showing an example of processing contents performed by the positioning calculation unit 32 of the carrier phase relative positioning device according to Embodiment 1 of the present invention.

(S101) First, as step S101, the satellite information given from the GPS receiver 201, the phase difference observation amount given from the phase difference calculation unit 31, and the baseline vector and ionosphere delay amount generated from the phase difference observation amount From this time update, the L1 band bias, the WL bias, the baseline vector, and the ionospheric delay amount are estimated using, for example, a Kalman filter. The L1 band bias and WL bias estimated here are bias values having a fractional part called an integer bias float solution (hereinafter, this solution is referred to as an L1 band bias float solution and a WL bias float solution). .)

(S102) Next, the estimated float solution of the L1 band bias and the float solution of the WL bias are converted into integers using a known technique such as the LAMBDA method.

(S103) Step S103 is a process for testing whether or not the integer bias obtained in step S102 is correct. If the integer bias test fails, the calculation of the integer bias float solution is performed again (step S101), and the integer processing (S102) is performed. On the other hand, if the integer bias test is passed, the process proceeds to a baseline vector estimation process. Thereby, it is possible to obtain the L1 band bias and the WL bias from which the influence of the ionospheric delay amount is removed.

(S104) In step S105, a baseline vector is calculated based on the determined L1 band bias, WL bias, and ionospheric delay amount. Thereby, a baseline vector from which the influence of the ionospheric delay amount is removed can be obtained.
(S105) Relative positioning is performed using the obtained baseline vector.

Next, the integer bias float solution estimation process described in step S101 will be described in more detail with reference to an example in which a Kalman filter is used.

(Observation equation)
The pseudo-range P and the accumulated carrier phase (hereinafter referred to as ADR) Ψ of the own receiver observation amount are respectively defined by the following equations. For example, P ⁱ _1k represents a pseudo distance obtained by observing the L1 band signal of the satellite i at the receiver k.

Further, ADR of WL are satellite i, j, receiver k, for l, using a double difference _∇ΔΨ ^ij 2kl double difference ∇ΔΨ ^ij _1kl and L2 bands ADR of L1 band ADR, as follows Can be expressed as

Here, when f ₁ −f ₂ = f _WL and λ _WL = C / f _WL (C is the speed of light), the following equation (5) can be obtained.

By the way, tropospheric errors can be removed in advance by correction using a model. The geometric distance ∇Δρ can be expressed as ∇Δρ = ΔHb using the baseline vector b = [x, y, z] ^T and the direction cosine difference matrix ΔH. Using this, an observation equation such as the following equation (6) can be established from equations (1) and (5).

Here, if the state vector is [b, ∇ΔN ₁ , ∇ΔN _WL , −∇ΔIon1] ^T , the observation equation (6) can be expressed as the following equation (7). As can be seen from the following equation, the integer bias float solution estimation process according to Embodiment 1 of the present invention uses a pseudorange observable having a larger error than the phase observable due to the influence of multipath or the like. Not done. Therefore, the accuracy of the state vector estimation result can be improved as compared with the case where the pseudo-range observation amount is used for the float solution estimation process.

The positioning calculation unit 32 estimates the state vector of equation (7) using a Kalman filter. The time update and observation update at this time are set as follows.

(Time update)
The time update is a process for obtaining a predicted value by calculation until a new observation amount is obtained. Here, since the integer bias does not change with time unless cycle slip occurs, the integer bias, ionospheric error, and baseline vector time update in the Kalman filter are set as follows.

1. Since the integer bias does not change with time, the integer bias is constant.

2. The ionospheric error ∇Δψ ₁ −∇Δψ _WL can be obtained from the following equation (8).

Accordingly, ∇ΔIon1 is represented by the following equation (9).

As described above, since the integer bias does not change with time, the amount of change in the ionospheric error per unit time can be expressed as the following equation (10).

Therefore, when the amount of change in the ionospheric error per unit time shown in the equation (10) is delta∇Δion, the time update of the ionospheric error is expressed by the following equation (11).

3. The baseline vector baseline vector is updated using the L1 band observation amount because the L1 band observation amount is more accurate than the WL observation amount. Here, since the integer bias does not change with time and the tropospheric error can be removed in advance, ∇Δψ ₁ (t + 1) −∇Δψ ₁ (t) can be obtained from the following equation (12) from equation (1). it can.

When this equation (12) is arranged using delta∇Δion (amount of change in ionospheric error per unit time), the following equation is obtained.

Thus, the time base vector update can be expressed as the following equation (13).

Set as above. Integer bias, 2. 2. ionospheric error; When the time base update of the baseline vector is displayed in a matrix, the time update is expressed by the following equation (14).

(Observation update)
Observation update is a process to obtain a new estimated value from a newly obtained observation amount and a predicted value. By comparing the observed value with the predicted observed value, information on the error is obtained, and a certain gain is obtained. Is added to the predicted value to obtain an estimated value. This setting is the same as normal observation update.

(Integer bias float solution estimation process)
The positioning calculation unit 32, based on the time update generated from the phase difference observation amount and the observation update as described above, the state vectors [b, ∇ΔN ₁ , ∇ΔN _WL , −∇ΔIon1] ^{T in} Equation (7). Is estimated using a Kalman filter.

Thereafter, the estimated integer bias float solution is converted into an integer using a known LAMBDA method or the like, and the integer bias is tested. By passing this test, an integer bias is obtained. After the integer bias is determined, the baseline vector can be obtained from Equation (6) based on, for example, the ionospheric delay amount obtained by the above-described estimation calculation using the Kalman filter and the determined integer bias.

By performing the processing as described above, it is possible to remove the influence of the ionospheric delay amount during the estimation calculation of the state vector of Equation (7), and to obtain the integer bias and the baseline vector with high accuracy.
In addition, according to the present invention, an integer bias float solution can be estimated without using a pseudorange observable having a larger error than the phase observable due to the influence of multipath or the like. Compared to the case of using the distance observation amount, the accuracy of the state vector estimation result can be improved.

Next, the results of a simulation performed on the present invention are shown below.
4 and 5 are diagrams showing the results of a simulation performed on the carrier phase relative positioning apparatus according to Embodiment 1 of the present invention. FIG. 4 shows a simulation result when ionosphere estimation is performed using the technique of the present invention, and FIG. 5 shows a result obtained when the ionosphere is not estimated under the same conditions.

The method according to the first embodiment of the present invention is implemented on a PC, and the effect is confirmed by post-processing using data recorded in an environment of about 35 km in base line length for about 24 hours from 10:00 on July 20, 2004. did. Reset the Kalman filter on the program 24 times every 3600 seconds. Since the Kalman filter is in a state where estimation has been started by resetting, the estimation result using the Kalman filter is obtained 24 times an hour with different satellite arrangements. The average error of 24 estimated baseline vectors was calculated for each elapsed time. That is, FIG. 4 shows average errors in the X, Y, and Z axis directions from 24 estimated baseline vectors in a certain elapsed time (1 to 3600 sec). Since the correct ionospheric error is unknown, the effect was confirmed by comparison with the baseline accuracy obtained when the ionosphere shown in FIG. 5 is not estimated.

As shown in the figure, the estimated baseline vector average error does not converge in any time in FIG. 5 where ionosphere estimation is not performed, whereas in FIG. 4 in which ionosphere estimation is performed using the present invention, gradually after about 1000 sec. It was confirmed that the estimated baseline vector average error converged to zero.

As described above, according to the carrier phase relative positioning apparatus according to Embodiment 1 of the present invention, time updates of the baseline vector and the ionospheric delay amount are generated from the phase difference observation amount, and the generated time update and the phase difference observation are performed. Quantities and the satellite information are used to estimate integer biases and baseline vectors that eliminate the effects of ionospheric delay errors by estimating integer biases for reference frequencies, integer biases for wide lane signals, baseline vectors, and ionosphere delays. be able to. Thereby, even in the case of a long baseline, positioning calculation can be performed without the influence of the ionospheric delay amount, which contributes to improvement of positioning accuracy.

In addition, it is possible to further improve the positioning accuracy by continuously estimating the ionospheric delay amount after determining the integer bias with respect to the reference frequency and correcting the ionospheric delay amount with respect to the observed amount.

(Embodiment 2)
Next, a carrier phase relative positioning apparatus according to Embodiment 2 of the present invention will be described. The carrier phase relative positioning device according to the second embodiment of the present invention is different from the carrier phase relative positioning device according to the first embodiment in the processing contents of the positioning calculation unit 32 shown in FIG. Therefore, in the following description, the process which the positioning calculating part 32 performs is demonstrated, and the description about another component is abbreviate | omitted.

FIG. 6 is a flowchart showing an example of processing contents performed by the positioning calculation unit 32 of the carrier phase relative positioning device according to Embodiment 2 of the present invention.

The wavelength of the wide lane signal is about 0.86 m, which is longer than the L1 wave wavelength of 0.19 m and the L2 wave wavelength of 0.24 m. Therefore, the WL bias can be obtained relatively easily as compared with the L1 band bias and the L2 band bias. Therefore, in the carrier phase relative positioning apparatus according to the second embodiment of the present invention, first, the integer bias of the WL bias is determined, and this is used as known information to determine the L1 band bias and the baseline vector from which the influence of the ionospheric delay is removed. .

(S201) First, in step S201, a float solution of WL bias is estimated. As this estimation method, for example, a technique using a well-known Melbourne-Bubena linear combination or a technique using a Kalman filter can be considered.

Here, the technique using the Melbourne-Bubena linear combination means that the pseudo-range P of the own receiver observation amount and the accumulated carrier phase (hereinafter referred to as ADR) Ψ are expressed by WL from Formulas (1) to (4). It is a technique for finding a bias. Specifically, (ρ ⁱ _k + T ^ik ) in the above-described formulas (1) to (4) is regarded as one unknown, and two unknowns (ρ ⁱ ) from the two formulas (3) and (4). _k + ^{T ik} and ^I _{i k)} seek. Thereafter, the solution is substituted into the equations (1) and (2) to obtain n ⁱ _1k and n ⁱ _2k, and the WL bias is obtained from n ⁱ _1k −n ⁱ _2k . Since the pseudo distance P expressed by the equations (3) and (4) includes a large error, this technique is generally used for calculating a WL bias having a long wavelength. It is not practical to use the bias determination of the short wavelength L1 wave and L2 wave.

(S202) Next, the estimated WL bias float solution is converted to an integer using a known technique such as the LAMBDA method.

(S203) Step S203 is a process for examining whether or not the WL bias obtained in step S202 is correct. When the integer bias test fails, the calculation of the WL bias float solution is performed again (step S201), and the integer processing (S202) is performed. On the other hand, if the integer bias test is passed, the process proceeds to the L1 band bias and baseline vector estimation processing. Since the WL bias obtained here has a long wavelength, it is less susceptible to errors due to ionospheric delay.

(S204) Next, as S204, the satellite information given from the GPS receiver 201, the phase difference observation amount given from the phase difference calculation unit 31, and the baseline vector and ionosphere delay amount generated from the phase difference observation amount From the time update, the L1 band bias, the baseline vector, and the ionospheric delay amount are estimated using, for example, a Kalman filter.

(S205) Next, the estimated L1 band bias float solution is converted to an integer using a known technique such as the LAMBDA method.

(S206) Step S206 is a process for examining whether or not the L1 band bias obtained in step S102 is correct. If the integer bias test fails, the calculation of the float solution for the L1 band bias is again performed (step S204) and the integer processing (S205) is performed. On the other hand, if the integer bias test is passed, the process proceeds to a baseline vector estimation process. Thereby, it is possible to obtain the L1 band bias from which the influence of the ionospheric delay amount is removed.

(S207) In step S207, a baseline vector is calculated based on the determined L1 band bias and WL bias. Thereby, a baseline vector from which the influence of the ionospheric delay amount is removed can be obtained.
(S208) Relative positioning is performed using the obtained baseline vector.

Next, the estimation process of the L1 band bias float solution described in step S204 will be described in more detail using a case where a Kalman filter is used as an example.

(Observation equation)
The observation equation for the L1ADR double phase difference and the WLADR double phase difference after the WL bias is determined is expressed by the following equation (15).

Here, if the state vector is [b, ∇ΔN ₁ , −∇ΔIon1] ^T , the observation equation (15) can be expressed as the following equation (16). As can be seen from the following equation, the integer bias float solution estimation process according to Embodiment 1 of the present invention uses a pseudorange observable having a larger error than the phase observable due to the influence of multipath or the like. Not done. Therefore, the accuracy of the state vector estimation result can be improved as compared with the case where the pseudo-range observation amount is used for the float solution estimation process.

(Time update / Observation update)
Since the time update and the observation update are the same as those described in the first embodiment, description thereof is omitted here.

(Integer bias float solution estimation process)
The positioning calculation unit 32 estimates the state vector [b, ∇ΔN ₁ , −∇ΔIon1] ^T of Equation (16) using a Kalman filter based on the time update generated from the phase difference observation amount and the observation update.

Thereafter, the estimated float solution of the L1 band bias is converted into an integer using a known LAMBDA method or the like, and the L1 band bias is tested. By passing this test, the L1 band bias is obtained. After the determination of the L1 band bias, the baseline vector can be obtained from the equation (15) based on the ionospheric delay amount obtained by the above-described Kalman filter estimation calculation and the determined L1 band bias, for example.

By performing the processing as described above, it is possible to eliminate the influence of the ionospheric delay amount during the estimation calculation of the state vector of equation (16), and to obtain the L1 band bias and the baseline vector with higher accuracy.
In addition, according to the present invention, an integer bias float solution can be estimated without using a pseudorange observable having a larger error than the phase observable due to the influence of multipath or the like. Compared to the case of using the distance observation amount, the accuracy of the state vector estimation result can be improved.

Next, the results of a simulation performed on the present invention are shown below.
FIG. 7 is a diagram showing a result of a simulation performed on the carrier phase relative positioning device according to the second embodiment of the present invention. The WL bias uses a value calculated in advance based on the correct baseline, and other conditions are the same as those in FIGS. 4 and 5 described in the first embodiment.

As shown in FIG. 7, the baseline vector was obtained within an error range of ± 0.03 m on any of the x, y, and z axes, and it was confirmed that the baseline vector could be calculated with high accuracy.

As described above, according to the carrier phase relative positioning apparatus according to Embodiment 2 of the present invention, first, the integer bias of the wide lane signal is determined from the phase difference observation amount and the satellite information, and then the determined wide lane signal By using integer bias, time update, phase difference observables, and satellite information to estimate integer bias, baseline vector, and ionospheric delay relative to the reference frequency, the effect of ionospheric delay error is removed and integer bias and baseline vector are estimated. Can be requested. Thereby, even in the case of a long baseline, positioning calculation can be performed without the influence of the ionospheric delay amount, which contributes to improvement of positioning accuracy.

In addition, it is possible to further improve the positioning accuracy by continuously estimating the ionospheric delay amount after determining the integer bias with respect to the reference frequency and correcting the ionospheric delay amount with respect to the observed amount.

The first and second embodiments described above are examples of the best embodiment, and various modifications can be made without departing from the spirit of the present invention. The present invention is not limited to the above-described embodiments. Absent.

Schematic showing the positioning environment according to this embodiment 1 is a block diagram showing an example of the configuration of a carrier phase relative positioning device according to Embodiment 1 of the present invention. The flowchart which shows an example of the processing content which the positioning calculating part of the carrier phase relative positioning apparatus by Embodiment 1 of this invention performs. The figure which shows the simulation result at the time of performing an ionosphere estimation using the technique by Embodiment 1 of this invention The figure which shows the simulation result obtained when not performing ionosphere estimation on the same conditions as FIG. The flowchart which shows an example of the processing content which the positioning calculating part of the carrier phase relative positioning apparatus by Embodiment 2 of this invention performs. The figure which shows the simulation result at the time of performing an ionosphere estimation using the technique by Embodiment 2 of this invention

Explanation of symbols

100, 101 GPS antenna 201 GPS receiver 301 Relative positioning calculation processing section 31 Phase difference calculation section 32 Positioning calculation sections sat1 to satN Positioning satellite

Claims (4)

A plurality of antennas, at least one of which is fixed on the moving body and receives radio waves of the first frequency and the second frequency transmitted from the positioning satellite;
A receiver for obtaining satellite information superimposed on a positioning signal together with a carrier phase from positioning signals received by the plurality of antennas;
A phase difference calculation unit for calculating at least a phase difference observation amount for a radio wave of a first frequency from the carrier phase, and a phase difference observation amount of a wide lane signal obtained by differentially combining the radio waves of the first frequency and the second frequency ;
An integer bias and a baseline vector are obtained from the phase difference observation amount and the satellite information, and a positioning calculation unit that performs positioning calculation based on the obtained baseline vector,
The positioning calculation unit, an integer bias, baseline vector with respect to the first frequency, and the estimation calculation of the ionospheric delay, and the phase difference observables for radio waves of the first frequency, and the phase difference observables wide-lane signal, the phase difference A carrier phase relative positioning device characterized by using at least a baseline vector generated from a change amount of ionospheric error per unit time obtained from an observation amount and time update of ionosphere delay amount. A plurality of antennas, at least one of which is fixed on the moving body and receives radio waves of the first frequency and the second frequency transmitted from the positioning satellite;
A receiver for obtaining satellite information superimposed on a positioning signal together with a carrier phase from positioning signals received by the plurality of antennas;
A phase difference calculation unit for calculating at least a phase difference observation amount for a radio wave of a first frequency from the carrier phase, and a phase difference observation amount of a wide lane signal obtained by differentially combining the radio waves of the first frequency and the second frequency ;
An integer bias and a baseline vector are obtained from the phase difference observation amount and the satellite information, and a positioning calculation unit that performs positioning calculation based on the obtained baseline vector,
The positioning calculation unit is configured to estimate the integer bias for the first frequency , the baseline vector, and the ionospheric delay amount by using the phase difference observation amount of the wide lane signal and the integer bias of the wide lane signal determined in advance using the satellite information. The baseline vector and ionosphere delay amount generated from the phase difference observation amount for the radio wave of the first frequency , the phase difference observation amount of the wide lane signal, and the change amount of the ionospheric error per unit time obtained from the phase difference observation amount. A carrier phase relative positioning device using at least time update. In the carrier phase relative positioning device according to claim 2,
The positioning operation unit uses a Melbourne-Bubena linear combination formula to determine an integer bias of a wide lane signal. In the carrier phase relative positioning device according to claim 1 or 2,
A carrier phase relative positioning device, wherein the estimation calculation by the positioning calculation unit is performed using a Kalman filter.

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