KR101423265B1 - Method And Apparatus for Eliminating Sea Clutter - Google Patents

Abstract

A method and apparatus for removing a sponge clutter are disclosed.
A database for storing wave shape information classified by wave height and matching information related to the wave shape information and storing the wave shape information; An antenna for radiating an electromagnetic wave toward a target or a predetermined area and receiving a reflection signal reflected from the target or the predetermined area; A filtering unit for filtering the reflection signal according to a predetermined frequency; A calculation unit for calculating a specific coefficient based on the filtered signal; A comparison unit for extracting the wave shape information corresponding to the specific coefficient calculated from the database and extracting a threshold corresponding to the wave shape information; And a clutter removing unit for removing the clutter from the reflected signal by applying a value corresponding to the threshold value to the clutter canceling unit.

Description

TECHNICAL FIELD The present invention relates to a method and apparatus for removing sea surface clutter,

The present embodiment relates to a method and apparatus for removing sea surface clutters. More specifically, because the characteristics of the marine radar are many, it is difficult to distinguish the target of the target because the wave clutter occurs frequently. Therefore, the classification of the clutter originating from the sea surface is classified so that the desired clutter can be removed And more particularly, to a method and apparatus for removing a sea surface clutter.

The contents described in this section merely provide background information on the present embodiment and do not constitute the prior art.

Ship radars are generally used in two types: S-band at 3 GHz band or X-band at 10 GHz band.

Because of the characteristics of maritime radar, there are many waves and non-clutter, and it is difficult to distinguish the target of the ship radar. That is, in the conventional case, when the ship radar signal processing is performed in a high clutter region, performance is degraded and a large amount of memory is required. That is, in the case of the conventional technique, the average value must be constantly calculated. In the case where there is no small target and Doppler shift, there is no effect of removing the clutter, and there is a problem that the search itself is difficult when the clutter is a high frequency clutter. Therefore, there is a need for a technique for classifying the type of clutter and removing the desired clutter if necessary.

In this embodiment, it is difficult to discriminate the target of the target because the wave radar generates a lot of wave clutter due to the characteristics of the marine radar. Therefore, it is possible to classify the type of clutter originating from the sea surface, There is a primary purpose in providing a method and apparatus for removing a sponge clutter.

According to an embodiment of the present invention, a database for matching and storing wave form information classified by wave height and related information according to the wave form information, and storing the information; An antenna for radiating an electromagnetic wave toward a target or a predetermined area and receiving a reflection signal reflected from the target or the predetermined area; A filtering unit for filtering the reflection signal according to a predetermined frequency; A calculation unit for calculating a specific coefficient based on the filtered signal; A comparison unit for extracting the wave shape information corresponding to the specific coefficient calculated from the database and extracting a threshold corresponding to the wave shape information; And a clutter removing unit for removing the clutter from the reflected signal by applying a value corresponding to the threshold value to the clutter canceling unit.

According to another aspect of the present invention, there is provided a data processing apparatus comprising: a database for storing waveform type information classified by wave height and matching information related to the wave type information; An antenna for radiating an electromagnetic wave toward a target or a predetermined area and receiving a reflection signal reflected from the target or the predetermined area; A zero velocity filter for filtering the velocity of the zero Doppler region in the reflected signal; A magnitude unit for identifying a magnitude corresponding to the filtered signal; A calculation unit for calculating a specific coefficient based on the identified signal; A comparison unit for extracting the wave shape information corresponding to the specific coefficient calculated from the database and extracting a threshold corresponding to the wave shape information; And a clutter removing unit for removing the clutter from the reflected signal by applying a value corresponding to the threshold value to the clutter canceling unit.

According to another aspect of the present invention, there is provided a receiving method comprising: a receiving step of radiating an electromagnetic wave toward a target or a predetermined area from an antenna and receiving a reflection signal reflected from the target or the predetermined area; A filtering step of filtering the reflection signal according to a predetermined frequency in a filtering unit; Calculating a specific coefficient based on the filtered signal in a calculation unit; An extracting step of extracting the wave form information corresponding to the specific coefficient calculated from the database by the comparator and extracting a threshold corresponding to the wave form information; And removing the sponge clutter by applying a value corresponding to the threshold value to the reflection signal in the clutter removal.

As described above, according to this embodiment, it is difficult to discriminate the target of the target from the ship radar because a large number of wave clutter occurs due to the characteristics of the sea. Therefore, it is necessary to classify the type of clutter originating from the sea surface, There is an effect that it can be removed according to.

1 is a block diagram schematically showing a device for removing sea surface clutters according to the present embodiment.
2 is a block diagram schematically showing a device for removing a sea surface clutter including a zero Doppler filter according to the present embodiment,
3 is an exemplary view for explaining an inner module in the sea surface clutter removal apparatus according to the present embodiment,
4 is an exemplary diagram for explaining a method of obtaining a frequency reflection speed using parameters according to the present embodiment,
5 is a block diagram schematically showing a device for removing a sea surface clutter including a zero velocity filter and a magnitude part according to the present embodiment.
6 is an exemplary diagram for explaining an improvement index level of a wave according to the present embodiment,
7 is a flowchart illustrating a method of removing a sea surface clutter according to an embodiment of the present invention.
8 is an exemplary diagram for explaining detection probabilities according to the present embodiment,
9 is an exemplary diagram for explaining a single pulse ambiguity function according to the present embodiment,
10 is an exemplary view for explaining a conventional method of removing a sea surface clutter,
11 is an exemplary view for explaining the removal of the sea surface clutter according to the present embodiment.

Hereinafter, the present embodiment will be described in detail with reference to the accompanying drawings.

The clutter described in this embodiment refers to a reflection obstacle such as an echo (reflex) caused by unwanted reflected waves generated from the ground, sea surface, raindrops, etc. in a radar. That is, the sea surface clutter is influenced by the wave height, the wind direction, and the height of the antenna, and the raindrop clutter is a noise phenomenon appearing on the screen under the influence of rainfall, snowfall, and mist.

1 is a block diagram schematically showing a device for removing a sea surface clutter according to the present embodiment.

The apparatus 100 for removing sea surface clutter according to the present embodiment includes an antenna 110, a filtering unit 120, a subtracting unit 130, a calculating unit 140, a comparing unit 150, a database 160, Removal unit 170. In this embodiment, the apparatus 100 for removing sea surface clutter includes an antenna 110, a filtering unit 120, a subtracting unit 130, a calculating unit 140, a comparing unit 150, a database 160, It should be understood that those skilled in the art may change or modify the embodiments without departing from the spirit and scope of the present invention. Various modifications and variations may be applied to the constituent elements included in the sponge-clutter removing apparatus 100.

The antenna 110 emits electromagnetic waves toward a target or a predetermined area and receives a reflected signal reflected from a target or a predetermined area. The antenna 110 emits an S-band of 3 GHz band or an X-band frequency of 10 GHz band.

The filtering unit 120 filters the reflected signal according to a predetermined frequency. The filtering unit 120 filters the zero Doppler frequency in the reflected signal or extracts the spectrum of the zero Doppler region including the harmonic component in the reflected signal, The envelope can be detected or the velocity of the zero Doppler region in the reflected signal can be filtered. Here, the zero Doppler region is a frequency region in which the object moves in a direction perpendicular to the direction of the radar beam, so that a Doppler signal is not generated.

The subtractor 130 subtracts the filtered signal and transmits the subtracted signal to the calculator 140. The subtractor 130 is a module that performs a subtraction function using a digital signal. The subtractor 130 can accept three inputs indicating the number of subtractions, the number of digits, and the number of digits, and outputs two outputs Can be exported. Further, the subtraction unit 130 expresses the difference in the number expressed by the input data as the output data. That is, the subtracting unit 130 outputs the difference between the number of senses to be inspected, the number of subtests, and the carry. That is, the subtractor 130 expresses the difference of the number of the filtered signal as output data as the output data, and matches the frequency of the reflected signal to the cell region of the frequency of the reflected signal. Also, the subtractor 130 may detect a square law applied to the filtered signal, and may check the magnitude corresponding to the filtered signal.

The calculation unit 140 calculates a specific coefficient based on the filtered signal. That is, the calculation unit 140 calculates the improvement index I and the frequency reflection speed V, which are specific coefficients. Here, the calculation unit 140 calculates the improvement index I by using Equation (1).

(I: improvement index, S: output signal, C: clutter)

That is, the improvement factor is a value obtained by dividing the output signal clutter power ratio of the clutter filter by the clutter filter input signal clutter power ratio. At this time, all target radial speeds are average. As described above, the improvement index evaluates the output signal as a radial velocity average of all possible targets. In this way, the ratio of the output to the input between the signal and the signal can give an average elimination gain. Thus, the improvement index can be defined as the ratio between input and output clutters.

On the other hand, the calculation unit 140 extracts the frequency reflection velocity V using the database 160. Here, the frequency reflection rate is as shown in [Table 1]. That is, the frequency reflection speed is the speed at which the frequency is reflected from the wave clutter.

That is, the improvement index I and the spectrum fluctuation through the calculating unit 140 will be described as follows. If I look at the improvement spectrum (I) when the object moves and the improvement rate (I) when the object moves at a high speed in the basic mode and the clutter spectrum which is the rate of emission from the target, the spectrum is small when the speed is low, The spectrum is large and the size of the improvement index is almost constant. That is, when the depression angle is small, the constant clutter spectrum is maintained without any change, but when the depression angle is increased to 80 °, the clutter spectrum has a constant frequency reflection rate of about 30 to 40 m / s.

The comparator 150 extracts wave form information corresponding to the specific coefficient calculated from the database 160 and extracts a threshold corresponding to the wave form information. That is, the comparator 150 extracts wave shape information corresponding to at least one of the improvement index I and the frequency reflection velocity V calculated from the database 160. The comparison unit 150 extracts a threshold value corresponding to the wave shape information extracted from the database 160.

Meanwhile, the comparison unit 150 may use a CFAR (Constant False Alarm Rate) algorithm. Here, the flow of the radar signal processing of the CFAR algorithm will be briefly described as follows. First, the downconversion signal is converted to a digital signal through an analog-to-digital conversion (ADC) to a baseband stage. At this time, the signals are classified by a certain angle through clutter estimation and digital beamforming. Time Domain signals coming into each beam or angle are converted into frequency domain signals through FFT (Fast Fourier Transform), and only the valid signals are adopted through the CFAR algorithm. Then, angle information is obtained through Amplitude Monopulse Process for the effective signal component, and angle, velocity, and distance information for multiple targets are extracted through pairing and frequency modulated continuous waveform (FMCW) processing do.

The CFAR algorithm is an environment adaptive filter that can extract only the valid signal reflected by the actual moving target from many clutter and noise signals generated on the sea surface. Therefore, when driving in a stationary target or clutter environment, all the clutter is removed by raising the valid signal threshold. In case of no clutter, , Thereby ensuring a wide dynamic range of signals.

The database 160 stores wave form information classified by wave height and related information according to wave form information and stores the information. Such a database may be implemented inside or outside of the sponge clutter removal device 100. Meanwhile, the related information stored in the database 160 may include at least one or more information among the wind speed information, the beam angle information of the antenna, the moving speed information of the ship, the reflection speed information according to the wave form information, . In addition, the wave form information stored in the database 160 may be a calm form, a smooth form, a Slight form, a Moderate form, a Rough form, a Very Rough form, A high type, a very high type, and a phenomenal type.

The status information and size information of the waves stored in the database 160 will be described as follows. Here, the wave condition can be represented by the standard size used in the ship by measuring the wave height as shown in [Table 2]. This state of the waves can be implemented based on the table used in the global weather organization. Wave condition conditions can be classified according to the Douglas Scale, the Hydrographic Office Scale, and the Beaufort Scale.

In Table 2, the wave form information is classified into about 9 wave form information, but it is not limited thereto.

The clutter removing unit 170 removes the sea surface clutter by applying a value corresponding to the threshold value received by the calculating unit 140 to the reflected signal.

2 is a block diagram schematically showing a device for removing a sea surface clutter including a zero Doppler filter according to the present embodiment.

The apparatus 100 for removing sea surface clutter according to the present embodiment includes an antenna 110, a Zero Doppler filter 210, a subtractor 130, a calculator 140, a comparator 150, (160) and a clutter removal unit (170). The sponge clutter removal apparatus 100 includes an antenna 110, a zero Doppler filter 210, a subtraction unit 130, a calculation unit 140, a comparison unit 150, a database 160, It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the appended claims. It is possible to apply various modifications and variations to the components included in the sponge-clutter removal apparatus 100 in the scope of the present invention.

The antenna 110, the subtractor 130, the calculator 140, the comparator 150, the database 160, and the clutter removal unit 170 are the same as those in FIG. 1, do. The zero Doppler filter 210 is preferably included in the filtering unit 120, but is not limited thereto. Here, the zero Doppler filter 210 filters the zero Doppler frequency in the reflected signal.

Hereinafter, a sponge clutter removal apparatus 100 including a zero Doppler filter 210 will be described. A general ship radar uses a method of removing the clutter in the analog signal area. The apparatus 100 for removing the sea surface clutter according to the present embodiment may apply the digital signal processing to remove the clutter by a desired level. Here, the magnetron system representing the analog processing system is a pulse radar system. The technique of removing clutter according to the level of the sea (sea level) and the level of rain (rain) through the radio wave that is transmitted by the transmitted radio wave is the gain offset of the STC (Sensitivity Time Control) GAIN Off-Set). On the other hand, the transmission pulse implementation technique uses a fixed type pulse waveform, is dependent on the magnetron method, and consumes high power. Such a signal processing technique performs simple comparison signal processing of a detected signal and has a distance resolution capability dependent on the pulse width. The magnetron signal processing method includes Matched Filter, Automatic Gain Control (AGC) and Quad Detection processing at the IF.

However, the digital signal processing method used in the apparatus 100 for removing sea surface clutter according to the present embodiment is a pulse compression radar system. Transmission pulse implementation technology utilizes digital frequency generation technology to form optimal pulse waveform, enable adaptive power design, and enable low power transmission with frequency bandwidth suitable for pulse compression. The implementation of this signal processor improves the resolution and resolution ability of the pulse compression signal processing technique using FPGA (Field-Programmable Gate Array) / DSP (Digital Signal Processor) and the pulse compression signal processing technique. That is, in this signal processing method, digital signals are processed in a digital signal processor after sampling by an IF digitizer, and matched filters, AGC, and quad detection processed by an analog receiver in a digital signal processor are digitally processed in a signal processor.

The signal processing is simplified through the sponge-clutter removing apparatus 100, the reliability is improved, and the maintenance is made easy. In addition, no analog adjustments are required, and all signal processing is possible by changing the numerical value of the parameter (Parameta). In addition, the sea surface clutter removal apparatus 100 calculates an output signal clutter ratio to the input signal clutter ratio in the logic for removing the desired wave clutter to calculate an application factor. At this time, the sponge clutter removal apparatus 100 calculates the reflection speed using parameters such as antenna beam angle (Azimuth / Depression) information, radar moving speed information, wind speed information, and the like.

In addition, when the sea level clutter removal apparatus 100 stores about 9 clutter levels in the database 160 in Table 2 and desires to remove a desired level of clutter using the data, .

The process of removing the clutter of the target level is performed by the sponge-clutter removing apparatus 100. The signal processing algorithm process includes a zero-Doppler filter 210, a subtractor 130, a comparator 150, The clutter removal unit 170 compares the frequency reflection rate of the clutter calculated by the calculation unit 140 with the data stored in the database 160 and applies a value corresponding to the threshold value. Table 3 compares the function of removing the sea surface clutter from the sea surface clutter removal apparatus 100 according to the present embodiment.

3 is an exemplary view for explaining an inner module in the sea surface clutter removal apparatus according to the present embodiment.

The apparatus for removing sea surface clutter 100 according to the present embodiment includes an envelope detector 310, a square law detector 320, a DMB (Data Matrix Bank) filter 330, a memory operation unit 340, a comparator 350 and a control level unit 360. [ In this embodiment, the sponge clutter removal apparatus 100 includes only the envelope detection unit 310, the square detector 320, the DMB filter 330, the memory operation unit 340, the comparator 350 and the control level unit 360 It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit and scope of the present invention. And various modifications and variations may be applied to the components included in the apparatus 100. [

The envelope detection unit 310 is preferably included in the filtering unit 120, but is not limited thereto. Here, the envelope detection unit 310 detects the spectral envelope of the zero Doppler region including the harmonic component in the reflected signal.

The square detector 320 is preferably implemented to be included in the subtraction unit 130, but is not limited thereto. The squared detector 320 detects the squared rule applied to the filtered signal, if any. In addition, the square detector 320 expresses the difference between the number of the filtered signals represented by the input data as output data, and matches the frequency of the reflected signal to the cell region of the frequency of the reflected signal.

The DMB filter 330, and the memory operation unit 340 may be included in the calculation unit 140, but the present invention is not limited thereto. The DMB filter 330 filters the corresponding cell of the frequency of the reflected signal matched to the cell region by the frequency of the reflected signal. The memory operation unit 340 calculates a specific coefficient based on the filtered signal. At this time, the memory operation unit 340 calculates the improvement index I and the frequency reflection speed V, which are specific coefficients. At this time, the memory operation unit 340 calculates the improvement index I using Equation (1). Also, the memory operation unit 340 extracts the frequency reflection velocity V using the database 160.

The comparator 350 and the control level unit 360 are preferably implemented to be included in the comparison unit 150, but are not limited thereto. The comparator 350 extracts a threshold corresponding to the wave form information extracted from the database 160. [ The control level unit 360 extracts wave shape information corresponding to at least one of the improvement index I and the frequency reflection velocity V calculated from the database 160.

4 is an exemplary diagram for explaining a method of obtaining a frequency reflection speed using parameters according to the present embodiment.

As shown in FIG. 4, the improvement index I of the clutter and the frequency reflection speed of the clutter are calculated using parameters such as the radar speed, the antenna speed, and the angle, . Such clutter data may be reflected in the data classified by the size of the waves shown in [Table 2], and the database 160 may be updated. That is, the sponge clutter removal apparatus 100 calculates the improvement index I of the receiving clutter and the frequency reflection speed V of the clutter, searches for a value present in the clutter, compares the value at the threshold, The level of the clutter can be determined.

5 is a block diagram schematically showing a device for removing a sea surface clutter including a zero velocity filter and a magnitude part according to the present embodiment.

The apparatus 500 for removing sea surface clutter according to the present embodiment includes a zero velocity filter 510, a magnitude unit 520, a memory operation unit 340, a comparator 350, and a control level unit 360. In this embodiment, it is described that the sponge-clutter removal apparatus 100 includes only the zero velocity filter 510, the magnitude unit 520, the memory operation unit 340, the comparator 350, and the control level unit 360 However, those skilled in the art will appreciate that the present invention is not limited to the description of the technical idea of the present embodiment and can be applied to the apparatus 100 for removing sponge clusters without departing from the intrinsic characteristics of the present embodiment And various modifications and variations may be applied to the included components.

The zero velocity filter 510 is preferably included in the filtering unit 120, but is not limited thereto. The zero velocity filter 510 filters the velocity of the zero Doppler region in the reflected signal. The magnitude unit 520 is preferably implemented to be included in the subtraction unit 130, but is not limited thereto. The magnitude section 520 identifies a magnitude corresponding to the filtered signal.

The memory operation unit 340 is preferably included in the calculation unit 140, but is not limited thereto. The memory operation unit 340 calculates a specific coefficient based on the filtered signal. At this time, the memory operation unit 340 calculates the improvement index I and the frequency reflection speed V, which are specific coefficients. At this time, the memory operation unit 340 calculates the improvement index I using Equation (1). Also, the memory operation unit 340 extracts the frequency reflection velocity V using the database 160.

The comparator 350 and the control level unit 360 are preferably implemented to be included in the comparison unit 150, but are not limited thereto. The comparator 350 extracts a threshold corresponding to the wave form information extracted from the database 160. [ The control level unit 360 extracts wave shape information corresponding to at least one of the improvement index I and the frequency reflection velocity V calculated from the database 160.

Hereinafter, the operation of the apparatus 100 for removing sea surface clutter shown in FIG. 5 will be described. 5, the values of the receiving cells passing through the zero velocity filter 510 and the magnitude unit 520 are divided into moving speed information of a radar corresponding to a cell, rotating speed information of an antenna, , The antenna speed information is calculated in the memory from the clutter improvement index (I) and the frequency reflection speed (V) of the cell, and the sponge clutter removal apparatus 100 calculates the level of the corresponding clutter, .

Here, the required storage requires a storage space size in which the level reference value is stored. If yn-1 (k) is the last evaluated value, Zn is the value input from the kth cell. This current evaluation value is expressed by Equation (2).

(Zn: display of input of Kth cell, W: unit of 0 to 1)

Where w is a weight between 0 and 1. On the other hand, if the failure detection probability is calculated, Equation (3) is obtained.

(α: elimination factor that will determine the failure probability, W: unit from 0 to 1)

On the other hand, the probability of the detector is calculated as shown in Equation (4).

(α: elimination factor that will determine the failure probability, W: unit from 0 to 1)

이다.here,

to be.

6 is an exemplary diagram for explaining the improvement index level of a wave according to the present embodiment.

The database 160 stores wave shape information classified by wave height and related information according to wave shape information, and stores the matched information. Such a database may be implemented inside or outside of the sponge clutter removal device 100. Meanwhile, the related information stored in the database 160 may include at least one or more information among the wind speed information, the beam angle information of the antenna, the moving speed information of the ship, the reflection speed information according to the wave form information, . In addition, the wave form information stored in the database 160 is divided into at least one of a calm form, a smooth form, a slight form, a normal form, a rough form, a very rough form, a high form, a very high form and a wonderful form.

As shown in FIG. 6, the database 160 can be applied by dividing the wave clutter removal classification matrix classified by the CCF (Clutter Cancellation Factor) into about nine levels (see [Table 2]). The sponge-clutter removal apparatus 100 divides the wave form information into about nine wave form information in the database 160 to remove the clutter, and the frequency reflection rate and the application coefficient And can be used as a parameter for extracting a threshold value.

7 is a flowchart for explaining a method of removing a sea surface clutter according to the present embodiment.

The sponge clutter removal apparatus 100 emits an electromagnetic wave toward a target or a predetermined region using the antenna 110 provided therein, and receives a reflection signal reflected from the target or a predetermined region (S710). In step S710, the sponge clutter removal apparatus 100 emits an X-band frequency of S-Band or 10 GHz band of 3 GHz band through antenna 110. The sponge clutter removal apparatus 100 filters the reflection signal according to a preset frequency using the filtering unit 120 (S720). In step S720, the sponge-clutter removal apparatus 100 performs filtering processing of the zero Doppler frequency in the reflected signal, detects the spectral envelope of the zero Doppler region including the harmonic component in the reflected signal, or detects the zero- Filtering processing can be performed.

The sponge-clutter removing apparatus 100 subtracts the filtered signal using the subtracting unit 130, and transmits the subtracted signal to the calculating unit 140 (S730). In step S730, the sponge-clutter removal apparatus 100 expresses the difference in the number of the filtered signal expressed by the input data as the output data, and matches the frequency of the reflected signal to the cell area of the frequency of the reflected signal. In addition, the sponge-clutter removal apparatus 100 can detect the square law applied to the filtered signal, or confirm the magnitude corresponding to the filtered signal. The sponge-clutter removal apparatus 100 calculates a specific coefficient based on the filtered signal using the calculation unit 140 (S740). In step S740, the sponge clutter removal apparatus 100 calculates the improvement index I and the frequency reflection speed V, which are specific coefficients. Here, the decalcification apparatus 100 may calculate the improvement index I using Equation (1) and extract the frequency reflection speed (V) using the database 160.

The sponge-clutter removal apparatus 100 extracts wave form information corresponding to a specific coefficient calculated from the database 160 using the comparison unit 150 (S750). In step S750, the sponge clutter removal apparatus 100 extracts wave form information corresponding to at least one of the improvement index I and the frequency reflection velocity V calculated from the database 160 provided. The sponge-clutter removal apparatus 100 extracts a threshold corresponding to the wave shape information from the database 160 using the comparison unit 150 (S760). In step S760, the sponge-clutter removal apparatus 100 extracts a threshold value corresponding to the wave shape information extracted from the database 160 provided. The sponge clutter removal apparatus 100 removes the sponge clutter by applying a value corresponding to the threshold value to the reflection signal using the clutter removal unit 170 (S770).

7, steps S710 to S770 are sequentially performed. However, this is merely an example of the technical idea of the present embodiment, and it will be apparent to those skilled in the art that the present invention is not limited to this embodiment It will be understood that various changes and modifications may be made to the invention without departing from the essential characteristics thereof, such as by changing the order described in FIG. 7 or by performing one or more of steps S710 through S770 in parallel, But is not limited thereto.

As described above, the method of removing the sea surface clutter according to the present embodiment described in Fig. 7 can be implemented by a program and recorded on a computer-readable recording medium. A program for implementing the method of removing a sea surface clutter according to the present embodiment is recorded, and a computer-readable recording medium includes all kinds of recording devices for storing data that can be read by a computer system. Examples of such computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, etc., and also implemented in the form of a carrier wave (e.g., transmission over the Internet) . The computer readable recording medium may also be distributed over a networked computer system so that computer readable code is stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the present embodiment can be easily inferred by programmers in the technical field to which the present embodiment belongs.

8 is an exemplary diagram for explaining detection probabilities according to the present embodiment.

When the parameters are used in the radar specification designed by applying the failure detection probability of Equation (3) and the detection probability of Equation (4) in the sponge-clutter removal apparatus 100, the detection probability is calculated 0.65 as detected.

At this time, the radar design specifications for the sponge clutter removal apparatus 100 are as shown in [Table 4]. In other words, the basic specification of radar which operates by Pulse Compression method of SSPA (Solid State Power Amplifier) radar of ship having performance of [Table 4] is applied.

9 is an exemplary diagram for explaining a single pulse ambiguity function according to the present embodiment.

The ambiguity analysis is performed in order to verify and analyze the resolution, the side lobe, the range for a given waveform, and the ambiguity of the Doppler, which are designed according to the present embodiment. That is, the specifications designed using the analysis tool for designing and analyzing simple characteristics of the propagation waveform together with the matched filter are shown in FIG.

10 is an exemplary view for explaining a conventional method of removing a sea surface clutter.

For example, the ambiguity is analyzed with a single LFM pulse ambiguity function by applying Doppler processing and ambiguity levels ranging from -40 ° to 40 ° to levels 1 to 1 and applying a delay to the time axis. As a result of ambiguity analysis of designed specifications, Doppler processing and matched filter show high accuracy. That is, using the verified radar specification, in this embodiment, the clutter is combined with the target, the matched filter is applied, the clutter is removed using the general clutter removal method, and the output is calculated using the output value output from the same matched filter The unit 140 searches the value obtained by calculating the improvement index I and the reflection speed V and the stored standard clutter value of the database 160. If the two values are greater than the threshold value, do. Here, as a result of simulation using a general clutter removal method, results as shown in FIG. 10 can be obtained.

11 is an exemplary view for explaining the removal of the sea surface clutter according to the present embodiment.

When the improvement index I and the frequency reflection speed V are calculated through the sponge clutter removal apparatus 100 according to the present embodiment and the clutter is removed, the result as shown in FIG. 11 can be obtained. That is, the standard data is stored in the database 160 in order to remove the desired clutter from the moving target, and the parameters are collected to calculate the improvement index (I) and the speed of the spectrum to calculate an applicable factor Apply the clutter removal level to that value. This is because it is easy to remove the clutter above the high sea level and the clutter which is the high frequency component can be removed at the same time.

That is, according to the present embodiment, since the improvement index I and the frequency reflection speed V are calculated and applied, it is possible to compare with the threshold value of the accurate clutter without consuming a lot of memory in order to continuously calculate the average value. This Doppler processing for clutter identification (Discrimination) can generate 4-32 filters. The performance index is shown in [Table 5].

In other words, in [Table 5], ship radar signal processing design for analysis of the algorithm suitable to the ship radar performance, signal ambiguity function analysis of vessel radar, algorithm Design, algorithm analysis, simulation, and performance comparison of the clutter removal method using the designed radar specification and the general clutter removal method can be confirmed.

The foregoing description is merely illustrative of the technical idea of the present embodiment, and various modifications and changes may be made to those skilled in the art without departing from the essential characteristics of the embodiments. Therefore, the present embodiments are to be construed as illustrative rather than restrictive, and the scope of the technical idea of the present embodiment is not limited by these embodiments. The scope of protection of the present embodiment should be construed according to the following claims, and all technical ideas within the scope of equivalents thereof should be construed as being included in the scope of the present invention.

100: Sponge clutter removal device
110: antenna 120: filtering unit
130: Subtraction unit 140:
150: comparison unit 160: database
170: Clutter removing unit 210: Zero Doppler filter
310: Envelope detection unit 320: Square detector
330: DMB filter 340: Memory operation unit
350: comparator 360: control level section
510: Zero Velocity Filter 520: Magnitude portion

Claims (21)

A database for storing wave shape information classified by wave height and matching information related to the wave shape information and storing the wave shape information;
An antenna for radiating an electromagnetic wave toward a target or a predetermined area and receiving a reflection signal reflected from the target or the predetermined area;
A filtering unit for filtering the reflection signal according to a predetermined frequency;
A calculation unit for calculating a specific coefficient based on the filtered signal;
A comparison unit for extracting the wave shape information corresponding to the specific coefficient calculated from the database and extracting a threshold corresponding to the wave shape information; And
And applying a value corresponding to the threshold value to the reflected signal to remove the sponge clutter,
Wherein the apparatus comprises: The method according to claim 1,
Wherein the filtering unit comprises:
And a zero Doppler filter for filtering the zero Doppler frequency in the reflected signal. 3. The method of claim 2,
Wherein the zero Doppler filter comprises:
And an envelope detector for detecting a spectral envelope of a zero Doppler region including a harmonic component in the reflected signal. 3. The method of claim 2,
Wherein the zero Doppler filter comprises:
And a zero velocity filter for filtering the velocity of the zero Doppler region in the reflected signal. The method according to claim 1,
Further comprising a subtractor for subtracting the filtered signal from the subtracted signal and for transmitting the subtracted signal to the calculator. 6. The method of claim 5,
Wherein,
Wherein a difference between the number of the filtered signals represented by the input data is represented by output data and a frequency of the reflected signal is matched to a cell region corresponding to a frequency of the reflected signal, Device. 6. The method of claim 5,
Wherein,
And a square law detector for detecting a square law applied to the filtered signal when the square law is applied to the filtered signal. 6. The method of claim 5,
Wherein,
And a magnitude unit for checking a magnitude corresponding to the filtered signal. The method according to claim 1,
The calculating unit calculates,
And a memory arithmetic unit for calculating the improvement index (I) and the frequency reflection speed (V) which are the specific coefficients. 10. The method of claim 9,
Wherein the memory arithmetic unit comprises:

(I: improvement index, S: output signal, C: clutter)
And the improvement index (I) is calculated by using the following equation. 10. The method of claim 9,
Wherein the memory arithmetic unit comprises:
Wherein the frequency reflection rate (V) is extracted using the database. 10. The method of claim 9,
Wherein,
A control level unit for extracting the wave shape information corresponding to at least one of the improvement index (I) and the frequency reflection velocity (V) calculated from the database; And
And a comparator for extracting a threshold value corresponding to the wave form information extracted from the database
Wherein the apparatus comprises: The method according to claim 1,
The above-
Wherein the information includes at least one of a velocity information of the wind, beam angle information of the antenna, moving velocity information of the ship, reflection velocity information according to the wave shape information, and standard deviation information according to the wave shape information. Clutter removal device. The method according to claim 1,
The wave form information includes:
Very Slow, Moderate, Rough, Very Rough, High, Very High, Slight, Slow, Rough, Wherein the at least one information is at least one of a shape, a shape, and a phenomenal shape. A database for storing wave shape information classified by wave height and matching information related to the wave shape information and storing the wave shape information;
An antenna for radiating an electromagnetic wave toward a target or a predetermined area and receiving a reflection signal reflected from the target or the predetermined area;
A zero velocity filter for filtering the velocity of the zero Doppler region in the reflected signal;
A magnitude unit for identifying a magnitude corresponding to the filtered signal;
A calculation unit for calculating a specific coefficient based on the identified signal;
A comparison unit for extracting the wave shape information corresponding to the specific coefficient calculated from the database and extracting a threshold corresponding to the wave shape information; And
And applying a value corresponding to the threshold value to the reflected signal to remove the sponge clutter,
Wherein the apparatus comprises: A receiving step of radiating an electromagnetic wave from the antenna toward a target or a predetermined area and receiving a reflection signal reflected from the target or the predetermined area;
A filtering step of filtering the reflection signal according to a predetermined frequency in a filtering unit;
Calculating a specific coefficient based on the filtered signal in a calculation unit;
Extracts the wave form information corresponding to the specific coefficient calculated from the database storing the wave form information classified by the wave height and the related information according to the wave form information in the comparison unit, An extraction process for extracting a threshold value for performing a filtering process; And
A removal process of removing the sponge clutter by applying a value corresponding to the threshold value to the reflection signal in the clutter removal,
Wherein the method comprises the steps of: 17. The method of claim 16,
The filtering process includes:
And filtering the zero Doppler frequency from the reflected signal by the filtering unit. 17. The method of claim 16,
Further comprising a process of subtracting the filtered signal from the subtracted signal and delivering the subtracted signal. 19. The method of claim 18,
The process comprises:
And a step of representing the difference of the number of the filtered signals by the output data in the subtraction unit as output data and matching the frequency of the reflected signal to a cell region of the frequency of the reflection signal Wherein the method comprises the steps of: 17. The method of claim 16,
The calculation process includes:
And calculating the improvement index (I) and the frequency reflection speed (V), which are the specific coefficients, in the calculation unit. 21. The method of claim 20,
Wherein the comparing comprises:
Extracting the wave form information corresponding to at least one of the improvement index (I) and the frequency reflection velocity (V) calculated from the database by the comparison unit; And
A step of extracting a threshold value corresponding to the wave form information extracted from the database by the comparison unit
Wherein the method comprises the steps of:

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