Radar clutter distribution tail modeling method, tail characteristic analysis method and device

Abstract

The present invention relates to the field of radar echo modeling technology, specifically a radar clutter distribution tail modeling method, tail characteristic analysis method, and device. By performing polynomial fitting on the probability density function of the clutter distribution tail, a polynomial model of the radar clutter distribution tail is constructed to accurately characterize the radar clutter distribution tail characteristic. The present invention has a simple structure and is easy to implement in engineering. Measured data has verified that the present invention has superior fitting results and can effectively improve the accuracy of the description of the clutter distribution tail characteristic.

Description

Technical Field

[0001] The present invention relates to the technical field of radar echo modeling, and in particular to a radar clutter distribution tail modeling method, a tail characteristic analysis method and a device. Background Art

[0002] During radar detection, clutter always accompanies target echoes. Its complex characteristics are a key factor limiting radar target detection performance. Accurate clutter modeling is a key factor in improving target detection performance. Amplitude statistical distribution is a key aspect of clutter modeling, reflecting the fluctuations in sea clutter echo amplitude and often described by a probability density function. For low-resolution radar clutter, its amplitude statistical distribution is often described by a Rayleigh distribution. As radar resolution increases or the radar grazing angle decreases, the clutter amplitude distribution tends to deviate from the Rayleigh distribution, exhibiting a significant heavy tail. Heavy tailing, defined as the slow decay at the far right end of the clutter amplitude distribution curve, is typically caused by factors such as multipath effects, complex scattering mechanisms, or specific environmental conditions. The presence of heavy tailing complicates modeling the statistical characteristics of the clutter amplitude distribution. For radar detection, the accuracy of the model fitting the probability density function of the tail portion of the clutter amplitude distribution is often more important than the global probability density function of the clutter amplitude distribution, directly impacting the accuracy of radar detection threshold setting.

[0003] In recent years, numerous researchers have devoted themselves to researching and solving the challenge of modeling heavy tailing in clutter amplitude distribution. This research can be broadly categorized into four directions: 1) designing and establishing a single-structure statistical distribution model with tailing characteristics; 2) designing and establishing a composite Gaussian distribution model; 3) designing and establishing a composite structural distribution model; and 4) designing and establishing an amplitude distribution tailing model. However, due to the significant differences in clutter amplitude distribution characteristics under different radar and environmental parameters, and the varying dynamic ranges and tailing levels of different models, a universal model currently does not exist to summarize existing amplitude distribution models. Existing models still fail to fully overcome their limitations in describing extreme heavy tailing, making it difficult to accurately characterize the tailing characteristics of radar clutter distributions. Summary of the Invention

[0004] The purpose of the present invention is to provide a radar clutter distribution tail modeling method, a tail characteristic analysis method and a device, which can establish a distribution tail polynomial model with both flexibility and convenience to accurately characterize the tail characteristics of radar clutter distribution.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A radar clutter distribution tail modeling method includes the following steps:

[0007] Extract radar clutter samples from radar echo data and construct radar clutter sample set ;

[0008] Radar clutter sample set For the reference data, calculate the empirical cumulative distribution function;

[0009] set up T value ， Get the empirical cumulative distribution function of the radar clutter sample set equal to T Radar clutter samples of ;

[0010] Select the radar clutter sample set that is larger than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set;

[0011] Radar clutter tail sample set For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value, ;

[0012] Construct a polynomial model of radar clutter tails:

[0013]

[0014] in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power;

[0015] The position and height of each histogram box in the statistical distribution histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

[0016] Furthermore, the present invention also includes evaluating the fitting effect of the polynomial model of radar clutter distribution tail on the radar clutter samples, and using the root mean square error as a description of the fitting effect of the polynomial model of radar clutter distribution tail, which is defined as:

[0017] .

[0018] In another aspect, a method for analyzing tail characteristics of radar clutter distribution is provided, comprising:

[0019] The above radar clutter distribution tail modeling method is used to obtain a polynomial model of radar clutter distribution tail;

[0020] Based on the polynomial model of radar clutter distribution tail, the clutter distribution tail characteristics of radar clutter data are obtained.

[0021] In another aspect, a radar clutter distribution tail modeling device is provided, comprising:

[0022] The first module is used to extract radar clutter samples from radar echo data and construct a radar clutter sample set ;

[0023] The second module is used to collect radar clutter samples For the reference data, calculate the empirical cumulative distribution function;

[0024] The third module is used to set T value ， Get the empirical cumulative distribution function of the radar clutter sample set equal to T Radar clutter samples of ;

[0025] The fourth module is used to select the radar clutter sample set that is greater than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set;

[0026] The fifth module is used to collect radar clutter tail samples For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value, ;

[0027] The sixth module is used to build a polynomial model for radar clutter tailing:

[0028]

[0029] in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power;

[0030] The seventh module is used to statistically distribute the position and height of each histogram box in the histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

[0031] In another aspect, a device for analyzing tail characteristics of radar clutter distribution is provided, comprising:

[0032] A model building module, configured to obtain a polynomial model of radar clutter distribution tails using the radar clutter distribution tail modeling method;

[0033] The tail characteristic analysis module is used to obtain the clutter distribution tail characteristic of the radar clutter data based on the polynomial model of the radar clutter distribution tail.

[0034] A device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0035] Extract radar clutter samples from radar echo data and construct radar clutter sample set ;

[0036] Radar clutter sample set For the reference data, calculate the empirical cumulative distribution function;

[0037] set up T value ， Get the empirical cumulative distribution function of the radar clutter sample set equal to T Radar clutter samples of ;

[0038] Select the radar clutter sample set that is larger than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set;

[0039] Radar clutter tail sample set For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value, ;

[0040] Construct a polynomial model of radar clutter tails:

[0041]

[0042] in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power;

[0043] The position and height of each histogram box in the statistical distribution histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

[0044] A storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0045] Extract radar clutter samples from radar echo data and construct radar clutter sample set ;

[0046] Radar clutter sample set For the reference data, calculate the empirical cumulative distribution function;

[0047] set up T value ， Get the empirical cumulative distribution function of the radar clutter sample set equal to T Radar clutter samples of ;

[0048] Select the radar clutter sample set that is larger than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set;

[0049] Radar clutter tail sample set For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value, ;

[0050] Construct a polynomial model of radar clutter tails:

[0051]

[0052] in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power;

[0053] The position and height of each histogram box in the statistical distribution histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

[0054] The beneficial effects of the present invention are:

[0055] By performing polynomial fitting on the probability density function (PDF) of the clutter distribution tail, a polynomial model of the radar clutter distribution tail is constructed. This invention has a simple structure and is easy to implement in engineering. Measured data has verified that this invention has a superior fitting effect and can effectively improve the accuracy of the description of the clutter distribution tail characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0057] Figure 1 This is a flow chart of a radar clutter distribution tail modeling method of the present invention;

[0058] Figure 2 A schematic diagram of radar echo data and clutter samples provided by an embodiment;

[0059] Figure 3 A graph showing the relationship between the empirical cumulative distribution function (ECDF) and amplitude values ​​of radar clutter samples provided in one embodiment;

[0060] Figure 4 A graph showing the relationship between the probability density function PDF of radar clutter tail samples and the clutter amplitude value provided by one embodiment;

[0061] Figure 5 A comparison chart of the probability density function (PDF) of the polynomial model provided in one embodiment and other models with the clutter sample;

[0062] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0065] The present invention provides a radar clutter distribution tail modeling method, specifically a radar clutter distribution tail modeling method based on polynomial fitting. The present invention can establish a distribution tail model that is both flexible and convenient to accurately characterize the tail characteristics of the radar clutter distribution.

[0066] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0067] like Figure 1 As shown, an embodiment provides a radar clutter distribution tail modeling method, comprising the following steps:

[0068] Extract radar clutter samples from radar echo data and construct radar clutter sample set ;

[0069] Radar clutter sample set For the reference data, calculate the empirical cumulative distribution function ;

[0070] set up T value ， Get the empirical cumulative distribution function of the radar clutter sample set Radar clutter samples ,in, ;

[0071] Select the radar clutter sample set that is larger than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set;

[0072] Radar clutter tail sample set For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value, ;

[0073] Construct a polynomial model of radar clutter tails:

[0074] (1)

[0075] in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power;

[0076] The position and height of each histogram box in the statistical distribution histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

[0077] In one embodiment, , the polynomial model of radar clutter tail is constructed as follows:

[0078] (2)

[0079] The position and height of each histogram box in the statistical distribution histogram As reference data, the least squares method is used to solve the polynomial model of radar clutter tailing. The process is as follows:

[0080] According to the least squares rule, Parameters The following relationship should be satisfied:

[0081] (3)

[0082] remember

[0083] (4)

[0084] but It's about The quaternion function of

[0085] Step 5.3: Make Parameters to obtain minimum value Should meet

[0086] (5)

[0087] So there is

[0088] (6)

[0089] That is

[0090] (7)

[0091] Solving equation (7), we get ,Sure ,but is the obtained polynomial model of radar noise tail.

[0092] In one embodiment, the method further includes evaluating the fitting effect of the polynomial model of the radar clutter distribution tail on the radar clutter samples, and using the root mean square error as a description of the fitting effect of the polynomial model of the radar clutter distribution tail, which is defined as:

[0093] (8)

[0094] In one embodiment, a method for analyzing tail characteristics of radar clutter distribution is provided, comprising:

[0095] The above radar clutter distribution tail modeling method is used to obtain a polynomial model of radar clutter distribution tail;

[0096] Based on the polynomial model of radar clutter distribution tail, the clutter distribution tail characteristics of radar clutter data are obtained.

[0097] In order to verify the effectiveness and practicality of the radar clutter distribution tail modeling method based on polynomial fitting provided by the present invention, this embodiment is further explained by combining the echo data recorded during the field test of the radar.

[0098] Figure 2 The radar echo data used in this embodiment is the actual echo data collected during the field test. The radar operating center frequency is 9.4 GHz, the transmitted signal is a linear frequency modulation signal, the bandwidth is 5 MHz, the pulse repetition frequency is 8 kHz, and the sampling rate is 10 MHz. The polarization mode is HV polarization, each distance unit is 15 m, and except for the distance unit where the target is located, the remaining units are clutter units. Extract the radar clutter amplitude sample, and record the clutter sample as . The clutter amplitude sample is taken Figure 2 The modulus of the radar echo complex data from the 20th to 230th range unit and the 260th to 480th range unit.

[0099] Figure 3 The empirical cumulative distribution function of the clutter amplitude sample selected in this embodiment is In order to highlight the tail part of the clutter amplitude sample, the vertical axis is selected with Expressed and described in logarithmic coordinates. Figure 3 The gray dashed line is , its corresponding .at the same time, Figure 3The classical model and the empirical cumulative distribution function of radar clutter amplitude samples are shown in It can be noted that, in general, the gamma distribution model has a better fitting effect than other classical models. When , several classic models such as the gamma distribution model can fit the measured data clutter amplitude distribution well. However, when When , there is a large deviation between the gamma distribution model and the measured data clutter amplitude distribution.

[0100] Figure 4 The radar clutter amplitude tailing sample probability density function of this embodiment is A plot of the relationship between the radar clutter and the amplitude. Medium to large The samples are radar clutter tail samples .remember Figure 4 The horizontal coordinate of the sample data point is , the vertical axis is , the width between two data points , is the number of data points. Figure 4 The classical model and the radar clutter amplitude tailing sample probability density function are shown in It can be noted that, from the perspective of fitting effect, the exponential distribution model has a better fitting effect than other classic models. When , the probability density function of the tail amplitude estimated by the exponential distribution model is It is obviously lower than the measured data, and it fails to accurately describe the heavy-tailing characteristics of the amplitude distribution.

[0101] Figure 5 The probability density function of the polynomial model of this embodiment and other classical models with the clutter tail sample is Comparison chart of polynomial model. Establish according to step 5. According to the least squares rule, satisfy Parameters of relationships for , , , .

[0102] Table 1 summarizes the polynomial model and other models of this embodiment and the measured clutter amplitude distribution tailing probability density function The root mean square error (RMS) is used to evaluate how well a polynomial model fits a sample. The lower the RMS error, the better the model fit. The polynomial model has the lowest RMS error. The polynomial model obtained by the polynomial fitting-based radar clutter distribution tail modeling method disclosed in this invention more accurately describes the measured clutter distribution tail.

[0103] Table 1 Root mean square error of polynomial model

[0104]

[0105] In one embodiment, a radar clutter distribution tail modeling device is provided, the device comprising:

[0106] The first module is used to extract radar clutter samples from radar echo data and construct a radar clutter sample set ;

[0107] The second module is used to collect radar clutter samples For the reference data, calculate the empirical cumulative distribution function ;

[0108] The third module is used to set T value ， Get the empirical cumulative distribution function of the radar clutter sample set Radar clutter samples ;

[0109] The fourth module is used to select the radar clutter sample set that is greater than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set;

[0110] The fifth module is used to collect radar clutter tail samples For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value, ;

[0111] The sixth module is used to build a polynomial model for radar clutter tailing:

[0112]

[0113] in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power;

[0114] The seventh module is used to statistically distribute the position and height of each histogram box in the histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

[0115] In one embodiment, a device for analyzing tail characteristics of radar clutter distribution is provided, comprising:

[0116] A model building module, configured to obtain a polynomial model of radar clutter distribution tails using the radar clutter distribution tail modeling method;

[0117] The tail characteristic analysis module is used to obtain the clutter distribution tail characteristic of the radar clutter data based on the polynomial model of the radar clutter distribution tail.

[0118] In one embodiment, a device, which may be a server, is provided. The device includes a processor, memory, a grid interface, and a database connected via a system bus. The processor of the device provides computing and control capabilities. The memory of the device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and computer program in the non-volatile storage medium to run. The database of the device stores data used in radar clutter distribution tail modeling. The grid interface of the device communicates with an external terminal via a grid connection. When executed by the processor, the computer program implements a radar clutter distribution tail modeling method.

[0119] Those skilled in the art will understand that the description of the technical features of the equipment in the above embodiments does not constitute a limitation on all equipment to which the present invention is applied. The specific equipment may include more or fewer components, or combine certain components, or have different component arrangements.

[0120] In one embodiment, a storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0121] Extract radar clutter samples from radar echo data and construct radar clutter sample set ;

[0122] Radar clutter sample set For the reference data, calculate the empirical cumulative distribution function ;

[0123] set up T value ， Get the empirical cumulative distribution function of the radar clutter sample set Radar clutter samples ;

[0124] Select the radar clutter sample set that is larger than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set;

[0125] Radar clutter tail sample set For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value, ;

[0126] Construct a polynomial model of radar clutter tails:

[0127]

[0128] in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power;

[0129] The position and height of each histogram box in the statistical distribution histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

[0130] Those skilled in the art will understand that all or part of the processes of the above-mentioned embodiment methods can be implemented by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods.

[0131] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. A radar clutter distribution tail modeling method, characterized in that: The method comprises the following steps: Extract radar clutter samples from radar echo data and construct radar clutter sample set ; Radar clutter sample set For the reference data, calculate the empirical cumulative distribution function; set up T value ， Get the empirical cumulative distribution function of the radar clutter sample set equal to T Radar clutter samples of ; Select the radar clutter sample set that is larger than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set; Radar clutter tail sample set For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value; Construct a polynomial model of radar clutter tails: in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power; The position and height of each histogram box in the statistical distribution histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

2. The radar clutter distribution tail modeling method according to claim 1, characterized in that: It also includes the evaluation of the fitting effect of the polynomial model of radar clutter distribution tail on the radar clutter samples. The root mean square error is used as the description of the fitting effect of the polynomial model of radar clutter distribution tail, which is defined as: 。 3. The radar clutter distribution tail modeling method according to claim 1, characterized in that: The radar clutter samples are radar clutter amplitude data.

4. The radar clutter distribution tail modeling method according to claim 1, characterized in that: described .

5. The radar clutter distribution tail modeling method according to claim 1, characterized in that: The histogram bin width ,in, is the interquartile range.

6. A method for analyzing the tailing characteristics of radar clutter distribution, characterized in that: include: A polynomial model of radar clutter distribution tail is obtained by adopting the radar clutter distribution tail modeling method according to any one of claims 1 to 5; Based on the polynomial model of radar clutter distribution tail, the clutter distribution tail characteristics of radar clutter data are obtained.

7. A radar clutter distribution tail modeling device, characterized in that: include: The first module is used to extract radar clutter samples from radar echo data and construct a radar clutter sample set ; The second module is used to collect radar clutter samples For the reference data, calculate the empirical cumulative distribution function; The third module is used to set T value ， Get the empirical cumulative distribution function of the radar clutter sample set equal to T Radar clutter samples of ; The fourth module is used to select the radar clutter sample set that is greater than The radar clutter samples are used as radar clutter tail samples to obtain the radar clutter tail sample set ,Right now , ,in, is the number of radar clutter tail samples in the radar clutter tail sample set; The fifth module is used to collect radar clutter tail samples For reference data, a statistical distribution histogram is established, where the histogram box width is , No. j Histogram bin height It is recorded as the logarithmic probability density function PDF, that is, j The vertical height of the histogram bins , ,in, For the j The number of radar clutter tail samples in a histogram bin, is the number of histogram bins, j The horizontal coordinates of the histogram bins are marked as , Characterize the clutter amplitude value, ; The sixth module is used to build a polynomial model for radar clutter tailing: in The K parameters to be determined in the polynomial model representing the radar clutter tail are: is the clutter amplitude value, for of power; The seventh module is used to statistically distribute the position and height of each histogram box in the histogram As reference data, the least square method is used to solve the polynomial model of radar clutter tail.

8. Radar clutter distribution tail characteristics analysis device, characterized in that: include: A model building module, configured to obtain a polynomial model of radar clutter distribution tails using the radar clutter distribution tail modeling method according to any one of claims 1 to 5; The tail characteristic analysis module is used to obtain the clutter distribution tail characteristic of the radar clutter data based on the polynomial model of the radar clutter distribution tail.

9. A device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the radar clutter distribution tail modeling method according to any one of claims 1 to 5 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the radar clutter distribution tail modeling method according to any one of claims 1 to 5 are implemented.

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