A Constant False Alarm Rate Detection Method for Ship Targets in SAR Images

Abstract

The invention discloses a SAR image ship target constant false alarm rate detection method, comprising: obtaining a SAR image to be detected and corresponding external parameters; obtaining a sea surface backscatter coefficient based on the SAR image to be detected and the external parameters; obtaining a target signal-to-clutter ratio based on the sea surface backscatter coefficient; obtaining a detection threshold based on the target signal-to-clutter ratio; obtaining a sea surface backscatter coefficient distribution probability density based on the sea surface backscatter coefficient; obtaining a constant false alarm rate value based on the sea surface backscatter coefficient distribution probability density and the detection threshold; and obtaining a ship target image coordinate value based on the constant false alarm rate value and the SAR image to be detected. The detection efficiency and detection accuracy of the ship target are improved by accurately setting the constant false alarm rate.

Description

Technical Field

[0001] The invention relates to the technical field of SAR image target detection, and more particularly to a SAR image ship target constant false alarm rate detection method. Background Art

[0002] At present, ship target detection in synthetic aperture radar (SAR) images is a typical application scenario of radar signal detection. First, a suitable distribution model is used to describe sea clutter, and then the detection thresholds of different areas are adaptively obtained through the clutter model and the given constant false alarm probability. From the principle of the constant false alarm rate detection algorithm, it can be seen that the clutter model and the set false alarm probability value determine the final target detection performance of the ship detection system.

[0003] However, in the engineering system of actual application, a false alarm probability value is generally given based on experience or test data test results, and the sea clutter distribution model (such as distribution model) to be adopted is selected. In the detection process, the actual SAR image is used to solve the specific parameters of the probability density of the clutter background distribution, and finally the detection threshold is obtained. However, the traditional K distribution, distribution and other models are not well applicable to the wide range of incident angles. In particular, with the improvement of SAR load capacity, the local incident angles at different positions on the same SAR image can also cover low, medium and high ranges. Therefore, a single sea clutter model no longer meets the needs of SAR image ship detection.

[0004] In order to reduce the impact of local incident angle on system robustness, technicians proposed a clutter distribution model based on sea surface physical scenes (such as a dual-scale model). This model takes the sea surface physical scene as input and considers the sea surface scattering law under a large span of incident angles. However, the model requires more parameters when designing, which makes its solution process complicated. Specifically, it is necessary to design a larger detector sliding window; ② It is necessary to read more clutter data for solving the background distribution probability density; ③ The complexity of solving the distribution probability density will increase exponentially. In engineering systems, this will have a greater impact on detection efficiency.

[0005] The most widely used two-scale sea surface scattering model (TSM) is a combination of the quasi-specular scattering model and the composite surface Bragg scattering model. However, the design of this type of model is cumbersome and the parameter solution is complex. In actual application systems, the target detection efficiency is poor and it is difficult to meet the requirements of real-time detection.

[0006] Therefore, how to accurately set the constant false alarm rate to improve the efficiency and accuracy of ship target detection is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0007] In view of this, the present invention provides a constant false alarm rate detection method for ship targets in SAR images, which improves the detection efficiency and detection accuracy of ship targets by accurately setting the constant false alarm rate.

[0008] In order to achieve the above object, the present invention adopts the following technical solution:

[0009] A method for detecting ship targets with a constant false alarm rate in a SAR image, comprising:

[0010] Obtain the SAR image to be detected and the corresponding external parameters;

[0011] Obtaining a sea surface backscatter coefficient based on the SAR image to be detected and the external parameters;

[0012] Obtaining a target signal-to-clutter ratio based on the sea surface backscatter coefficient;

[0013] Obtaining a detection threshold based on the target signal-to-noise ratio;

[0014] Obtaining a sea surface backscatter coefficient distribution probability density based on the sea surface backscatter coefficient;

[0015] Obtaining a constant false alarm rate value based on the sea surface backscatter coefficient distribution probability density and the detection threshold;

[0016] The coordinate value of the ship target image is obtained based on the constant false alarm rate value and the SAR image to be detected.

[0017] Preferably, the external parameters include: wind direction information, scattering coefficient, Fresnel reflection coefficient at vertical incidence and average backscattering coefficient of ship target.

[0018] Preferably, the method for obtaining the sea surface backscatter coefficient is:

[0019] Obtaining a radar image incident angle based on the SAR image;

[0020] Obtaining a quasi-specular scattering GO component based on the radar image incident angle and the wind direction information;

[0021] Obtaining a first-order Bragg resonance scattering component based on the radar image incident angle and the scattering coefficient;

[0022] Based on the quasi-specular scattering GO component and the first-order Bragg resonant scattering component The sea surface backscatter coefficient σ(θ) corresponding to the incident angle of the radar image is obtained:

[0023]

[0024] Preferably, the method for obtaining the quasi-specular scattering GO component is:

[0025] Based on the wind direction information, respectively obtain the upwind slope and the crosswind slope;

[0026] Obtaining a slope probability density of a mirror point based on the upwind slope and the crosswind slope;

[0027] The quasi-specular scattering GO component is obtained based on the slope probability density of the mirror point and the incident angle of the radar image

[0028]

[0029] Among them, p(ζ x' ,ζ y' ) represents the slope probability density of the mirror point, ζ x' represents the upwind slope, ζ y' represents the crosswind slope, θ represents the incident angle of the radar image, and R represents the Fresnel reflection coefficient at vertical incidence.

[0030] Preferably, the first-order Bragg resonance scattering component for:

[0031]

[0032] Among them, g qp represents the scattering coefficient, K represents the wave number size, and W(·) represents the two-dimensional wave number spectrum with folding symmetry.

[0033] Preferably, the target signal-to-noise ratio is:

[0034] SCR(θ)=RCS Ship -σ(θ)

[0035] Where SCR(θ) represents the target signal-to-clutter ratio, RCS Ship Represents the average backscatter coefficient of the ship target.

[0036] Preferably, the detection threshold is:

[0037] T(θ)=SCR(θ)-N ship

[0038] N ship =RMSE(RCS Ship )

[0039] Where T(θ) represents the detection threshold, N ship It represents the mean square error of the average backscatter coefficient of the ship target, and RMSE(·) represents the mean square error operation.

[0040] Preferably, the sea surface backscatter coefficient distribution probability density is specifically:

[0041]

[0042] Where x represents the pixel amplitude of the SAR image to be detected.

[0043] Preferably, the constant false alarm rate value is specifically:

[0044]

[0045] Among them, P fa (θ) represents the constant false alarm rate value.

[0046] A SAR image ship target constant false alarm rate detection system, comprising: a data acquisition module, a detection threshold acquisition module, a constant false alarm rate value acquisition module and a result output module;

[0047] The data acquisition module is used to acquire the SAR image to be detected and the corresponding external parameters;

[0048] The detection threshold acquisition module is used to obtain a sea surface backscatter coefficient based on the SAR image to be detected and the external parameters; obtain a target signal-to-clutter ratio based on the sea surface backscatter coefficient; and obtain a detection threshold based on the target signal-to-clutter ratio;

[0049] The constant false alarm rate value acquisition module is used to obtain the sea surface backscatter coefficient distribution probability density based on the sea surface backscatter coefficient; and obtain the constant false alarm rate value based on the sea surface backscatter coefficient distribution probability density and the detection threshold;

[0050] The result output module is used to obtain the image coordinate value of the ship target based on the constant false alarm rate value and the SAR image to be detected.

[0051] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a method for detecting ship targets in constant false alarm rate in SAR images. Based on the sea surface scattering model, statistical analysis is performed on the external parameters of the radar image to obtain reasonable preset values ​​of the constant false alarm rate of the target under different local incident angles. The coordinate value of the ship target image is obtained based on the preset value of the constant false alarm rate, thereby realizing rapid and accurate detection of ship targets in radar images, and having the following beneficial effects:

[0052] 1. The scattering modeling for the physical scene of the sea surface is realized. The reasonable value of the preset false alarm rate is analyzed by using the backscattering characteristics of the sea surface radar under different local incident angles, and the reasonable preset false alarm rate under different local incident angles is obtained, which ensures the detection robustness of this method under different incident angles.

[0053] 2. The present invention adopts a relatively simple method to describe the sea surface radar backscattering without considering the influence of the local incident angle, thereby reducing the number of parameters for solving the probability density of the clutter background distribution during the detection process and improving the system detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0055] Figure 1 The present invention provides a flow chart of a method for detecting ship targets in SAR images using a constant false alarm rate.

[0056] Figure 2 The SAR image obtained by the GF-3 satellite provided by the present invention.

[0057] Figure 3 The present invention provides a schematic diagram of a curve showing a change in the backscatter coefficient of the sea surface with the incident angle.

[0058] Figure 4 This is a schematic diagram of a curve showing how the detection threshold value provided by the present invention changes with the incident angle.

[0059] Figure 5 This is a schematic diagram of the detection results of the traditional method provided by the present invention under a fixed detection threshold of 15.7dB.

[0060] Figure 6 This is a flow chart of the traditional CFAR detection method provided by the present invention.

[0061] Figure 7 This is a schematic diagram of the detection results of the traditional method provided by the present invention under a fixed detection threshold of 13dB.

[0062] Figure 8 A schematic diagram of the detection results of changing the preset false alarm rate of the method provided by the present invention.

[0063] Fig. 9 The present invention provides a structural schematic diagram of a SAR image ship target constant false alarm rate detection system. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0065] Example 1

[0066] The purpose of radar signal detection is to determine whether a target exists in an area with interference or clutter. In the radar automatic detection system, a detection threshold needs to be provided, and then a decision on whether a target exists is made based on the decision criteria. The Constant False Alarm Rate (CFAR) detection algorithm is a signal processing algorithm that provides a threshold for the detection strategy in the radar automatic detection system and minimizes the impact of clutter and interference on the false alarm probability of the system. The determination of the threshold is related to the clutter model and the preset constant false alarm rate.

[0067] For a given SAR image, two factors determine the performance of the system in ship detection: 1) whether it can accurately describe the backscattering characteristics of the sea surface in all scenes; and 2) how to reasonably set the constant false alarm rate.

[0068] Based on this, Figure 1 As shown, the embodiment of the present invention discloses a method for detecting a ship target with a constant false alarm rate in a SAR image, comprising:

[0069] Obtain the SAR image to be detected and the corresponding external parameters;

[0070] The sea surface backscatter coefficient is obtained based on the SAR image to be detected and the external parameters;

[0071] The target signal-to-clutter ratio is obtained based on the sea surface backscatter coefficient;

[0072] The detection threshold is obtained based on the target signal-to-noise ratio;

[0073] Based on the sea surface backscatter coefficient, the probability density of the sea surface backscatter coefficient distribution is obtained;

[0074] The constant false alarm rate value is obtained based on the probability density of the sea surface backscatter coefficient distribution and the detection threshold;

[0075] The image coordinates of the ship target are obtained based on the constant false alarm rate value and the SAR image to be detected.

[0076] Example 2

[0077] The embodiment of the present invention discloses a method for detecting a ship target with a constant false alarm rate in a SAR image, comprising:

[0078] Get the SAR image to be detected and the corresponding external parameters:

[0079] Preferably, this embodiment can obtain various radar images including SAR images for subsequent analysis and processing.

[0080] Preferably, the external parameters include: wind direction information, scattering coefficient, Fresnel reflection coefficient at vertical incidence and average backscattering coefficient of ship target.

[0081] Preferably, wind direction information is obtained through public data on the meteorological satellite network; the scattering coefficient of this embodiment adopts the scattering coefficient of the wave, which is obtained by looking up a table and is a known quantity; this embodiment adopts the Fresnel reflection coefficient at vertical incidence on the water surface, which is obtained by looking up a table and is a known quantity; the average backscattering coefficient of the ship target is an empirical value, which is related to the ship model, and the average backscattering coefficient of the ship target is obtained based on the ship model.

[0082] The sea surface backscatter coefficient is obtained based on the SAR image to be detected and the external parameters:

[0083] Preferably, the method for obtaining the sea surface backscatter coefficient is:

[0084] Obtaining the incident angle of the radar image based on the SAR image;

[0085] The quasi-specular scattering GO component is obtained based on the incident angle and wind direction information of the radar image;

[0086] The first-order Bragg resonance scattering component is obtained based on the incident angle and scattering coefficient of the radar image;

[0087] Based on quasi-specular scattering GO component and the first-order Bragg resonant scattering component The sea surface backscatter coefficient σ(θ) corresponding to the incident angle of the radar image is obtained:

[0088]

[0089] Preferably, It is a dual-scale electromagnetic scattering model, which is used to calculate the sea surface backscattering coefficient corresponding to different incident angles.

[0090] Preferably, the method for obtaining the quasi-specular scattering GO component is:

[0091] Based on the wind direction information, the upwind slope and the crosswind slope are obtained respectively;

[0092] The slope probability density of the mirror point is obtained based on the upwind slope and the crosswind slope;

[0093] The quasi-specular scattering GO component is obtained based on the slope probability density of the mirror point and the incident angle of the radar image

[0094]

[0095] Among them, p(ζ x' ,ζ y' ) represents the slope probability density of the mirror point, ζ x' represents the upwind slope, ζ y' represents the crosswind slope, θ represents the incident angle of the radar image, and R represents the Fresnel reflection coefficient at vertical incidence.

[0096] Preferably, the first-order Bragg resonance scattering component for:

[0097]

[0098] Among them, g qp represents the scattering coefficient, K represents the wave number size, and W(·) represents the two-dimensional wave number spectrum with folding symmetry.

[0099] Preferably, the present invention adopts a relatively simple method to describe the sea surface radar backscattering without considering the influence of the local incident angle, thereby reducing the number of parameters for solving the probability density of the clutter background distribution during the detection process and improving the detection efficiency of the system.

[0100] The target signal-to-clutter ratio is obtained based on the sea surface backscatter coefficient:

[0101] Preferably, the target signal-to-noise ratio is:

[0102] SCR(θ)=RCS Ship -σ(θ)

[0103] Where SCR(θ) represents the target signal-to-clutter ratio, RCS Ship Represents the average backscatter coefficient of the ship target.

[0104] The detection threshold is obtained based on the target signal-to-noise ratio:

[0105] Preferably, considering the fluctuation of the backscatter value of the target, the detection threshold is:

[0106] T(θ)=SCR(θ)-N ship

[0107] N ship =RMSE(RCS Ship )

[0108] Where T(θ) represents the detection threshold, N ship It represents the mean square error of the average backscatter coefficient of the ship target, and RMSE(·) represents the mean square error operation.

[0109] Based on the sea surface backscatter coefficient, the probability density of the sea surface backscatter coefficient distribution is obtained:

[0110] Preferably, the probability density of the sea surface backscatter coefficient distribution is specifically:

[0111]

[0112] Where x represents the SAR image pixel amplitude.

[0113] The constant false alarm rate value is obtained based on the probability density of the sea surface backscatter coefficient distribution and the detection threshold:

[0114] Preferably, the constant false alarm rate value is specifically:

[0115]

[0116] Among them, P fa (θ) represents the constant false alarm rate value.

[0117] Based on the constant false alarm rate value and the SAR image to be detected, the image coordinate value of the ship target is obtained:

[0118] Preferably, a constant false alarm rate detection method is used to perform ship target detection on the SAR image to be detected, and the target position is detected by comparing whether the grayscale of each image pixel exceeds the constant false alarm rate one by one, and the coordinate value of the ship target image is obtained, thereby realizing ship target detection.

[0119] Preferably, the constant false alarm rate value P fa (θ) is brought into the traditional constant false alarm rate detection method, and the Gaussian distribution probability density p'(x) is obtained based on the pixel amplitude mean μ and standard deviation α of the SAR image to be detected:

[0120]

[0121] The conversion relationship between the Gaussian distribution probability density p'(x) and the standard normal distribution table is:

[0122]

[0123] Among them, Φ(T') represents the standard normal distribution table, T' represents the judgment threshold, X represents the random variable of the pixel value of the SAR image to be detected, P(X≤T') represents the probability of X≤threshold, t represents the integral variable, It represents the Gaussian distribution probability density p'(x) with a pixel amplitude mean μ of 0 and a standard deviation α of 1.

[0124] The judgment threshold T' is obtained through the standard normal distribution table. The previous step gives the false alarm rate P fa , and Φ(T') in the previous formula has proved that P fa=1-Φ(T'), so we can get the value of Φ(T') = 1-P fa , and then find the judgment threshold T' corresponding to the Φ(T') value according to the distribution table.

[0125] Find the value that matches 1-P in the standard normal distribution table. fa (θ) The T' corresponding to the same value is used as the judgment threshold T';

[0126] like This means that the pixel corresponding to the center of the sliding window of the SAR image to be detected is the target of the ship.

[0127] Label, otherwise it is background;

[0128] Repeat the above steps until all pixels of the SAR image to be detected are judged, and the final ship target detection result is obtained and marked and displayed.

[0129] Example 3

[0130] This embodiment uses SAR image data acquired by the GF-3 satellite scanning mode to simulate and verify the method of the present invention:

[0131] like Figure 2 As shown, the acquired SAR image has a width of 300 km and an incident angle ranging from 31° to 48°. Using the dual-scale electromagnetic scattering model of the present invention, as shown in FIG. Figure 3 As shown, the curve of the change of the sea surface backscattering coefficient with the incident angle is obtained. The figure shows that the larger the incident angle, the smaller the sea surface backscattering coefficient. The difference between the sea surface backscattering coefficient at the incident angle of 31° and the incident angle of 48° is nearly 15dB.

[0132] The average backscatter coefficient of the ship target corresponding to the ship to be detected is set based on the ship backscatter coefficient. The backscatter coefficient of the ship is fixed, but the signal-to-clutter ratio changes due to the change of the clutter background with the incident angle, so the detection threshold changes, such as Figure 4 As shown, the detection threshold is between 13dB and 18dB at incident angles of 31° to 48°.

[0133] In this SAR image, 100 ships are randomly distributed and the detection threshold is set to 15.7 dB according to the traditional CFAR method. A large number of ships are missed in the near-end viewing angle. The detection results are shown in the figure below. Figure 5 shown.

[0134] The traditional CFAR method requires that the target has a strong contrast with the background when applied. The system detects the target by comparing the grayscale of each pixel one by one to see if it exceeds a certain threshold value. The method flow chart is as follows: Figure 6 shown.

[0135] The fixed detection threshold is set to 13dB. Although the target is not missed, a large number of false alarms are generated. The detection results are as follows: Figure 7 shown.

[0136] By using the method of the present invention to change the detection threshold for detection, all targets are detected, and there is no obvious increase in false alarms. The detection results are as follows Figure 8 shown.

[0137] It can be seen from the above results that, compared with the traditional CFAR method, the method of the present invention can significantly improve the target detection performance by adjusting the preset value of the false alarm rate under different local incident angles through the modeling and analysis results of the sea surface scattering characteristics.

[0138] Example 4

[0139] like Fig. 9 As shown, a SAR image ship target constant false alarm rate detection system includes: a data acquisition module, a detection threshold acquisition module, a constant false alarm rate value acquisition module and a result output module;

[0140] A data acquisition module is used to acquire the SAR image to be detected and the corresponding external parameters;

[0141] A detection threshold acquisition module is used to obtain a sea surface backscatter coefficient based on the SAR image to be detected and external parameters; obtain a target signal-to-clutter ratio based on the sea surface backscatter coefficient; and obtain a detection threshold based on the target signal-to-clutter ratio;

[0142] A constant false alarm rate value acquisition module is used to obtain a probability density of a sea surface backscatter coefficient distribution based on the sea surface backscatter coefficient; and obtain a constant false alarm rate value based on the probability density of a sea surface backscatter coefficient distribution and a detection threshold;

[0143] The result output module is used to obtain the image coordinate value of the ship target based on the constant false alarm rate value and the SAR image to be detected.

[0144] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a method for detecting ship targets in constant false alarm rate in SAR images. Based on the sea surface scattering model, statistical analysis is performed on the external parameters of the radar image to obtain reasonable preset values ​​of the constant false alarm rate of the target under different local incident angles. The coordinate value of the ship target image is obtained based on the preset value of the constant false alarm rate, thereby realizing rapid and accurate detection of ship targets in radar images, and having the following beneficial effects:

[0145] 1. The scattering modeling for the physical scene of the sea surface is realized. The reasonable value of the preset false alarm rate is analyzed by using the backscattering characteristics of the sea surface radar under different local incident angles, and the reasonable preset false alarm rate under different local incident angles is obtained, which ensures the detection robustness of this method under different incident angles.

[0146] 2. The present invention adopts a relatively simple method to describe the sea surface radar backscattering without considering the influence of the local incident angle, thereby reducing the number of parameters for solving the probability density of the clutter background distribution during the detection process and improving the system detection efficiency.

[0147] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0148] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting ship targets with constant false alarm rate in SAR images, characterized in that: include: Obtain the SAR image to be detected and the corresponding external parameters; Obtaining a sea surface backscatter coefficient based on the SAR image to be detected and the external parameters; The method for obtaining the sea surface backscatter coefficient is: Obtaining a radar image incident angle based on the SAR image; Obtaining a quasi-specular scattering GO component based on the incident angle and wind direction information of the radar image; Obtaining a first-order Bragg resonance scattering component based on the radar image incident angle and scattering coefficient; Based on the quasi-specular scattering GO component and the first-order Bragg resonant scattering component The sea surface backscatter coefficient σ(θ) corresponding to the incident angle of the radar image is obtained: The method for obtaining the quasi-specular scattering GO component is: Based on the wind direction information, respectively obtain the upwind slope and the crosswind slope; Obtaining a slope probability density of a mirror point based on the upwind slope and the crosswind slope; The quasi-specular scattering GO component is obtained based on the slope probability density of the mirror point and the incident angle of the radar image Among them, p(ζ x' ,ζ y' ) represents the slope probability density of the mirror point, ζ x' represents the upwind slope, ζ y' represents the crosswind slope, θ represents the incident angle of the radar image, and R represents the Fresnel reflection coefficient at vertical incidence; The first-order Bragg resonance scattering component for: Among them, g qp represents the scattering coefficient, K represents the wave number size, and W(·) represents the two-dimensional wave number spectrum with folded symmetry; Obtaining a target signal-to-clutter ratio based on the sea surface backscatter coefficient; Obtaining a detection threshold based on the target signal-to-noise ratio; Obtaining a sea surface backscatter coefficient distribution probability density based on the sea surface backscatter coefficient; Obtaining a constant false alarm rate value based on the sea surface backscatter coefficient distribution probability density and the detection threshold; The coordinate value of the ship target image is obtained based on the constant false alarm rate value and the SAR image to be detected.

2. A SAR image ship target constant false alarm rate detection method according to claim 1, characterized in that: The target signal-to-noise ratio is: SCR(θ)=RCS Ship -s(θ) Where SCR(θ) represents the target signal-to-clutter ratio, RCS Ship Represents the average backscatter coefficient of the ship target.

3. A SAR image ship target constant false alarm rate detection method according to claim 2, characterized in that: The detection threshold is: T(θ)=SCR(θ)-N ship N ship =RMSE(RCS Ship ) Where T(θ) represents the detection threshold, N ship It represents the mean square error of the average backscatter coefficient of the ship target, and RMSE(·) represents the mean square error operation.

4. A method for detecting ship targets in SAR images using a constant false alarm rate according to claim 3, characterized in that: The probability density of the sea surface backscatter coefficient distribution is specifically: Where x represents the pixel amplitude of the SAR image to be detected.

5. A method for detecting ship targets in SAR images using a constant false alarm rate according to claim 4, characterized in that: The constant false alarm rate value is specifically: Among them, P fa (θ) represents the constant false alarm rate value.

6. A SAR image ship target constant false alarm rate detection system, applied to a SAR image ship target constant false alarm rate detection method as claimed in any one of claims 1 to 5, characterized in that: include: Data acquisition module, detection threshold acquisition module, constant false alarm rate value acquisition module and result output module; The data acquisition module is used to acquire the SAR image to be detected and the corresponding external parameters; The detection threshold acquisition module is used to obtain a sea surface backscatter coefficient based on the SAR image to be detected and the external parameters; and obtain a target signal-to-clutter ratio based on the sea surface backscatter coefficient; Obtaining a detection threshold based on the target signal-to-noise ratio; The constant false alarm rate value acquisition module is used to obtain the sea surface backscatter coefficient distribution probability density based on the sea surface backscatter coefficient; Obtaining a constant false alarm rate value based on the sea surface backscatter coefficient distribution probability density and the detection threshold; The result output module is used to obtain the image coordinate value of the ship target based on the constant false alarm rate value and the SAR image to be detected.

Images