Constant false alarm probability detection method, device and equipment based on phase characteristics

Abstract

The present invention provides a method, device and equipment for detecting a target to be detected based on a phase feature, the method comprising: obtaining a pulse echo obtained by detecting a target to be detected in a sea surface environment by a coherent radar; obtaining phase information of multiple continuous pulse echoes of a first distance unit of a reference unit in the pulse echo; determining a linear relationship of the phase information of the first distance unit based on the phase information of the multiple continuous pulse echoes; when the linear relationship is linearly correlated, deleting the pulse echo of the first distance unit, and performing target detection on the target to be detected based on the remaining reference units by a constant false alarm probability detection method. The embodiment of the present invention is used to solve the defect in the prior art that when there are two or more targets or strong ground clutter interference around the target to be detected, the CFAR detector cannot detect the target, and a target shielding phenomenon occurs.

Description

Technical Field

[0001] The present invention relates to the technical field of target detection, and in particular to a method, device and equipment for detecting a constant false alarm probability based on phase characteristics. Background Art

[0002] In a complex marine environment, marine radars such as shore-based radars and ship-borne radars will inevitably be affected by sea clutter when detecting military and civilian targets such as ships, sea-skimming aircraft, channel buoys, fishing boats, small yachts, and floating ice. Especially under high-resolution radar and high sea conditions, spikes frequently appear in sea clutter, and the overall energy is strong, which can easily cause false alarms and seriously affect the detection of marine targets. In order to avoid losses caused by false detection and missed detection, various CFAR (Constant False Alarm Rate) detectors are needed to reduce the occurrence of false alarms.

[0003] Common CFAR detectors are mean level (ML) type CFAR detectors. In this type of detector, their local interference power level estimation adopts the averaging method. The three most classic ones are cell average CFAR (CA-CFAR), cell average selection of great GO (Greatest Of)-CFAR and cell average selection of small SO (Smallest Of)-CFAR. However, the concept of cell average CFAR is limited by two basic assumptions.

[0004] 1. The targets are independent. There is at least a reference window length between targets, so that there is no possibility of two targets existing in the reference window at the same time.

[0005] 2. All interference data within the reference window are independently distributed and are identically distributed to the interference within the cell containing the target, that is, the interference is uniform.

[0006] In a complex marine environment, the actual situation often violates one or both of these conditions. When there are two or more targets or strong ground clutter interference around the target to be detected, the target echo power of the reference unit may exceed the surrounding interference power, and the clutter power estimation value will be increased. The CFAR threshold will therefore be raised, and the CFAR detector will be unable to detect the target, resulting in target shielding. Summary of the invention

[0007] The present invention provides a constant false alarm probability detection method, device and equipment based on phase characteristics, which are used to solve the defect in the prior art that when there are two or more targets around a target to be detected, a CFAR detector cannot detect the target and a target shielding phenomenon occurs, thereby improving the detection performance of target detection.

[0008] The present invention provides a constant false alarm probability detection method based on phase characteristics, comprising:

[0009] Acquire a pulse echo obtained by a coherent radar detecting a target to be detected in a sea surface environment;

[0010] Acquire phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echo;

[0011] Determine a linear relationship of phase information of the first distance unit based on phase information of the plurality of consecutive pulse echoes;

[0012] In the case where the linear relationship is linearly correlated, the pulse echo of the first distance unit is deleted, and target detection is performed on the target to be detected based on the remaining reference units by a constant false alarm probability detection method.

[0013] The present invention also provides a constant false alarm probability detection device based on phase characteristics, comprising:

[0014] The first acquisition module is used to acquire the pulse echo obtained by the coherent radar detecting the target to be detected in the sea environment;

[0015] A second acquisition module, used to acquire phase information of multiple continuous pulse echoes of a first distance unit of a reference unit in the pulse echo;

[0016] A linear relationship determination module, configured to determine a linear relationship of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes;

[0017] The target detection module is used to delete the pulse echo of the first distance unit when the linear relationship meets the preset conditions, and perform target detection on the target to be detected based on the remaining reference units through a constant false alarm probability detection method.

[0018] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the constant false alarm probability detection method based on phase characteristics as described above is implemented.

[0019] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the constant false alarm probability detection method based on phase characteristics as described in any one of the above is implemented.

[0020] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned constant false alarm probability detection methods based on phase features.

[0021] The constant false alarm probability detection method, device and equipment based on phase characteristics provided by the present invention are: a pulse echo obtained by detecting a target to be detected in a sea surface environment by a coherent radar; the phase information of multiple continuous pulse echoes of a first distance unit of a reference unit in the pulse echo is obtained; the linear relationship of the phase information of the first distance unit is determined based on the phase information of the multiple continuous pulse echoes; when the linear relationship is linearly correlated, the pulse echo of the first distance unit is deleted, and the target to be detected is detected by a constant false alarm probability detection method based on the remaining reference units. When the target to be detected in the sea surface environment is continuously detected by a coherent radar, the phase characteristics of land islands, strong interference targets or sea peaks are often linear under certain confidence levels. Therefore, the embodiment of the present invention determines the linear relationship of the phase information of the first distance unit based on the phase information of multiple continuous pulse echoes of the first distance unit of the reference unit in the pulse echo; when the linear relationship is linearly correlated, the pulse echo of the first distance unit is deleted, and the target to be detected is detected by a constant false alarm probability detection method based on the remaining reference units. Thus, strong interfering targets or strong sea clutter near the target to be detected are screened and eliminated, making the amplitude probability density function of the sea clutter more consistent with the Rayleigh distribution, and the background clutter power is not affected by the interfering targets, which is more in line with the prerequisites for the use of the CFAR detection method. At the same time, it is avoided that the interference factors of the first distance unit with a linear relationship may accidentally raise the detection threshold, thereby improving the detection performance of target detection and reducing missed detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 It is a flow chart of a constant false alarm probability detection method based on phase characteristics provided by the present invention;

[0024] Figure 2 It is a schematic diagram showing the calculation principle of the traditional CA-CFAR method;

[0025] Figure 3a Schematic diagram showing that phase characteristics are linearly related;

[0026] Figure 3b Schematic diagram showing that phase features are nonlinearly related;

[0027] Figure 4 A schematic diagram showing the calculation principle of the improved CA-CFAR method of the present invention;

[0028] Figure 5 A schematic diagram showing comparison of detection performance curves of a single target detection by an ML-CFAR detector, a CMLD-CFAR detector and an improved CA-CFAR detection method according to an embodiment of the present invention in a uniform single target background environment;

[0029] Figure 6a A schematic diagram showing two target signals of different simulation sizes;

[0030] Figure 6b Schematic diagram showing the ROC curve of the larger of the two targets;

[0031] Figure 7a A schematic diagram showing the simulation of four target signals;

[0032] Figure 7b A schematic diagram showing a comparison of the A-display detection thresholds of a SO-CFAR detector and an improved CA-CFAR detection method according to an embodiment of the present invention;

[0033] Figure 8a A schematic diagram showing the simulation of four target signals in a clutter edge environment;

[0034] Figure 8b A schematic diagram showing a comparison of the A-image detection thresholds of the GO-CFAR detector and the improved CA-CFAR detection method according to an embodiment of the present invention;

[0035] Fig. 9 A schematic diagram showing a P display of scan data according to an embodiment of the present invention;

[0036] Fig.10a A schematic diagram showing a comparison of thresholds of a conventional CA-CFAR device and an improved CA-CFAR method according to an embodiment of the present invention;

[0037] Fig.10b A schematic diagram showing a comparison of thresholds of a conventional SO-CFAR device and an improved CA-CFAR method according to an embodiment of the present invention;

[0038] Fig.11 It is a structural schematic diagram of a constant false alarm probability detection device based on phase characteristics provided by the present invention;

[0039] Fig.12 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are 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.

[0041] The echo signal received by the radar contains not only the target signal, but also various clutter, noise and interference signals. At the same time, the radar itself may also affect the detection. If a fixed threshold is used for detection, a large number of missed alarms or false alarms will occur. Therefore, an adaptive threshold is needed to replace the fixed threshold. The CFAR method can be adaptively adjusted according to the size of the background noise, clutter and interference of the detected point. Among them, CA-CFAR (unit average constant false alarm detection) is the most basic target detection algorithm. Its working principle is as follows: Figure 2 Please refer to Figure 2 , Figure 2 Represents the calculation principle of the traditional CA-CFAR method. Figure 2 In the figure, D represents the current unit to be detected (CUT), and the amplitude of the unit will be compared with the adaptive threshold. Since the power of the target may leak into the adjacent units, the units adjacent to the target are not used as the background clutter estimation, but as the protection unit P. When calculating the background power, the protection unit is not included. A total of N reference units x are taken on the left and right sides of the unit to be detected D. i (i=1,…,N), the reference unit, protection unit, and unit to be detected are collectively referred to as the CFAR processing window; then the reference units on the left and right sides are summed and averaged to estimate the background clutter power Z of the unit to be detected; given the expected false alarm probability P FA The background clutter power Z is multiplied by the normalization factor α to obtain the detection threshold T. The unit to be detected D is compared with the detection threshold T. If the amplitude of the target to be detected is greater than the threshold value, the detection unit is considered to be the target, otherwise it is not the target.

[0042] Sea clutter is composed of the superposition of scattered signals from a large number of scattering units in the antenna beam area. Therefore, it can be approximately considered that sea clutter is Gaussian distributed. After amplitude detection, the amplitude probability density function of the clutter echo also conforms to the Rayleigh distribution. Its probability density function is:

[0043]

[0044] From the unit average constant false alarm principle diagram, we can know that the background clutter power Z of the unit to be detected is

[0045]

[0046] The threshold value T can be obtained by multiplying the background clutter power Z of the unit to be detected D by the normalization factor α, which is expressed as

[0047]

[0048] Therefore, the detection threshold expression can be finally obtained by estimation:

[0049]

[0050] Let c = α / N, and combine it with formula (1) to calculate the probability density distribution of the threshold T, which is expressed as

[0051]

[0052] Then, by using the Neyman-Pearson criterion, the probability density distribution of the false alarm probability is integrated to obtain the false alarm probability. The final result is expressed as

[0053]

[0054] According to the above formula, for a given expected false alarm probability P FA The required normalization factor can be obtained by solving the formula

[0055]

[0056] It should be noted that the false alarm probability P FA It does not depend on the actual interference noise power, but only on the adjacent unit samples N and the normalization factor α involved in the average. Therefore, the unit average constant false alarm shows the characteristics of CFAR.

[0057] The concept of cell-average CFAR is limited by two basic assumptions.

[0058] 1. The targets are independent. There is at least a reference window length between targets, so that there is no possibility of two targets existing in the reference window at the same time.

[0059] 2. All interference data within the reference window are independently distributed and are identically distributed to the interference within the cell containing the target, that is, the interference is uniform.

[0060] In a complex marine environment, the actual situation often violates one or both of these conditions. When there are two or more targets or strong ground clutter interference around the target to be detected, the target echo power of the reference unit may exceed the surrounding interference power, and the clutter power estimation value will be increased. The CFAR threshold will therefore be raised, and the CFAR detector will be unable to detect the target, resulting in target shielding.

[0061] In view of this, an embodiment of the present invention provides a constant false alarm probability detection method, device and equipment based on phase characteristics, which is used to solve the defect in the prior art that when there are two or more targets around the target to be detected, the CFAR detector cannot detect the target and target shielding occurs, thereby improving the detection performance of target detection.

[0062] Combine the following Figure 1 The present invention describes a constant false alarm probability detection method based on phase characteristics, the method comprising:

[0063] Step 100: Acquire a pulse echo obtained by detecting a target to be detected in a sea surface environment by a coherent radar.

[0064] The electronic device acquires the pulse echo obtained by the coherent radar when detecting the target to be detected in the sea surface environment.

[0065] Among them, the coherent radar can be various shore-based radars or ship-borne radars. The coherence in the coherent radar means that the initial phase between pulses is deterministic, that is, the initial phase of the first pulse may be random, but the phase between the subsequent pulses and the first pulse is deterministic. The randomness of the initial phase of the first pulse does not affect the subsequent signal detection, which is the basis for extracting Doppler information.

[0066] When the coherent radar continuously detects sea surface targets, the phase characteristics of land islands, strong interference targets or sea peaks are often linear under certain confidence limits. Therefore, by obtaining the pulse echo obtained by the coherent radar to detect the target to be detected in the sea environment, it is beneficial to obtain the phase characteristics of the reference unit near the target to be detected. It is convenient to screen out reference units with strong phase linearity based on the phase characteristics of the reference units near the target to be detected.

[0067] Step 200: Acquire phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echo.

[0068] The electronic device obtains phase information of multiple continuous pulse echoes of the first distance unit of the reference unit in the pulse echo. The reference unit refers to the distance units on the left and right sides of the unit D to be detected in the CA-CFAR detection algorithm. The first distance unit refers to any distance unit on the left and right sides of the unit D to be detected. In other words, in the embodiment of the present invention, the linear relationship of the phase information of all distance units on the left and right sides of the unit D to be detected is judged.

[0069] For example, the electronic device obtains 10 or 16 continuous pulse echoes of a certain distance unit in the reference unit of the pulse echo, and obtains their phase information.

[0070] Step 300: determining a linear relationship of phase information of the first distance unit based on phase information of the plurality of continuous pulse echoes;

[0071] The electronic device determines the linear relationship of the phase information of the first distance unit based on the phase information of the plurality of consecutive pulse echoes. For example, step 300, determining the linear relationship of the phase information of the first distance unit based on the phase information of the plurality of consecutive pulse echoes, includes:

[0072] Step 310: Calculate the phase information of the plurality of continuous pulse echoes by a univariate linear regression method to determine a linear relationship of the phase information of the first distance unit.

[0073] In some embodiments, a large amount of measured data of pulse echoes of a coherent radar may be tested to find a suitable confidence level, and whether the linear relationship of the phase information of the first distance unit is linearly correlated is determined within an allowable range of the confidence level.

[0074] In one embodiment, step 310, calculating the phase information of the plurality of continuous pulse echoes by a univariate linear regression method to determine the linear relationship of the phase information of the first distance unit, specifically includes:

[0075] Step 311, calculating the phase information of the plurality of continuous pulse echoes by using a Regress function to obtain a model statistic;

[0076] Step 312: Determine the linear relationship of the phase information of the first distance unit according to the size of the model statistic and the size of the significance probability value.

[0077] For the convenience of calculation, the embodiment of the present invention can use the Regress function in the mathematical calculation tool Matlab to perform a univariate linear regression method on the phase information of the multiple continuous pulse echoes, so as to obtain the model statistic R 2 According to the model statistic R 2 The size of and the significance probability value p are used to determine whether there is a linear relationship between the phases of consecutive pulse echoes of the first distance unit.

[0078] In one embodiment, step 312, determining the linear relationship of the phase information of the first distance unit based on the size of the model statistic and the size of the significance probability value, specifically includes: when the model statistic is greater than or equal to a first set threshold and the significance probability value is less than or equal to a second set threshold, determining that the phase information of the first distance unit is linearly correlated.

[0079] It should be noted that the first set threshold value and the second set threshold value can be determined by testing based on a large amount of measured data of pulse echoes of a large number of coherent radars.

[0080] In the embodiment of the present invention, when the model statistic R is selected 2 When the default significance level with a value greater than 0.90 and a significance probability value p less than 0.05 is used as the basis for judging linear correlation, too many reference units with good linearity are eliminated, resulting in a lower threshold, which is prone to false alarms and affects detection performance. 2 When the default significance level of the value greater than 0.98 and the significance probability value p less than 0.05 is used as the basis for judging linear correlation, the detection performance improvement compared with the traditional CA-CFAR detector is small and of little significance due to the small number of reference units removed. After a large number of actual data tests and comprehensive actual conditions, when the model statistic R 2 When the value is greater than 0.95 and the significance probability value p is less than the default significance level of 0.05, the detection performance is improved while avoiding the occurrence of false alarms as much as possible. Therefore, this parameter can be used to determine whether the phase characteristics of the reference unit are linearly correlated. Figure 3a and Figure 3b The test is performed using two groups of 10 consecutive pulse echoes of the same distance unit. Please refer to Figure 3a , Figure 3a This is a schematic diagram showing that the phase characteristics are linearly related. Please refer to Figure 3b , Figure 3b It is a schematic diagram showing that the phase characteristics are nonlinearly related. Figure 3a Obtain the model statistic R 2 The value 0.9981 is greater than 0.95 and close to 1, and the significance probability value p 0.0133 is less than the default significance level of 0.05, so it can be judged as linear correlation; Figure 3b Obtain the model statistic R 2 The value 0.8343 is less than 0.95, and the significance probability value p-value is 0.2507, which is greater than the default significance level of 0.05, so it can be judged as nonlinear correlation.

[0081] In the embodiment of the present invention, the range of the first set threshold is [0.95, 0.98], and the first set threshold is preferably 0.95.

[0082] Step 400: When the linear relationship is linearly correlated, delete the pulse echo of the first distance unit, and perform target detection on the target to be detected based on the remaining reference units by a constant false alarm probability detection method.

[0083] In a coherent radar, if the phase linearity of continuous pulse echoes in the same distance unit is very good, then the distance unit may be a target, strong clutter, interference target or land clutter. In order to obtain a more appropriate detection threshold, it is necessary to remove the reference unit with good linearity near the unit to be detected D. Therefore, when the linear relationship of the phase information of the pulse echo of the first distance unit is linearly correlated, the pulse echo of the first distance unit is deleted, and the target to be detected is detected based on the remaining reference units through a constant false alarm probability detection method.

[0084] In some embodiments, step 400, performing target detection on the target to be detected by a constant false alarm probability detection method based on the remaining reference units, includes:

[0085] Step 410, taking an average value based on the pulse echoes of the remaining reference units to obtain an updated background clutter power estimate;

[0086] Step 420: obtaining an updated threshold value based on the product of the updated background clutter power estimate value and the normalization factor;

[0087] Step 430: Target detection is performed based on the comparison result between the updated threshold value and the pulse echo of the unit to be detected.

[0088] Please refer to Figure 4 , Figure 4 A schematic diagram showing the calculation principle of the improved CA-CFAR method of the present invention, wherein the present invention performs target detection on the target to be detected by a constant false alarm probability detection method based on the remaining reference units. Figure 4 The selection rules of the detection unit D, protection unit P, and reference unit N are as follows: Figure 2 The method is consistent with the classical CA-CFAR method in, except that the reference units on the left and right sides are selected. In the embodiment of the present invention, step 300 selects the first distance unit of the reference unit with good linearity and changes its pulse echo intensity to zero. In the process of sliding the window, the number m and n of pulse echo intensities on the left and right sides equal to zero are counted, and then the N reference units are summed and averaged. The mean value at this time is actually the mean value of N-(m+n) reference units, that is, the new background clutter power estimation value Z. The new background clutter power Z is then multiplied by the normalization factor α to obtain a new threshold value, and finally compared with the unit to be detected D to determine whether there is a target in this distance unit. For example, assuming that the reference unit N is 32 at the beginning, 16 on each side, and then the strong target or strong clutter with good linearity is eliminated by judging the phase linearity of a certain model statistic. At this time, the actual number of reference units may become 24, and the background clutter power estimation value obtained by the remaining reference units is far more suitable than the background clutter power estimation value obtained by 32 reference units.

[0089] The embodiment of the present invention determines the phase linearity of continuous pulse echoes in the distance unit of the same reference unit, removes the reference unit with strong phase linearity, and forms a detection threshold with better adaptability of the unit to be detected.

[0090] The following describes the detection performance of the phase feature-based constant false alarm probability detection method according to an embodiment of the present invention when applied to a uniform single-target background environment, a multi-target background environment, and a clutter edge environment.

[0091] The detection performance of the constant false alarm probability detection method based on phase characteristics in the embodiment of the present invention is respectively applied to the detection performance of a uniform single target background environment.

[0092] Please refer to Figure 5 , Figure 5 The figure shows the comparison of the detection performance curves (ROC curve, i.e., receiver operating characteristic curve, translated as receiver operating characteristic curve, referred to as ROC curve) of the ML-CFAR detector (i.e., mean-class constant false alarm detector), the CMLD-CFAR detector (i.e., certified mean level detector) and the improved CA-CFAR detection method of the present invention for single target detection in a uniform single target background environment. -6 , with reference to the case of unit N=32, the detection performance curves (ROC curves) of the ML-CFAR detector, the CMLD-CFAR detector and the improved CA-CFAR detection method of the embodiment of the present invention for single target detection. The ML-CFAR detector includes an average detector (i.e. CA-CFAR) and an extreme detector (i.e. GO-CFAR and SO-CFAR). CA-CFAR represents a unit average constant false alarm detector, GO-CFAR represents a maximum selection constant false alarm detector, and SO-CFAR represents a minimum selection constant false alarm detector.

[0093] Figure 5Where opt is the optimal detection performance curve corresponding to a specific signal-to-noise ratio, and the other detection performance curves are, from top to bottom, the improved CA-CFAR detection method of the embodiment of the present invention, CA-CFAR, CMLD-CFAR, GO-CFAR, and SO-CFAR. It should be noted that since there is only one target and the improved CA-CFAR detection method of the embodiment of the present invention only has a screening and elimination effect on strong clutter or strong interference targets, the improved CA-CFAR detection method of the embodiment of the present invention is consistent with the detection performance of the traditional CA-CFAR detector. When the target signal-to-noise ratio is close to 19dB, the detection probability reaches 80%, and the detection method of the embodiment of the present invention that uses phase characteristics to screen reference units does not lose the original detection function; CMLD-CFAR deletes some reference units during the detection process, so it has a smaller signal-to-noise ratio loss compared to CA-CFAR; SO-CFAR has better detection performance in multi-target detection, but a larger signal-to-noise ratio loss for single target detection.

[0094] Therefore, under the uniform single target background, the improved constant false alarm probability detection method based on phase features in the embodiment of the present invention has a comparable detection performance with the unit average constant false alarm detection performance, and has an improved detection performance compared with other mean-type constant false alarm detectors.

[0095] The detection performance of the constant false alarm probability detection method based on phase characteristics in the embodiment of the present invention is respectively applied to the detection performance of the multi-target background environment

[0096] In the detection of multi-target background environment, it is often the case that the target with high amplitude will cover the target with low amplitude, which will reduce the detection probability. Figure 6a , Figure 6a It indicates that two target signals of different sizes are simulated in the detection of multi-target background environment. Figure 6a These are two large and small targets that are close to each other. The power value of the large target is 5dB higher than that of the small target. The average clutter power is around 20dB. The phase characteristic linearity of the small target is better. Please refer to Figure 6b , Figure 6b The traditional CA-CFAR detector and the improved CA-CFAR detection method of the present invention using phase characteristics to screen reference units have a false alarm probability of 10 -6 , the detection performance curve of the detection of targets with larger power values ​​(the signal-to-noise ratio of large targets increases gradually from 0dB to 30dB, and the signal-to-noise ratio of small targets increases accordingly) when the reference unit N=32.

[0097] Figure 6b Represents the ROC curve for the larger of the two targets. Figure 6bIt can be seen that when the target signal-to-noise ratio is less than 5dB, the detection performance of the two detectors is equivalent, and the detection performance of both is enhanced with the increase of the signal-to-noise ratio. When the system requires the detection probability to reach 50%, the traditional CA-CFAR detector requires the target to reach 17dB, and the improved CA-CFAR detection method of the present invention eliminates the reference unit where the small target is located, and obtains a more suitable threshold, and the target only needs to reach 14dB to be detected. It can be seen that the detection performance of the improved CA-CFAR detection method of the present invention is better than that of the traditional CA-CFAR detector.

[0098] Please refer to Figure 7a , Figure 7a Indicates simulation of 4 target signals. Figure 7a Four targets close to each other are simulated in the 80th, 88th, 98th, and 104th distance units of the clutter. The power values ​​of the targets in the 80th and 98th distance units are large enough and the phase linearity is good, so they can be screened out by the constant false alarm probability detection method based on phase characteristics of the present invention. The present invention selects the SO-CFAR detector with the best multi-target detection effect from the mean-type constant false alarm detector and compares it with the improved CA-CFAR detection method of the present invention. The results show that Figure 7b For A display, please refer to Figure 7b ,like Figure 7b As shown in the figure, the SO-CFAR detector can detect most of the targets among many targets, but because the target power value of the 88th distance unit is too small, it fails to detect successfully; while the improved CA-CFAR detection method of the present invention screens the reference unit and successfully detects all targets. Therefore, the improved CA-CFAR detection method of the embodiment of the present invention can show its advantages in the multi-target detection simulation experiment and has good detection performance.

[0099] The detection performance of the constant false alarm probability detection method based on phase characteristics in the embodiment of the present invention is respectively applied to the clutter edge environment.

[0100] The typical clutter edge environment is generally where the sea and land meet. Energy mutation occurs in the distance dimension, so that the target at the edge of low clutter is judged as high-power clutter, resulting in missed detection; it may also mistake the edge clutter in the high-power area for the target, resulting in false alarm. The embodiment of the present invention simulates the environment of the clutter edge and adds two targets at the 88th and 95th distance units in the low-power area. The phase linearity of the left target is better. Please refer to Figure 8a , Figure 8a It means simulating 4 target signals in a clutter edge environment; Figure 8b Indicates the detection threshold comparison of A display. Please refer to Figure 8b , Figure 8bThe GO-CFAR detector with better detection effect on clutter edge environment is selected for comparison with the improved CA-CFAR detection method of the embodiment of the present invention. In the reference unit N=32, the false alarm probability P FA =10 -6 Two thresholds are obtained under the circumstances. From the results, both detectors successfully detected the first target, but due to the influence of the large target, the GO-CFAR detector could not successfully detect the second target; the improved CFAR detection method of the embodiment of the present invention lowered the threshold at the target by improving the reference unit selection, and successfully detected the second target. In the clutter edge environment, the improved algorithm and GO-CFAR both have good detection performance, but when there are multiple targets in the clutter edge environment, the improved CA-CFAR detection method of the embodiment of the present invention has better detection performance than GO-CFAR.

[0101] In summary, the improved CFAR detector that uses the phase characteristics of the embodiment of the present invention to screen the reference unit has a detection performance that is basically consistent with the traditional CA-CFAR detection and does not lose the function of the original detector under a uniform single-target clutter background because there is no reference unit that needs to be eliminated; the detection performance under a multi-target background and clutter edge background is better than other mean-type constant false alarm detectors.

[0102] In order to further verify the performance of the constant false alarm probability detection method based on phase characteristics of the embodiment of the present invention, this paper uses a set of scanning data (a set of 2239×2224 matrices, each row represents an azimuth / pulse, and each column represents a distance unit) for testing. The P display diagram of the scanning data is shown in FIG. Fig. 9 Please refer to Fig. 9 , Fig. 9 A P display diagram showing the scanning data of an embodiment of the present invention. The group of scanning data records the information of the radar scanning range from 259.445° to 0° to 125.992°.

[0103] The embodiment of the present invention randomly selects data of ten consecutive echoes for testing. At the azimuth of 71.781°, there are several ships near the distance units 1501, 1784 and 1791. The reference unit N is 64. Due to factors such as the width of the ship, four protection units are selected on each side. The constant false alarm rate PFA is 10 -4 In the improved CA-CFAR detection method of the embodiment of the present invention, the model statistic R 2 Whether the value is greater than 0.95 and whether the significance probability value p is less than 0.05 is used as the standard for linear judgment. The test results are as follows Fig.10a and Fig.10b Please refer to Fig.10a , Fig.10aIt represents the threshold comparison between the traditional CA-CFAR device and the improved CA-CFAR method of the embodiment of the present invention. Near the 1501 distance unit, since the amplitude of the main target is large enough and the amplitude of the adjacent interfering target is small, both the traditional CA-CFAR and the improved CA-CFAR detection method of the embodiment of the present invention can detect the target ship, but the improved CA-CFAR detection of the embodiment of the present invention only needs a lower power value to be detected; near the 1784 and 1791 distance units, since there are strong sea clutter or strong interfering targets near the main target, the use of the traditional CA-CFAR detector will cause the target to be shielded, while the use of the improved CA-CFAR detection method of the embodiment of the present invention avoids this situation and successfully detects the target. The test results of SO-CFAR with better multi-target detection effect and the improved CA-CFAR detection of the embodiment of the present invention are shown in the figure. Fig.10b Please refer to Fig.10b , Fig.10b The figure shows the threshold comparison between the traditional SO-CFAR device and the improved CA-CFAR method of the embodiment of the present invention. Both successfully detect the target, but since both lower the threshold, there may be false alarms.

[0104] The embodiment of the present invention deletes the distance unit where the strong clutter or strong interference target with good phase linearity is located, so that the detection background is more in line with the use premise of the mean-type CFAR. Through the analysis and verification of simulation data and measured data, it can be known that the improved CA-CFAR method of the embodiment of the present invention can detect targets that the traditional CA-CFAR cannot detect in a multi-target environment and a clutter edge environment, effectively solve the target shielding problem without losing the original detection performance, and has a good detection performance improvement compared with other mean-type constant false alarm CFARs, which shows the effectiveness of the improved CA-CFAR method of the embodiment of the present invention.

[0105] The embodiment of the present invention obtains the pulse echo obtained by detecting the target to be detected in the sea environment by a coherent radar; obtains the phase information of multiple continuous pulse echoes of the first distance unit of the reference unit in the pulse echo; determines the linear relationship of the phase information of the first distance unit based on the phase information of the multiple continuous pulse echoes; when the linear relationship is linearly correlated, delete the pulse echo of the first distance unit, and perform target detection on the target to be detected based on the remaining reference units by a constant false alarm probability detection method. When the target to be detected in the sea environment is continuously detected by a coherent radar, the phase characteristics of land islands, strong interference targets or sea peaks are often linear under certain confidence levels. Therefore, the embodiment of the present invention determines the linear relationship of the phase information of the first distance unit based on the phase information of multiple continuous pulse echoes of the first distance unit of the reference unit in the pulse echo; when the linear relationship is linearly correlated, delete the pulse echo of the first distance unit, and perform target detection on the target to be detected based on the remaining reference units by a constant false alarm probability detection method. Thus, strong interfering targets or strong sea clutter near the target to be detected are screened and eliminated, making the amplitude probability density function of the sea clutter more consistent with the Rayleigh distribution, and the background clutter power is not affected by the interfering targets, which is more in line with the prerequisites for the use of the CFAR detection method. At the same time, it is avoided that the interference factors of the first distance unit with a linear relationship may accidentally raise the detection threshold, thereby improving the detection performance of target detection and reducing missed detection.

[0106] The constant false alarm probability detection device based on phase characteristics provided by the present invention is described below. The constant false alarm probability detection device based on phase characteristics described below and the constant false alarm probability detection method based on phase characteristics described above can correspond to each other.

[0107] Please refer to Fig.11 The present invention provides a constant false alarm probability detection device based on phase characteristics, comprising:

[0108] The first acquisition module 201 is used to acquire the pulse echo obtained by the coherent radar detecting the target to be detected in the sea environment;

[0109] A second acquisition module 202 is used to acquire phase information of multiple continuous pulse echoes of a first distance unit of a reference unit in the pulse echo;

[0110] A linear relationship determination module 203, configured to determine a linear relationship of the phase information of the first distance unit based on the phase information of the plurality of consecutive pulse echoes;

[0111] The target detection module 204 is used to delete the pulse echo of the first distance unit when the linear relationship meets the preset conditions, and perform target detection on the target to be detected based on the remaining reference units by a constant false alarm probability detection method.

[0112] In one embodiment, the linear relationship determination module is used to calculate the phase information of the multiple consecutive pulse echoes by a univariate linear regression method to determine the linear relationship of the phase information of the first distance unit.

[0113] In one embodiment, the phase information of the multiple continuous pulse echoes is calculated by a univariate linear regression method to determine the linear relationship of the phase information of the first distance unit, specifically including: calculating the phase information of the multiple continuous pulse echoes by a Regress function to obtain a model statistic; and determining the linear relationship of the phase information of the first distance unit according to the size of the model statistic and the size of the significance probability value.

[0114] In one embodiment, determining the linear relationship of the phase information of the first distance unit according to the size of the model statistic and the size of the significance probability value includes:

[0115] When the model statistic is greater than or equal to a first set threshold and the significance probability value is less than or equal to a second set threshold, it is determined that the phase information of the first distance unit is linearly correlated.

[0116] In one embodiment, the first set threshold is in the range of [0.95, 0.98].

[0117] In one embodiment, the target detection module includes:

[0118] An updated background clutter power estimation value calculation module is used to obtain an updated background clutter power estimation value based on an average value of the pulse echoes of the remaining reference units;

[0119] An update threshold value calculation module, used to obtain an update threshold value based on the product of the update background clutter power estimate value and the normalization factor;

[0120] The final target detection module is used to perform target detection based on the comparison result between the updated threshold value and the pulse echo of the unit to be detected.

[0121] The constant false alarm probability detection device based on phase characteristics of the embodiment of the present application is obtained by obtaining a pulse echo obtained by detecting a target to be detected in a sea surface environment by a coherent radar; obtaining the phase information of multiple continuous pulse echoes of a first distance unit of a reference unit in the pulse echo; determining the linear relationship of the phase information of the first distance unit based on the phase information of the multiple continuous pulse echoes; in the case where the linear relationship is linearly correlated, deleting the pulse echo of the first distance unit, and performing target detection on the target to be detected based on the remaining reference units by a constant false alarm probability detection method. Since the phase characteristics of land islands, strong interference targets or sea peaks are often linear when a certain confidence level is allowed when a coherent radar is used to continuously detect the target to be detected in the sea surface environment. Therefore, the embodiment of the present invention determines the linear relationship of the phase information of the first distance unit based on the phase information of multiple continuous pulse echoes of the first distance unit of the reference unit in the pulse echo; in the case where the linear relationship is linearly correlated, deleting the pulse echo of the first distance unit, and performing target detection on the target to be detected based on the remaining reference units by a constant false alarm probability detection method. Thus, strong interfering targets or strong sea clutter near the target to be detected are screened and eliminated, making the amplitude probability density function of the sea clutter more consistent with the Rayleigh distribution, and the background clutter power is not affected by the interfering targets, which is more in line with the prerequisites for the use of the CFAR detection method. At the same time, it is avoided that the interference factors of the first distance unit with a linear relationship may accidentally raise the detection threshold, thereby improving the detection performance of target detection and reducing missed detection.

[0122] Fig.12 An example of a physical structure diagram of an electronic device is shown in FIG. Fig.12 As shown, the electronic device may include: a processor 1210, a communication interface 1220, a memory 1230 and a communication bus 1240, wherein the processor 1210, the communication interface 1220 and the memory 1230 communicate with each other through the communication bus 1240. The processor 1210 may call the logic instructions in the memory 1230 to execute a constant false alarm probability detection method based on phase characteristics, the method comprising: obtaining a pulse echo obtained by detecting a target to be detected in a sea surface environment by a coherent radar; obtaining phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echo; determining a linear relationship of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes; in the case where the linear relationship is linearly correlated, deleting the pulse echo of the first distance unit, and performing target detection on the target to be detected based on the remaining reference units by a constant false alarm probability detection method.

[0123] In addition, the logic instructions in the above-mentioned memory 1230 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0124] On the other hand, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the constant false alarm probability detection method based on phase characteristics provided by the above methods, and the method includes: obtaining a pulse echo obtained by a coherent radar to detect a target to be detected in a sea surface environment; obtaining phase information of multiple continuous pulse echoes of a first distance unit of a reference unit in the pulse echo; determining a linear relationship of the phase information of the first distance unit based on the phase information of the multiple continuous pulse echoes; when the linear relationship is linearly correlated, deleting the pulse echo of the first distance unit, and performing target detection on the target to be detected based on the remaining reference units through a constant false alarm probability detection method.

[0125] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the constant false alarm probability detection method based on phase characteristics provided by the above-mentioned methods, the method comprising: obtaining a pulse echo obtained by a coherent radar detecting a target to be detected in a sea surface environment; obtaining phase information of multiple continuous pulse echoes of a first distance unit of a reference unit in the pulse echo; determining a linear relationship of the phase information of the first distance unit based on the phase information of the multiple continuous pulse echoes; when the linear relationship is linearly correlated, deleting the pulse echo of the first distance unit, and performing target detection on the target to be detected based on the remaining reference units using a constant false alarm probability detection method.

[0126] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0127] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A constant false alarm probability detection method based on phase characteristics, characterized in that: include: Acquire a pulse echo obtained by a coherent radar detecting a target to be detected in a sea surface environment; Acquire phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echo; Determine a linear relationship of phase information of the first distance unit based on phase information of the plurality of consecutive pulse echoes; In the case where the linear relationship is linearly correlated, the pulse echo of the first distance unit is deleted, and target detection is performed on the target to be detected by a constant false alarm probability detection method based on the remaining reference units; The determining the linear relationship of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes comprises: Calculating the phase information of the plurality of continuous pulse echoes by a univariate linear regression method to determine a linear relationship of the phase information of the first distance unit; The step of calculating the phase information of the plurality of continuous pulse echoes by a univariate linear regression method to determine the linear relationship of the phase information of the first distance unit includes: The phase information of the plurality of continuous pulse echoes is calculated by using a Regress function to obtain a model statistic; Determining a linear relationship of the phase information of the first distance unit according to the size of the model statistic and the size of the significance probability value; Determining the linear relationship of the phase information of the first distance unit according to the size of the model statistic and the size of the significance probability value includes: When the model statistic is greater than or equal to a first set threshold and the significance probability value is less than or equal to a second set threshold, it is determined that the phase information of the first distance unit is linearly correlated.

2. The constant false alarm probability detection method based on phase characteristics according to claim 1 is characterized in that: The range of the first set threshold is [0.95, 0.98].

3. The constant false alarm probability detection method based on phase characteristics according to claim 1 is characterized in that: The performing target detection on the target to be detected by a constant false alarm probability detection method based on the remaining reference units includes: An updated background clutter power estimate is obtained by taking an average value based on the pulse echoes of the remaining reference units; Obtaining an updated threshold value based on the product of the updated background clutter power estimate and the normalization factor; Target detection is performed based on a comparison result between the updated threshold value and the pulse echo of the unit to be detected.

4. A constant false alarm probability detection device based on phase characteristics, characterized in that: include: The first acquisition module is used to acquire the pulse echo obtained by the coherent radar detecting the target to be detected in the sea environment; A second acquisition module, used to acquire phase information of multiple continuous pulse echoes of a first distance unit of a reference unit in the pulse echo; A linear relationship determination module, configured to determine a linear relationship of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes; A target detection module, configured to delete the pulse echo of the first distance unit when the linear relationship meets a preset condition, and perform target detection on the target to be detected by a constant false alarm probability detection method based on the remaining reference units; The linear relationship determination module is used to calculate the phase information of the plurality of continuous pulse echoes by a univariate linear regression method to determine the linear relationship of the phase information of the first distance unit; The step of calculating the phase information of the plurality of continuous pulse echoes by a univariate linear regression method to determine the linear relationship of the phase information of the first distance unit includes: The phase information of the plurality of continuous pulse echoes is calculated by using a Regress function to obtain a model statistic; Determining a linear relationship of the phase information of the first distance unit according to the size of the model statistic and the size of the significance probability value; Determining the linear relationship of the phase information of the first distance unit according to the size of the model statistic and the size of the significance probability value includes: When the model statistic is greater than or equal to a first set threshold and the significance probability value is less than or equal to a second set threshold, it is determined that the phase information of the first distance unit is linearly correlated.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the constant false alarm probability detection method based on phase characteristics as described in any one of claims 1 to 3 are implemented.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the constant false alarm probability detection method based on phase characteristics as claimed in any one of claims 1 to 3 are implemented.

7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the phase feature-based constant false alarm probability detection method according to any one of claims 1 to 3 are implemented.

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