CN115291181B - Constant false alarm probability detection method, device and equipment based on phase characteristics - Google Patents
Constant false alarm probability detection method, device and equipment based on phase characteristics Download PDFInfo
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Abstract
本发明提供一种基于相位特征的恒定虚警概率检测方法、装置和设备，方法包括：获取相参雷达对海面环境的待检测目标进行检测得到的脉冲回波；获取所述脉冲回波中参考单元的第一距离单元的多个连续脉冲回波的相位信息；基于所述多个连续脉冲回波的相位信息确定所述第一距离单元的相位信息的线性关系；在所述线性关系呈线性相关的情况下，删除所述第一距离单元的脉冲回波，并基于余下的所述参考单元通过恒定虚警概率检测方法对所述待检测目标进行目标检测。本发明实施例用以解决现有技术中当待检测目标周围有两个或多个目标或强地杂波干扰等，CFAR检测器就无法检测到该目标，发生目标遮蔽现象的缺陷。
The present invention provides a method, device and equipment for detecting a target to be detected based on a constant false alarm probability based on phase characteristics. The method comprises: 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, resulting in target shielding.
Description
Technical Field
The present invention relates to the field of target detection technologies, and in particular, to a method, an apparatus, and a device for detecting constant false alarm probability based on phase characteristics.
Background
In a complex marine environment, marine radars such as shore radars and ship-borne radars are inevitably affected by sea surface scattering echoes, i.e., sea clutter, when detecting military and civil targets such as ships, sea-skimming aircrafts, channel buoys, fishing boats, small yachts, floating ice, and the like. Especially under the working conditions of high-resolution radars and high sea conditions, spike phenomena frequently occur in sea clutter, the overall energy is strong, false alarms are easy to cause, and the detection of offshore targets is seriously affected. In order to avoid the loss caused by false detection and missing detection, various CFAR (Constant FALSE ALARM RATE) detectors are required to reduce the occurrence of false alarms.
A common CFAR detector is a mean (MEAN LEVEL, ML) class CFAR detector. In such detectors, their local interference power level estimates all employ an averaging approach, of which the most classical three are cell average CFAR (CELL AVERAGING, CA-CFAR), cell average large GO (Greatest Of) -CFAR and cell average small SO (Smallest Of) -CFAR. The concept of cell averaging CFAR is limited to two basic assumptions.
1. The targets are independent. The length of at least one reference window between the targets is such that there is no possibility of two targets being present simultaneously within the reference window.
2. All interference data within the reference window is distributed independently and is co-distributed with the interference within the cell containing the target, i.e. the interference is uniform.
In a complex marine environment, the actual situation often violates one or two conditions, when two or more targets or strong clutter interference exists around the target to be detected, the target echo power of the reference unit may exceed the surrounding interference power, the clutter power estimated value will be increased, the threshold of the CFAR will be raised, and thus the CFAR detector cannot detect the target, and the target shielding phenomenon occurs.
Disclosure of Invention
The invention provides a constant false alarm probability detection method, device and equipment based on phase characteristics, which are used for solving the defect that a CFAR detector cannot detect two or more targets around the target to be detected and a target shielding phenomenon occurs in the prior art, and improving the detection performance of target detection.
The invention provides a constant false alarm probability detection method based on phase characteristics, which comprises the following steps:
Acquiring pulse echoes obtained by detecting targets to be detected in sea surface environment by a coherent radar;
acquiring phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echoes;
determining a linear relationship of phase information of the first range bin based on phase information of the plurality of successive pulse echoes;
and deleting the pulse echo of the first distance unit under the condition that the linear relation is linearly related, and carrying out target detection on the target to be detected by a constant false alarm probability detection method based on the rest of the reference units.
The invention also provides a constant false alarm probability detection device based on the phase characteristics, which comprises:
The first acquisition module is used for acquiring pulse echoes obtained by detecting targets to be detected in the sea surface environment by the coherent radar;
the second acquisition module is used for acquiring phase information of a plurality of continuous pulse echoes of a first distance unit of the reference unit in the pulse echoes;
A linear relationship determination module for determining a linear relationship of phase information of the first range bin based on phase information of the plurality of successive pulse echoes;
and the target detection module is used for deleting the pulse echo of the first distance unit under the condition that the linear relation accords with a preset condition, and carrying out target detection on the target to be detected through a constant false alarm probability detection method based on the rest of the reference units.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the constant false alarm probability detection method based on the phase characteristics when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a constant false alarm probability detection method based on phase characteristics as described in any of the above.
The invention also provides a computer program product comprising a computer program which when executed by a processor implements a constant false alarm probability detection method based on phase characteristics as described in any one of the above.
The constant false alarm probability detection method, device and equipment based on the phase characteristics provided by the invention are used for obtaining pulse echoes 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 echoes, determining a linear relation of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes, deleting the pulse echoes of the first distance unit under the condition that the linear relation is linearly related, and detecting the target to be detected by the constant false alarm probability detection method based on the rest of the reference units. When the coherent radar is adopted to continuously detect the target to be detected in the sea surface environment, the phase characteristics of land islands, strong interference targets or sea spikes are often linear under the condition of certain confidence coefficient permission. Therefore, the method and the device for detecting the target to be detected based on the continuous pulse echo comprise the steps of determining the linear relation of the phase information of the first distance unit based on the phase information of a plurality of continuous pulse echoes of the first distance unit of the reference units in the pulse echoes, deleting the pulse echo of the first distance unit under the condition that the linear relation is in linear correlation, and detecting the target to be detected based on the rest of the reference units through a constant false alarm probability detection method. Therefore, strong interference targets or strong sea clutter near the target to be detected are screened and removed, so that the amplitude probability density function of the sea clutter better accords with Rayleigh distribution, the background clutter power is not influenced by the interference targets, the precondition of using the CFAR detection method is better met, meanwhile, the condition that the detection threshold is possibly accidentally raised by interference factors of a first distance unit with linear relation is avoided, the detection performance of target detection is improved, and missed detection is reduced.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a constant false alarm probability detection method based on phase characteristics;
FIG. 2 is a schematic diagram showing the calculation principle of a conventional CA-CFAR method;
FIG. 3a shows a schematic diagram of a linear correlation of phase characteristics;
FIG. 3b is a schematic diagram showing a nonlinear correlation of phase characteristics;
FIG. 4 is a schematic diagram showing the computational principle of the improved CA-CFAR method of the present invention;
FIG. 5 is a graph showing the comparison of detection performance curves for single target detection in a uniform single target background environment ML-CFAR detector, CMLD-CFAR detector, and an improved CA-CFAR detection method in accordance with an embodiment of the present invention;
FIG. 6a is a schematic diagram showing 2 target signals of different simulated sizes;
FIG. 6b shows a schematic representation of the ROC curve of a large target of two targets;
FIG. 7a shows a schematic diagram of a simulation of 4 target signals;
FIG. 7b is a schematic diagram showing comparison of the SO-CFAR detector with the detection threshold of the A-gram of the improved CA-CFAR detection method of an embodiment of the present invention;
FIG. 8a shows a schematic diagram of a simulation of 4 target signals in a clutter edge environment;
FIG. 8b is a schematic diagram showing the comparison of the detection threshold of the GO-CFAR detector with the A-gram of the improved CA-CFAR detection method of the present invention;
FIG. 9 is a schematic diagram of a P-display of scan data according to an embodiment of the present invention;
FIG. 10a is a diagram illustrating a threshold comparison of a conventional CA-CFAR with an improved CA-CFAR method in accordance with an embodiment of the present invention;
FIG. 10b is a diagram showing a threshold comparison of a conventional SO-CFAR with the improved CA-CFAR method of an embodiment of the present invention;
Fig. 11 is a schematic structural diagram of a constant false alarm probability detection device based on phase characteristics provided by the invention;
Fig. 12 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The echo signal received by the radar contains not only the target signal but also various clutter, noise and interference signals, and the radar itself may also influence detection. If a fixed threshold is adopted for detection, a large amount of false alarms or false alarms occur, so that the CFAR method can be adaptively adjusted along with the sizes of background noise, clutter and interference of detected points by adopting an adaptive threshold to replace the fixed threshold. The operation principle of the CA-CFAR (cell average constant false alarm detection) is shown in fig. 2, and referring to fig. 2, fig. 2 shows the calculation principle of the conventional CA-CFAR method. In fig. 2, D represents a current unit to be detected (CUT), the amplitude of which is compared with an adaptive threshold value, since the power of the target may leak into an adjacent unit, a plurality of units adjacent to the target are not used as an estimation of background clutter and are used as protection units P, when calculating the background power, the protection units are not included, N reference units x i (i=1,..and N) are shared on the left and right sides of the unit to be detected D, the reference units, the protection units and the unit to be detected are collectively referred to as CFAR processing windows, then the reference units on the left and right sides are summed and averaged respectively to estimate the background clutter power Z of the unit to be detected, and under a given expected false alarm probability P FA, the background clutter power Z is multiplied by a normalization factor α to obtain a detection threshold T, and if the amplitude of the target to be detected is greater than the threshold value, the detection unit is considered as the target, otherwise not the target.
The sea clutter is formed by overlapping scattering signals of a large number of scattering units in an antenna beam region, so that the sea clutter can be approximately considered to be Gaussian, the amplitude probability density function also accords with Rayleigh distribution after the clutter echo is subjected to amplitude detection, and the probability density function is that
As can be seen from the unit average constant false alarm principle diagram, the background clutter power Z of the unit to be detected is
Multiplying the obtained background clutter power Z of the unit D to be detected by a nominal factor alpha to obtain a threshold value T which is expressed as
Whereby the detection threshold expression can be obtained by estimation as
Let c=α/N, in conjunction with equation (1), the probability density distribution of the threshold T can be calculated as
Integrating the probability density distribution of the obtained false alarm probability by using a Nawman-Pearson criterion to obtain the false alarm probability, wherein the final result is expressed as
For the above equation, for a given expected false alarm probability P FA, the required normalization factor can be obtained by solving
It should be noted that the false alarm probability P FA is independent of the actual interference noise power, and is only related to the neighboring cell samples N participating in the averaging and the normalization factor α. Therefore, the unit average constant false alarm shows the characteristics of CFAR.
The concept of cell averaging CFAR is limited to two basic assumptions.
1. The targets are independent. The length of at least one reference window between the targets is such that there is no possibility of two targets being present simultaneously within the reference window.
2. All interference data within the reference window is distributed independently and is co-distributed with the interference within the cell containing the target, i.e. the interference is uniform.
In a complex marine environment, the actual situation often violates one or two conditions, when two or more targets or strong clutter interference exists around the target to be detected, the target echo power of the reference unit may exceed the surrounding interference power, the clutter power estimated value will be increased, the threshold of the CFAR will be raised, and thus the CFAR detector cannot detect the target, and the target shielding phenomenon occurs.
In view of this, embodiments of the present invention provide a method, an apparatus, and a device for detecting constant false alarm probability based on phase characteristics, so as to solve the defect that in the prior art, when two or more targets exist 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.
The method for detecting constant false alarm probability based on phase characteristics according to the present invention is described below with reference to fig. 1, and includes:
and 100, acquiring pulse echoes obtained by detecting targets to be detected in the sea surface environment by the coherent radar.
The electronic equipment acquires pulse echoes obtained by detecting targets to be detected in the sea surface environment by the coherent radar.
The coherent radar can be various shore radars or ship-borne radars. The phase correlation in the phase correlation radar means that the initial phase between pulses has certainty, that is, the initial phase of the first pulse may be random, but the phase between the subsequent pulse and the first pulse has certainty, and 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.
When the coherent radar continuously detects the sea surface target, the phase characteristics of land islands, strong interference targets or sea spikes are often linear under the condition of certain confidence coefficient permission. Therefore, the pulse echo obtained by detecting the target to be detected in the sea surface environment by the coherent radar is beneficial to obtaining the phase characteristics of the reference unit near the target to be detected. The reference units with strong phase linearity are conveniently screened out according to the phase characteristics of the reference units near the target to be detected.
Step 200, acquiring phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echoes.
The electronic device obtains phase information of a plurality of continuous pulse echoes of a first distance unit of the reference unit in the pulse echoes. The reference unit refers to distance units on the left side and the right side of the unit D to be detected in the CA-CFAR detection algorithm. The first distance unit refers to any one of 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 the distance units on the left and right sides of the unit D to be detected is determined.
For example, the electronic device acquires 10 or 16 consecutive pulse echoes of a certain distance unit in the reference unit of the pulse echo, and acquires their phase information.
Step 300, determining a linear relation of phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes;
The electronic device determines a linear relationship of phase information of the first range bin based on phase information of the plurality of successive pulse echoes. For example, step 300, the determining the linear relation of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes includes:
And 310, calculating the phase information of the plurality of continuous pulse echoes by a unitary linear regression method, and determining the linear relation of the phase information of the first distance unit.
In some embodiments, a large amount of measured data of pulse echoes of the coherent radar may be tested to find a suitable confidence, and whether the linear relationship of the phase information of the first distance unit is linearly related is determined within an allowable range of the confidence.
In one embodiment, in step 310, the calculating the phase information of the plurality of continuous pulse echoes by using a unitary linear regression method, determining the linear relationship of the phase information of the first distance unit specifically includes:
Step 311, calculating the phase information of the multiple continuous pulse echoes through Regress functions to obtain model statistics;
step 312, determining a linear relation of the phase information of the first distance unit according to the magnitude of the model statistic and the magnitude of the significant probability value.
For the convenience of calculation, the embodiment of the invention can use Regress functions in Matlab of a mathematical calculation tool to execute a unitary linear regression method on the phase information of the plurality of continuous pulse echoes, so that model statistics R 2 can be obtained. And judging whether the phases of the continuous pulse echoes of the first distance unit have a linear relation or not according to the magnitude of the model statistic R 2 and the magnitude of the significance probability value p.
In one embodiment, step 312, determining the linear relationship of the phase information of the first distance unit according to the magnitude of the model statistic and the magnitude of the saliency probability value specifically includes determining that the phase information of the first distance unit is linearly related when the model statistic is greater than or equal to a first set threshold and the saliency probability value is less than or equal to a second set threshold.
The first set threshold and the second set threshold may be determined by testing based on a lot of measured data of pulse echoes of a lot of coherent radars.
In the embodiment of the invention, when the default significance level of the model statistics R 2 with the value larger than 0.90 and the significance probability value p smaller than 0.05 is selected as the basis for judging linear correlation, as a result of eliminating excessive reference units with good linearity, a threshold is reduced, false alarms are easily generated and detection performance is influenced, when the default significance level of the model statistics R 2 with the value larger than 0.98 and the significance probability value p smaller than 0.05 is selected as the basis for judging linear correlation, as the eliminated reference units have fewer reference units, compared with the traditional CA-CFAR detector, detection performance is improved less and significance is not great, and a large number of actual measurement data tests prove that actual situation factors are synthesized, and when the model statistics R 2 with the value larger than 0.95 and the significance probability value p smaller than the default significance level of 0.05, the occurrence of the false alarms is avoided as much as possible while the detection performance is improved, so that whether the phase characteristics of the reference units are in linear correlation can be judged according to parameters. Fig. 3a and 3b are diagrams showing a linear correlation of phase characteristics, fig. 3a and 3b, respectively, using two consecutive 10 pulse echoes of the same distance unit, and fig. 3a and 3b are diagrams showing a nonlinear correlation of phase characteristics, respectively. Fig. 3a finds a default significance level where the model statistic R 2 value 0.9981 is greater than 0.95 and close to 1, and the significance probability value p 0.0133 is less than 0.05, and thus can be judged as a linear correlation, and fig. 3b finds a default significance level where the model statistic R 2 value 0.8343 is less than 0.95, and the significance probability value p is 0.2507 is greater than 0.05, and thus can be judged as a nonlinear correlation.
In the embodiment of the present invention, the range of the first set threshold is [0.95,0.98]. The first set threshold is preferably 0.95.
Step 400, deleting the pulse echo of the first distance unit under the condition that the linear relation is linearly related, and performing target detection on the target to be detected through a constant false alarm probability detection method based on the rest of the reference units.
In a coherent radar, if the phase linearity of the continuous pulse echo in the same distance unit is good, the continuous pulse echo may be a target, a strong clutter, an interference target or a land clutter in the distance unit. In order to obtain a more suitable detection threshold, reference units with better linearity near the unit to be detected D need to be removed. Therefore, under the condition that the linear relation of the phase information of the pulse echoes of the first distance unit is in linear correlation, deleting the pulse echoes of the first distance unit, and carrying out target detection on the target to be detected through a constant false alarm probability detection method based on the rest of the reference units.
In some embodiments, step 400, performing object detection on the object to be detected by using a constant false alarm probability detection method based on the rest of the reference units includes:
step 410, averaging based on pulse echoes of the rest reference units to obtain an updated background clutter power estimated value;
step 420, obtaining an updated threshold value based on the product of the updated background clutter power estimation value and the nominal factor;
and 430, performing target detection based on the comparison result of the updated threshold value and the pulse echo of the unit to be detected.
Referring to fig. 4, fig. 4 is a schematic diagram showing a calculation principle of the improved CA-CFAR method according to the present invention, where the present invention performs target detection on the target to be detected by a constant false alarm probability detection method based on the rest of the reference units. The selection rule of the unit to be detected D, the protection unit P, and the reference unit N in fig. 4 is identical to that of the classical CA-CFAR method in fig. 2, except that the reference units are selected on the left and right sides. In the embodiment of the invention, step 300 is screened out a first distance unit of a reference unit with good linearity, the pulse echo intensity is changed into zero, the numbers m and N of the pulse echo intensities at the left side and the right side equal to zero are counted in the sliding window process, then N reference units are summed and averaged, the average value at the moment is actually the average value of N- (m+n) reference units, namely a new background clutter power estimated value Z, the new background clutter power Z is multiplied by a normalization factor alpha to obtain a new threshold value, and finally the new threshold value is compared with a unit D to be detected to judge whether a target exists in the distance unit. For example, assuming that 32 reference units N are taken at the beginning, 16 reference units are taken at the left and right sides, and then strong targets or strong clutter with good linearity are removed under the judgment of phase linearity of certain model statistics, at this time, the actual number of the reference units may become 24, and the background clutter power estimated value obtained by using the rest reference units is far more suitable than that obtained by using 32 reference units.
According to the embodiment of the invention, the reference units with strong phase linearity are removed by judging the phase linearity condition of the continuous pulse echoes when the continuous pulse echoes are in the distance units of the same reference unit, so that the detection threshold with better adaptability of the unit to be detected is formed.
The following describes the detection performance of the constant false alarm probability detection method based on the phase characteristics in the embodiment of the invention, which is respectively applied to a uniform single-target background environment, a multi-target background environment and a clutter edge environment.
The constant false alarm probability detection method based on the phase characteristics of the embodiment of the invention is respectively applied to the detection performance of the uniform single-target background environment
Referring to fig. 5, fig. 5 shows a comparison of a detection performance curve (ROC curve, receiver operating characteristic curve, translated into a subject working characteristic curve, simply ROC curve) of a single target detection in a uniform single target background environment ML-CFAR detector (i.e., a mean-class constant false alarm detector), CMLD-CFAR detector (i.e., an estimated average level detector) and a modified CA-CFAR detection method according to an embodiment of the present invention. Under the condition of uniform clutter background and false alarm probability PFA=10 -6 and reference unit N=32, the ML-CFAR detector, the CMLD-CFAR detector and the detection performance curve (ROC curve) of the improved CA-CFAR detection method provided by the embodiment of the invention for single target detection. Wherein the ML-CFAR detector comprises an average detector (i.e., CA-CFAR) and a maximum detector (i.e., GO-CFAR and SO-CFAR). The CA-CFAR represents a unit average constant false alarm detector, the GO-CFAR represents a maximum selection constant false alarm detector, and the SO-CFAR represents a minimum selection constant false alarm detector.
In fig. 5, opt is an optimal detection performance curve corresponding to a specific signal-to-noise ratio, and other detection performance curves are, in order from top to bottom, an improved CA-CFAR detection method, CA-CFAR, CMLD-CFAR, GO-CFAR, SO-CFAR according to an embodiment of the present invention. It should be noted that, since there is only one target and the improved CA-CFAR detection method according to the embodiment of the present invention has a screening and rejecting effect only on the target with strong clutter or strong interference, the improved CA-CFAR detection method according to the embodiment of the present invention is consistent with the detection performance of the conventional CA-CFAR detector. The detection method for screening the reference unit by utilizing the phase characteristics does not lose the original detection function when the target signal-to-noise ratio is close to 19dB, the CMLD-CFAR has smaller signal-to-noise ratio loss compared with the CA-CFAR due to deleting part of the reference unit in the detection process, and the SO-CFAR has better detection performance in multi-target detection and larger signal-to-noise ratio loss for single-target detection.
Therefore, under a uniform single-target background, the constant false alarm probability detection method based on the phase characteristics, which is improved by the embodiment of the invention, is equivalent to the detection performance of the unit average constant false alarm, and is improved compared with the detection performance of other average constant false alarm detectors.
The constant false alarm probability detection method based on the phase characteristics of the embodiment of the invention is respectively applied to the detection performance of the multi-target background environment
In the detection of a multi-target background environment, a phenomenon that a target with high amplitude shields a target with low amplitude often occurs, so that the detection probability is reduced. Referring to fig. 6a, fig. 6a shows that 2 target signals with different sizes are simulated in the detection of the multi-target background environment, fig. 6a shows that two simulated targets with relatively close sizes are obtained, the power value of a large target is 5dB higher than that of a small target, the average clutter power is about 20dB, and the linearity of the phase characteristics of the position of the small target is better. Referring to fig. 6b, fig. 6b is a detection performance curve of a conventional CA-CFAR detector and the improved CA-CFAR detection method of the present invention using a phase feature to screen a reference unit for detecting a target with a larger power value (a large target signal-to-noise ratio is gradually increased from 0dB to 30dB, and a small target signal-to-noise ratio is increased with the large target signal-to-noise ratio) when the false alarm probability is 10 -6 and the reference unit n=32.
Fig. 6b shows ROC curves for a large target of the two targets. As can be seen from fig. 6b, when the target signal-to-noise ratio is smaller than 5dB, the detection performance of the two detectors is equivalent, and the detection performance of the two detectors is enhanced along with the improvement of the signal-to-noise ratio, when the system requirement detection probability reaches 50%, the conventional CA-CFAR detector needs to reach 17dB, and the improved CA-CFAR detection method of the present invention obtains a more suitable threshold by eliminating the reference unit where the small target is located, and can be detected only by reaching 14 dB. It can be seen that the detection performance of the improved CA-CFAR detection method of the present invention is superior to that of conventional CA-CFAR detectors.
Referring to fig. 7a, fig. 7a shows 4 simulated target signals, and fig. 7a shows four closely adjacent targets simulated by the 80,88,98,104 th distance unit of clutter, wherein the 80 th and 98 th distance units have sufficiently large power values and good phase linearity, and can be screened and removed by the constant false alarm probability detection method based on phase characteristics. The SO-CFAR detector with the best multi-target detection effect is selected from the average value type constant false alarm detectors, compared with the improved CA-CFAR detection method in the embodiment of the invention, the result is shown by the A display chart of FIG. 7b, and referring to FIG. 7b, the SO-CFAR detector can detect most targets in a plurality of targets, but the target power value of the 88 th distance unit is too small to be successfully detected, and the improved CA-CFAR detection method of the invention screens the reference unit to successfully detect all targets. Therefore, the improved CA-CFAR detection method provided by the embodiment of the invention can show the advantages in a multi-target detection simulation experiment and has better detection performance.
The constant false alarm probability detection method based on the phase characteristics of the embodiment of the invention is respectively applied to the detection performance of the clutter edge environment
The typical clutter edge environment is generally the place of the sea-land junction, and the energy mutation occurs in the distance dimension, so that the target at the low clutter edge is judged to be high-power clutter, and the detection omission is caused, and the edge clutter in the high-power area can be mistaken as the target, so that the false alarm is caused. The embodiment of the invention simulates the clutter edge environment, and adds two targets in the 88 th and 95 th distance units in the low power area, wherein the phase linearity of the left target is better, please refer to fig. 8a, fig. 8a shows 4 target signals simulated in the clutter edge environment, and fig. 8b shows the a-display detection threshold contrast. Referring to fig. 8b, fig. 8b shows a comparison between a GO-CFAR detector with a better clutter edge environment detection effect and the improved CA-CFAR detection method according to the embodiment of the present invention. Two thresholds are obtained in the case of the false alarm probability P FA＝10-6 at the reference unit n=32. From the results, both detectors successfully detected the first target, but the GO-CFAR detector failed to successfully detect the second target due to the impact of the large target; the improved CFAR detection method reduces the threshold at the target position through the improvement of the selection of the reference unit, and successfully detects the second target. In the clutter edge environment, the improved algorithm and the GO-CFAR have better detection performance, but when a plurality of targets exist in the clutter edge environment, the improved CA-CFAR detection method provided by the embodiment of the invention has better detection performance than the GO-CFAR detection method.
In summary, in the improved CFAR detector using the phase feature screening reference unit according to the embodiment of the present invention, since there is no reference unit to be removed in a uniform single-target clutter background, the detection performance of the improved CFAR detector is substantially consistent with that of the conventional CA-CFAR detection, and the detection performance of the improved CFAR detector in a multi-target background and a clutter edge background is superior to that of other average constant false alarm detectors.
To further verify the performance of the constant false alarm probability detection method based on the phase characteristics according to the embodiment of the present invention, a set of scan data (a set of 2239×2224 matrices, each row representing an azimuth/pulse, and each column representing a distance unit) is used for testing, and a P-display diagram of the scan data is shown in fig. 9, and referring to fig. 9, fig. 9 shows a P-display diagram of the scan data according to the embodiment of the present invention. The set of scan data records information for the radar scan range 259.445 ° to 0 ° to 125.992 °.
In the method for detecting the CA-CFAR, which is improved by the embodiment of the invention, whether the value of the model statistic R 2 is larger than 0.95 and whether the significance probability value p is smaller than 0.05 is used as a standard for linear judgment, wherein the number of the ships is about 71.781 degrees, the number of the ships is about the distance units 1501, 1784 and 1791, the number of the reference units N is 64, the number of the protection units is about four due to factors such as the width of the ships, the constant false alarm rate PFA is 10 -4, and the test results are shown in fig. 10a and 10 b. Referring to fig. 10a, fig. 10a shows a threshold comparison of a conventional CA-CFAR device and an improved CA-CFAR method according to an embodiment of the invention. In the vicinity of 1501 distance units, the main target amplitude is large enough and the adjacent interference target amplitude is small, so that the target ship can be detected by the conventional CA-CFAR detection method and the improved CA-CFAR detection method of the embodiment of the invention, but the improved CA-CFAR detection of the embodiment of the invention can be detected by only needing lower power values, and in the vicinity of 1784 and 1791 distance units, the target shielding phenomenon is caused by adopting the conventional CA-CFAR detector due to the fact that the main target is close to the strong sea clutter or the strong interference target, and the target is successfully detected by adopting the improved CA-CFAR detection method of the embodiment of the invention. The test results of the improved CA-CFAR detection of the improved CA-CFAR and the improved SO-CFAR detection of the embodiment of the invention are shown in FIG. 10b, and FIG. 10b shows the threshold comparison of the conventional SO-CFAR with the improved CA-CFAR method of the embodiment of the invention. Both successfully detect the target, but due to the reduced threshold, a false alarm may exist.
According to the embodiment of the invention, the detection background is more in line with the use premise of the mean value CFAR by deleting the distance unit where the strong clutter or strong interference target with good phase linearity is located. According to analysis verification of simulation data and measured data, the improved CA-CFAR method can detect targets which cannot be detected by the traditional CA-CFAR under a multi-target environment and a clutter edge environment, effectively solves the problem of target shielding without losing original detection performance, and has good detection performance improvement compared with other average value constant false alarm CFARs, so that effectiveness of the improved CA-CFAR method is shown.
The method comprises the steps of obtaining pulse echoes obtained by detecting targets to be detected in sea surface environment through 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 echoes, determining a linear relation of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes, deleting the pulse echoes of the first distance unit under the condition that the linear relation is linearly related, and detecting the targets to be detected through a constant false alarm probability detection method based on the rest of the reference units. When the coherent radar is adopted to continuously detect the target to be detected in the sea surface environment, the phase characteristics of land islands, strong interference targets or sea spikes are often linear under the condition of certain confidence coefficient permission. Therefore, the method and the device for detecting the target to be detected based on the continuous pulse echo comprise the steps of determining the linear relation of the phase information of the first distance unit based on the phase information of a plurality of continuous pulse echoes of the first distance unit of the reference units in the pulse echoes, deleting the pulse echo of the first distance unit under the condition that the linear relation is in linear correlation, and detecting the target to be detected based on the rest of the reference units through a constant false alarm probability detection method. Therefore, strong interference targets or strong sea clutter near the target to be detected are screened and removed, so that the amplitude probability density function of the sea clutter better accords with Rayleigh distribution, the background clutter power is not influenced by the interference targets, the precondition of using the CFAR detection method is better met, meanwhile, the condition that the detection threshold is possibly accidentally raised by interference factors of a first distance unit with linear relation is avoided, the detection performance of target detection is improved, and missed detection is reduced.
The constant false alarm probability detection device based on the phase characteristics provided by the invention is described below, and the constant false alarm probability detection device based on the phase characteristics described below and the constant false alarm probability detection method based on the phase characteristics described above can be correspondingly referred to each other.
Referring to fig. 11, the present invention provides a constant false alarm probability detection device based on phase characteristics, which includes:
The first acquisition module 201 is configured to acquire a pulse echo obtained by detecting a target to be detected in a sea surface environment by using a coherent radar;
A second acquisition module 202, configured to acquire phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echoes;
a linear relation determining module 203, configured to determine a linear relation of phase information of the first distance unit based on phase information of the plurality of continuous pulse echoes;
and the target detection module 204 is configured to delete the pulse echo of the first distance unit if the linear relationship meets a preset condition, and perform target detection on the target to be detected by using a constant false alarm probability detection method based on the rest of the reference units.
In one embodiment, the linear relation determining module is configured to calculate phase information of the plurality of continuous pulse echoes by using a unitary linear regression method, and determine a linear relation of the phase information of the first distance unit.
In one embodiment, the calculating the phase information of the plurality of continuous pulse echoes by a unitary linear regression method determines a linear relationship of the phase information of the first distance unit, and specifically includes calculating the phase information of the plurality of 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 magnitude of the model statistic and the magnitude of the significance probability value.
In one embodiment, the determining the linear relation of the phase information of the first distance unit according to the magnitude of the model statistic and the magnitude of the significance probability value includes:
And when the model statistic is greater than or equal to a first set threshold value and the significance probability value is less than or equal to a second set threshold value, determining that the phase information of the first distance unit is in linear correlation.
In one embodiment, the first set threshold is in the range of [0.95,0.98].
In one embodiment, the object detection module includes:
the updated background clutter power estimation value calculation module is used for obtaining an updated background clutter power estimation value based on the average value of pulse echoes of the rest reference units;
The updating threshold value calculation module is used for obtaining an updating threshold value based on the product of the updating background clutter power estimation value and the nominal factor;
And the final target detection module is used for carrying out target detection based on the comparison result of the updated threshold value and the pulse echo of the unit to be detected.
The constant false alarm probability detection device based on the phase characteristics is used for detecting a to-be-detected target in a sea surface environment by acquiring pulse echoes obtained by a coherent radar, acquiring phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echoes, determining a linear relation of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes, deleting the pulse echoes of the first distance unit under the condition that the linear relation is linearly related, and detecting the to-be-detected target through a constant false alarm probability detection method based on the rest of the reference units. When the coherent radar is adopted to continuously detect the target to be detected in the sea surface environment, the phase characteristics of land islands, strong interference targets or sea spikes are often linear under the condition of certain confidence coefficient permission. Therefore, the method and the device for detecting the target to be detected based on the continuous pulse echo comprise the steps of determining the linear relation of the phase information of the first distance unit based on the phase information of a plurality of continuous pulse echoes of the first distance unit of the reference units in the pulse echoes, deleting the pulse echo of the first distance unit under the condition that the linear relation is in linear correlation, and detecting the target to be detected based on the rest of the reference units through a constant false alarm probability detection method. Therefore, strong interference targets or strong sea clutter near the target to be detected are screened and removed, so that the amplitude probability density function of the sea clutter better accords with Rayleigh distribution, the background clutter power is not influenced by the interference targets, the precondition of using the CFAR detection method is better met, meanwhile, the condition that the detection threshold is possibly accidentally raised by interference factors of a first distance unit with linear relation is avoided, the detection performance of target detection is improved, and missed detection is reduced.
Fig. 12 illustrates a physical schematic diagram of an electronic device, as shown in fig. 12, which may include a processor (processor) 1210, a communication interface (Communications Interface) 1220, a memory 1230, and a communication bus 1240, where the processor 1210, the communication interface 1220, and the memory 1230 perform communication with each other through the communication bus 1240. The processor 1210 may invoke logic instructions in the memory 1230 to perform a constant false alarm probability detection method based on phase characteristics, where the method includes acquiring pulse echoes obtained by detecting a target to be detected in a sea surface environment by a coherent radar, acquiring phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echoes, 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, deleting the pulse echoes of the first distance unit if the linear relationship is linearly related, and performing target detection on the target to be detected by a constant false alarm probability detection method based on the remaining reference units.
In addition, the logic instructions in the memory 1230 described above may be implemented in the form of software functional units and sold or used as a stand-alone product, stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. The storage medium includes a U disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes.
In another aspect, the invention further provides a computer program product, the computer program product comprises a computer program, 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 program can execute the constant false alarm probability detection method based on the phase characteristics provided by the above methods, the method comprises the steps of acquiring pulse echoes obtained by detecting a target to be detected in sea surface environment by using a coherent radar, acquiring phase information of a plurality of continuous pulse echoes of a first distance unit of a reference unit in the pulse echoes, determining a linear relation of the phase information of the first distance unit based on the phase information of the plurality of continuous pulse echoes, deleting the pulse echoes of the first distance unit under the condition that the linear relation is in linear relation, and carrying out target detection on the target to be detected by using the constant false alarm probability detection method based on the rest of the reference unit.
In yet another aspect, the present invention further provides a non-transitory computer readable storage medium, on which a computer program is stored, the computer program being implemented when executed by a processor to perform the constant false alarm probability detection method based on phase characteristics provided by the above methods, where the method includes obtaining pulse echoes 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 echoes, 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, deleting the pulse echoes of the first distance unit if the linear relationship is linearly related, and performing target detection on the target to be detected by the constant false alarm probability detection method based on the rest of the reference units.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
It should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention, and not for limiting the same, and although the present invention has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the technical solution described in the above-mentioned embodiments may be modified or some technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present invention.
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