A method and device for analyzing detection performance of radar weak target hybrid accumulation

Abstract

The application discloses a radar weak target mixed accumulation detection performance analysis method and device. According to a medium undulation Rayleigh model, radar echoes are divided into a plurality of subframes. Each subframe contains a plurality of pulses, and the total number of accumulated pulses is obtained. A plurality of subframes are subjected to coherent accumulation processing to obtain coherent accumulation results of the plurality of subframes. The coherent accumulation results of the plurality of subframes are subjected to non-coherent accumulation processing to obtain mixed accumulation results of the plurality of subframes. The distribution of the mixed accumulation results of the subframes under the conditions of target absence and target presence is analyzed respectively to obtain closed expressions of false alarm probability and detection probability. Through analysis, a positive correlation coefficient of the optimal subframe length and the total number of accumulated pulses is obtained, and the optimal subframe length is obtained according to the positive correlation coefficient, so that the best detection performance is achieved. The application can be widely applied to the processing of radar and sonar signals.

Description

Technical Field

[0001] The present invention relates to the field of signal processing technology, and in particular to a radar weak target mixed accumulation detection performance analysis method and device. Background Art

[0002] Long-term integration algorithms are effective methods for improving the signal-to-noise ratio (SNR) in radar faint target detection. Most existing long-term integration algorithms implicitly assume that the radar cross section (RCS) does not fluctuate during the coherent processing interval (CPI). However, in practical applications, amplitude and phase fluctuations of the RCS during observation are almost unavoidable. Especially when observation times are long, target echoes may be partially correlated. Therefore, a more general fluctuation model, known as the medium-fluctuation target model, should be adopted. However, for the medium-fluctuation model, a more general and accurate closed-form analytical formula for evaluating hybrid integration detection performance and guiding the selection of hybrid integration subframe length is lacking.

[0003] Therefore, how to invent a mixed accumulation detection performance analysis method and provide a more general and accurate theoretical model to evaluate the detection performance of mixed accumulation medium-fluctuation Rayleigh targets has become an urgent problem to be solved. Summary of the Invention

[0004] To this end, the present invention provides a radar weak target mixed accumulation detection performance analysis method and device, by providing a more general and accurate theoretical model to evaluate the detection performance of mixed accumulation medium fluctuation Rayleigh targets, obtain a closed expression of the mixed accumulation detection performance, based on which the subframe is divided to obtain the optimal detection performance.

[0005] To achieve the above object, the present invention provides the following technical solution: a radar weak target mixed accumulation detection performance analysis method, comprising:

[0006] According to a moderate undulation Rayleigh model, the radar echo is divided into a plurality of subframes; each of the subframes includes a plurality of pulses; and a total accumulated pulse number is calculated based on the subframes and the pulses;

[0007] performing coherent accumulation processing on the plurality of subframes to obtain coherent accumulation results of the plurality of subframes;

[0008] performing non-coherent accumulation processing on the coherent accumulation results of the plurality of subframes to obtain mixed accumulation results of the plurality of subframes;

[0009] Analyzing the distribution of the subframe mixed accumulation results under the target absence condition to obtain the false alarm probability;

[0010] According to the false alarm probability, a detection threshold is reversely calculated and obtained; according to the detection threshold, a distribution of the subframe mixed accumulation result under a target existing condition is analyzed, and a closed expression of a detection probability is obtained;

[0011] Through the closed expression of the detection probability, performance of a moderately fluctuating Rayleigh target in mixed accumulation detection is analyzed, a positive correlation coefficient of an optimal subframe length and the total number of accumulated pulses is obtained, and according to the positive correlation coefficient and the total number of accumulated pulses, the optimal subframe length is calculated and obtained, so that the best detection performance is achieved.

[0012] As a preferred scheme of the radar weak target mixed accumulation detection performance analysis method, the expression of the moderately fluctuating Rayleigh model is:

[0013]

[0014] In the expression, s is a signal sample; σ is a variance of the signal sample s; ρ is a correlation coefficient, representing a correlation degree of RCS between adjacent pulses; and N is a pulse number.

[0015] As a preferred scheme of the radar weak target mixed accumulation detection performance analysis method, in a process of carrying out coherent accumulation processing on a plurality of subframes to obtain a plurality of subframe coherent accumulation results, an expression of the subframe coherent accumulation result is:

[0016]

[0017] In the expression, z k is a subframe; i is an i-th subframe; and N b is a pulse number contained in each subframe.

[0018] As a preferred scheme of the radar weak target mixed accumulation detection performance analysis method, in a process of carrying out non-coherent accumulation processing on a plurality of subframe coherent accumulation results to obtain a plurality of subframe mixed accumulation results, an expression of the subframe mixed accumulation result is:

[0019]

[0020] In the expression, N s is a subframe number; z ci is a subframe coherent accumulation result.

[0021] As a preferred scheme of the radar weak target mixed accumulation detection performance analysis method, an expression of the false alarm probability is:

[0022]

[0023] In the expression, I(·) is an incomplete gamma function. is the variance after coherent accumulation within the subframe; T is the detection threshold.

[0024] As a preferred solution for a radar weak target mixed accumulation detection performance analysis method, the closed-form expression for the detection probability is:

[0025]

[0026] Where z h is the sub-frame mixed accumulation result; σ 2 is the variance of the signal component and the noise component.

[0027] The present invention also provides a radar weak target mixed accumulation detection performance analysis device, based on the above radar weak target mixed accumulation detection performance analysis method, comprising:

[0028] A radar echo division processing module is used to divide the radar echo into a number of subframes according to a medium-fluctuation Rayleigh model; each subframe contains a number of pulses; and a total accumulated pulse number is calculated based on the subframes and the pulses;

[0029] A coherent accumulation processing module, configured to perform coherent accumulation processing on the plurality of subframes to obtain coherent accumulation results of the plurality of subframes;

[0030] a non-coherent accumulation processing module, configured to perform non-coherent accumulation processing on the coherent accumulation results of the sub-frames to obtain mixed accumulation results of the sub-frames;

[0031] a false alarm probability acquisition module, configured to analyze the distribution of the subframe mixed accumulation results under target absence conditions to obtain a false alarm probability;

[0032] A detection probability closed expression acquisition module is used to reversely calculate and obtain a detection threshold based on the false alarm probability; based on the detection threshold, the distribution of the subframe mixed accumulation results under the condition of target presence is analyzed to obtain a closed expression for the detection probability;

[0033] The optimal subframe length acquisition module is used to analyze the performance of mixed accumulation detection of medium-fluctuation Rayleigh targets through the closed expression of the detection probability, and obtain the positive correlation coefficient between the optimal subframe length and the total number of accumulated pulses; based on the positive correlation coefficient and the total number of accumulated pulses, the optimal subframe length is calculated to achieve the best detection performance.

[0034] As a preferred solution of a radar weak target mixed accumulation detection performance analysis device, in the radar echo division processing module, the medium fluctuation Rayleigh model expression is:

[0035]

[0036] Where, is the variance of signal samples; p is the correlation coefficient, representing the correlation degree of RCS between adjacent pulses; and N is the number of pulses.

[0037] As a preferred scheme of the radar weak target hybrid accumulation detection performance analysis device, in the coherent accumulation processing module, in the process of performing coherent accumulation processing on the plurality of subframes to obtain a plurality of subframe coherent accumulation results, the expression of the subframe coherent accumulation result is:

[0038]

[0039] In the formula, z k is a subframe; i is the i-th subframe; N b is the number of pulses contained in each subframe.

[0040] As a preferred scheme of the radar weak target hybrid accumulation detection performance analysis device, in the non-coherent accumulation processing module, in the process of performing non-coherent accumulation processing on the plurality of subframe coherent accumulation results to obtain a plurality of subframe hybrid accumulation results, the expression of the subframe hybrid accumulation result is:

[0041]

[0042] In the formula, N s is the number of subframes; is the subframe coherent accumulation result.

[0043] As a preferred scheme of the radar weak target hybrid accumulation detection performance analysis device, in the false alarm probability acquisition module, the expression of the false alarm probability is:

[0044]

[0045] In the formula, I(·) is an incomplete gamma function; is the variance of the coherent accumulation result in the subframe; and T is a detection threshold.

[0046] As a preferred scheme of the radar weak target hybrid accumulation detection performance analysis device, in the detection probability closed expression acquisition module, the closed expression of the detection probability is:

[0047]

[0048] In the formula, z h is the subframe hybrid accumulation result; σ 2 is the variance of the signal component and the noise component.

[0049] The present application has the following advantages: according to a moderate fluctuation Rayleigh model, radar echoes are divided into several subframes; each of the subframes contains several pulses; the total number of accumulated pulses is obtained according to the subframes and the pulses; several subframe coherent accumulation results are obtained by performing coherent accumulation processing on several of the subframes; several subframe hybrid accumulation results are obtained by performing non-coherent accumulation processing on the subframe coherent accumulation results; the false alarm probability is obtained by analyzing the distribution of the subframe hybrid accumulation results under the condition of target absence; the detection threshold is obtained by back-calculation according to the false alarm probability; the closed expression of the detection probability is obtained by analyzing the distribution of the subframe hybrid accumulation results under the condition of target presence according to the detection threshold; the positive correlation coefficient of the optimal subframe length and the total number of accumulated pulses is obtained by analyzing the performance of the hybrid accumulation detection of the moderate fluctuation Rayleigh target through the closed expression of the detection probability; and the optimal subframe length is obtained according to the positive correlation coefficient and the total number of accumulated pulses, so as to achieve the best detection performance. The radar weak target hybrid accumulation detection performance analysis method and device provided by the present application are more general, can analyze the fluctuation models of Swerling I and Swerling II and the fluctuation models between the two, and obtain the closed analytical expression of the hybrid accumulation detection performance of the moderate fluctuation Rayleigh target, so that the optimal subframe length can be obtained in numerical value to achieve the optimal detection performance. The present application can be widely applied to the processing of radar and sonar signals. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the following embodiment or prior art description will be briefly introduced. Obviously, the drawings in the following description are only exemplary, and for those skilled in the art, other drawings can be obtained by the provided drawings without creative labor.

[0051] The structures, proportions, sizes, etc. shown in the present specification are only used to cooperate with the content disclosed in the specification, so that those skilled in the art can understand and read, and are not used to limit the conditions that the present application can be implemented, so they do not have technical significance. Any modification of the structure, change of the proportion relationship or adjustment of the size, without affecting the effects and purposes that the present application can produce, should still fall within the scope of the technical content disclosed by the present application.

[0052] Figure 1 A radar weak target hybrid accumulation detection performance analysis method flowchart is provided in embodiment 1 of the present application;

[0053] Figure 2A medium fluctuation Rayleigh target mixed accumulation detection performance evaluation flowchart in a radar weak target mixed accumulation detection performance analysis method provided in embodiment 1 of the present application;

[0054] Figure 3 A medium fluctuation target amplitude and phase variation with pulse number diagram in a radar weak target mixed accumulation detection performance analysis method provided in embodiment 1 of the present application;

[0055] Figure 4 A medium fluctuation Rayleigh target mixed accumulation detection performance evaluation result diagram in a radar weak target mixed accumulation detection performance analysis method provided in embodiment 1 of the present application; wherein a is a detection probability at different input signal-to-noise ratios; b is a detection probability at different false alarm probabilities;

[0056] Figure 5 An optimal subframe length analysis result diagram in a radar weak target mixed accumulation detection performance analysis method provided in embodiment 1 of the present application; wherein a is an optimal subframe length at different correlation coefficients; b is an optimal subframe length at different total accumulation pulse numbers;

[0057] Figure 6 An apparatus architecture diagram in a radar weak target mixed accumulation detection performance analysis method provided in embodiment 2 of the present application. DETAILED DESCRIPTION

[0058] The embodiments of the present application will be described herein below with reference to specific embodiments. Those skilled in the art will readily understand other advantages and functions of the present application after reading the description of the embodiments revealed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0059] Embodiment 1

[0060] Referring to Figure 1 and Figure 2 , embodiment 1 of the present application provides a radar weak target mixed accumulation detection performance analysis method, comprising the following steps:

[0061] S1, according to a medium fluctuation Rayleigh model, dividing radar echoes into a plurality of subframes; each of the subframes contains a plurality of pulses; calculating a total accumulation pulse number according to the subframes and the pulses;

[0062] S2, performing coherent accumulation processing on the plurality of subframes to obtain a plurality of subframe coherent accumulation results;

[0063] S3, performing non-coherent accumulation processing on the coherent accumulation results of the plurality of subframes to obtain mixed accumulation results of the plurality of subframes;

[0064] S4. Analyze the distribution of the subframe mixed accumulation results under the target absence condition to obtain a false alarm probability;

[0065] S5. Based on the false alarm probability, reversely calculate and obtain a detection threshold; based on the detection threshold, analyze the distribution of the subframe mixed accumulation results under the condition that the target exists to obtain a closed expression for the detection probability;

[0066] S6. Analyze the performance of mixed accumulation detection of medium-fluctuation Rayleigh targets through the closed expression of the detection probability to obtain the positive correlation coefficient between the optimal subframe length and the total number of accumulated pulses; and calculate the optimal subframe length based on the positive correlation coefficient and the total number of accumulated pulses to achieve the best detection performance.

[0067] In this embodiment, in step S1, the radar echo is divided into a number of subframes according to the medium-fluctuation Rayleigh model; each subframe contains a number of pulses; and the total number of accumulated pulses is calculated based on the subframes and the pulses.

[0068] Specifically, assuming the radar echo Satisfy the moderate undulation Rayleigh model, according to the moderate undulation Rayleigh model, the radar echo Divided into N s subframes, each subframe contains N b pulses, such as the first subframe is Total accumulated pulse number N=N b ×N s , where N, N b 、N s All are positive integers.

[0069] The moderate fluctuation Rayleigh model is as follows:

[0070] Assuming that the radar echo of a moderately fluctuating Rayleigh target is a sequence of N pulses, the measured complex vector It can be expressed as:

[0071]

[0072] in[·] T represents the transpose operation, It can be further expressed as:

[0073]

[0074] where n=[n1,n2,...,n N ] Tis the noise sampling, s=[s1,s2,...,s N ] T is the signal sampling. It is generally assumed that n is a zero-mean complex Gaussian random vector, independent of s. In addition, the elements in n are independent of each other, and the variance is For the signal term, assume that s is also a zero-mean complex Gaussian random vector. The elements in s are partially correlated with each other, and the variance is Therefore, the input signal-to-noise ratio can be expressed as To describe the characteristics of medium fluctuations, the covariance matrix C = E{ss H}, where H represents the conjugate transpose operation and E{·} represents the expectation operation. Assuming that the correlation of the moderate fluctuation Rayleigh model obeys the exponential decay model, then

[0075]

[0076] Where ρ is the correlation coefficient, which indicates the correlation degree of RCS between adjacent pulses. When ρ = 1, ρ = 0 and 0 < ρ < 1, the amplitude and phase of the medium-fluctuation target change with the accumulated pulse number as shown in the figure below: Figure 3 shown.

[0077] In this embodiment, in step S2, a coherent accumulation process is performed on the plurality of subframes to obtain a plurality of subframe coherent accumulation results;

[0078] Specifically, a coherent accumulation process is performed on a plurality of said subframes to obtain a plurality of subframe coherent accumulation results.

[0079]

[0080] The expression of the subframe coherent accumulation result is:

[0081]

[0082] Where z k is the subframe; i is the i-th subframe; N b The number of pulses contained in each subframe.

[0083] In this embodiment, in step S3, non-coherent accumulation processing is performed on the coherent accumulation results of the plurality of sub-frames to obtain mixed accumulation results of the plurality of sub-frames;

[0084] Specifically, the coherent accumulation results of several subframes are Perform non-coherent accumulation processing to obtain mixed accumulation results of several subframes z h ;

[0085] The expression of the subframe mixed accumulation result is:

[0086]

[0087] Where N s is the number of subframes; The result is subframe coherent accumulation.

[0088] In this embodiment, in step S4, the distribution of the subframe mixed accumulation results under the target absence condition is analyzed to obtain the false alarm probability;

[0089] Specifically, the subframe mixed accumulation result z h Analyze the distribution under the condition of target absence H0 and obtain the false alarm probability P FA ;

[0090] Initial echo under H0 condition Contains only noise, and the noise is independent and identically distributed. Therefore, after coherent accumulation within the subframe, z ci |H0 is still a zero-mean complex Gaussian variable. Its variance is Therefore, after taking the square sum of its modulus value, z h |H0 obeys the parameter 2N s and The generalized chi-square distribution of . Then z h The probability density function of H0 is:

[0091]

[0092] False alarm probability P FA The above formula can be obtained by integrating from the detection threshold T to positive infinity:

[0093]

[0094] Using the incomplete gamma function

[0095]

[0096] and its properties

[0097]

[0098] The false alarm probability can be further written as:

[0099]

[0100] Where I(·) is the incomplete gamma function; is the variance after coherent accumulation within the subframe; T is the detection threshold.

[0101] In this embodiment, in step S5, the detection threshold is obtained by back calculation according to the false alarm probability; the distribution of the subframe mixed accumulation result under the condition of existence of the target is analyzed according to the detection threshold, and a closed expression of the detection probability is obtained;

[0102] Specifically, the false alarm probability P FA obtained in S4 is back calculated to obtain the detection threshold T, and the distribution of z h under the condition of existence of the target H1 is analyzed again.

[0103] Under the condition of H1, the initial echo z contains signal and noise. The noise term and the signal term are independent, so they can be considered separately. After coherent accumulation in each subframe, the noise component is the same as S4. The signal term s also obeys a zero-mean complex Gaussian distribution after coherent accumulation in each subframe, but because the covariance matrix is C, its variance is:

[0104]

[0105] In the formula, C ij is an element in C, and substituting C into the above formula has:

[0106]

[0107] Combining the signal component and the noise component, z ci |H1 obeys a zero-mean complex Gaussian distribution, and the variance is In order to obtain the analytical expression of P D , an approximate method is adopted, assuming that the coherent accumulation results of different subframes are completely decorrelated. Therefore, after taking the square sum of the modulus values, z h |H1 obeys a generalized chi-square distribution with parameters 2N s and σ 2 / 2. Then the probability density function of z h |H1 is:

[0108]

[0109] In practice, for a given false alarm probability value, the threshold T can be given by the following formula:

[0110]

[0111] In the formula, G -1 represents the inverse of the incomplete gamma function.

[0112] Finally, the probability density function of z h |H1 is integrated from the threshold T to positive infinity to obtain the probability of detection P D , that is:

[0113]

[0114] The above formula can be degenerated into Swerling I type detection probability when p = 1:

[0115]

[0116] The above formula can be degenerated into Swerling II type detection probability when p = 0:

[0117]

[0118] P D Monte Carlo simulation verification is performed, the accumulated total pulse number is set to 4096, the correlation coefficient is 0.99, the false alarm probability is fixed to 10 -8 , and the input signal-to-noise ratio is changed to obtain the detection performance curve. The specific process is that the input signal-to-noise ratio range is set to -25dB to 5dB with a step of 0.5dB. For each value of the input signal-to-noise ratio, a noise sequence with unit variance and a signal sequence with a covariance matrix C are generated. Then, the noise sequence and the signal sequence are summed to obtain a pulse sequence z h . z h is compared with a threshold to determine whether the target is detected. The process is repeated 1000 times to obtain the statistical result of the detection probability. Similarly, the input signal-to-noise ratio is fixed to -18dB, and the detection performance curve under different false alarm probabilities is generated. As Figure 4 shown, the solid line is the result obtained by the above formula, and the mark is the result obtained by Monte Carlo simulation, which proves the correctness of the theoretical derivation.

[0119] In this embodiment, in step S6, the performance of the mixed accumulation detection of the moderately fluctuating Rayleigh target is analyzed by the closed expression of the detection probability, the optimal subframe length is obtained in positive correlation with the accumulation total pulse number according to the positive correlation coefficient and the accumulation total pulse number, and the optimal detection performance is achieved.

[0120] Specifically, according to the formula of the detection probability P D obtained in step S5, it can be known that the detection probability is jointly influenced by the subframe length, the correlation coefficient, the accumulation total pulse number, the false alarm probability and the input signal-to-noise ratio. In order to maximize the detection probability, it is very important to select a suitable subframe length. Referring to Figure 4 , it can be known that although there are intersection points between the curves, the optimal subframe length remains unchanged regardless of the changes of the input signal-to-noise ratio and the false alarm probability. Therefore, the input signal-to-noise ratio and the false alarm probability have little influence on the selection of the subframe length and can be ignored. Then, the influence of the correlation coefficient and the accumulation total pulse number on the optimal subframe length is analyzed. The accumulation total pulse number is set to 4096, and the false alarm probability is set to 10-8 , the input signal-to-noise ratio is -16.4dB, and the optimal sub-frame length under different correlation coefficient values is calculated. Similarly, the correlation coefficient is set to 0.99, and the optimal sub-frame length under different total accumulated pulse numbers is calculated. As shown in FIG. 4, the optimal sub-frame length when the detection probability is maximum is positively correlated with the total accumulated pulse number and the correlation coefficient. After the total accumulated pulse number and the correlation coefficient of the echo are known, the optimal sub-frame length can be determined according to the present application to achieve the best detection performance. Figure 5

[0121] In summary, according to the present application, the radar echo is divided into a plurality of sub-frames according to the moderate fluctuation Rayleigh model; each of the sub-frames contains a plurality of pulses; the total accumulated pulse number is calculated according to the sub-frames and the pulses; a plurality of sub-frame coherent accumulation results are obtained by performing coherent accumulation processing on a plurality of the sub-frames; a plurality of sub-frame hybrid accumulation results are obtained by performing non-coherent accumulation processing on a plurality of the sub-frame coherent accumulation results; the false alarm probability is obtained by analyzing the distribution of the sub-frame hybrid accumulation results under the condition of target absence; the detection threshold is obtained by back-calculation according to the false alarm probability; the closed expression of the detection probability is obtained by analyzing the distribution of the sub-frame hybrid accumulation results under the condition of target presence according to the detection threshold; the positive correlation coefficient of the optimal sub-frame length and the total accumulated pulse number is obtained by analyzing the performance of the moderate fluctuation Rayleigh target in the hybrid accumulation detection through the closed expression of the detection probability; and the optimal sub-frame length is calculated according to the positive correlation coefficient and the total accumulated pulse number, so as to achieve the best detection performance. The radar weak target hybrid accumulation detection performance analysis method and device provided by the present application are more general, can analyze the fluctuation models of Swerling I and Swerling II and the fluctuation models between the two, and obtain the closed analytical expression of the hybrid accumulation detection performance of the moderate fluctuation Rayleigh target, so that the optimal sub-frame length can be obtained in numerical value to achieve the optimal detection performance. The present application can be widely applied to the processing of radar and sonar signals.

[0122] It should be noted that the method of the present embodiment can be performed by a single device, such as a computer or a server. The method of the present embodiment can also be applied in a distributed scenario, and completed by multiple devices cooperating with each other. In this distributed scenario, one of the multiple devices can only perform one or more steps in the method of the present embodiment, and the multiple devices can interact with each other to complete the method.

[0123] ​It is to be understood that the foregoing description is directed to some embodiments of the disclosure. Various changes can be made to the application claimed without departing from the scope of the disclosure. In some instances, the acts or steps can occur in different orders, and / or with peripheral actions or steps not presented and still be within the scope of aspects of the disclosure. Additionally, manifestations of a process are not restricted to sequential processes, but can also have additional features of parallel processes or heuristics that require no specific sequence. Some embodiments of the present disclosure can be implemented in different embodiments and of different types. Specifically, the claimed application is intended to be implemented by any combination of hardware, firmware, and / or software that integrates a television with a computer to provide a television computer.

[0124] Embodiment 2

[0125] Referring to Figure 6 Embodiment 2 of the present application also provides a radar weak target mixed accumulation detection performance analysis device, comprising:

[0126] A radar echo division processing module 001 is configured to divide radar echoes into a plurality of subframes according to a moderate fluctuation Rayleigh model; each of the subframes contains a plurality of pulses; and the total number of accumulated pulses is calculated according to the subframes and the pulses.

[0127] A coherent accumulation processing module 002 is configured to perform coherent accumulation processing on the plurality of subframes to obtain coherent accumulation results of the plurality of subframes.

[0128] A non-coherent accumulation processing module 003 is configured to perform non-coherent accumulation processing on the coherent accumulation results of the plurality of subframes to obtain mixed accumulation results of the plurality of subframes.

[0129] A false alarm probability acquisition module 004 is configured to analyze the distribution of the mixed accumulation results of the plurality of subframes under the condition of absence of a target to obtain a false alarm probability.

[0130] A detection probability closed expression acquisition module 005 is configured to inversely calculate a detection threshold according to the false alarm probability; and analyze the distribution of the mixed accumulation results of the plurality of subframes under the condition of presence of a target to obtain a closed expression of a detection probability according to the detection threshold.

[0131] An optimal subframe length acquisition module 006 is configured to analyze the performance of a moderate fluctuation Rayleigh target in mixed accumulation detection by using the closed expression of the detection probability to obtain a positive correlation coefficient of an optimal subframe length and the total number of accumulated pulses; and calculate the optimal subframe length according to the positive correlation coefficient and the total number of accumulated pulses to achieve the best detection performance.

[0132] In this embodiment, the expression of the moderate fluctuation Rayleigh model in the radar echo division processing module 001 is:

[0133]

[0134] In the formula, n is the total number of accumulated pulses, K is the number of subframes, and T is the length of each subframe. is the variance of the signal sample s; p is the correlation coefficient, representing the correlation degree of the RCS between adjacent pulses; and N is the number of pulses.

[0135] In the phase correlation accumulation processing module 002 in this embodiment, in the process of performing phase correlation accumulation processing on the subframes to obtain phase correlation accumulation results of the subframes, the expression of the phase correlation accumulation result of the subframe is:

[0136]

[0137] In the expression, z k is a subframe; i is the i-th subframe; N b is the number of pulses contained in each subframe.

[0138] In the non-phase correlation accumulation processing module 003 in this embodiment, in the process of performing non-phase correlation accumulation processing on the phase correlation accumulation results of the subframes to obtain hybrid accumulation results of the subframes, the expression of the hybrid accumulation result of the subframe is:

[0139]

[0140] In the expression, N s is the number of subframes; z ci is the phase correlation accumulation result of the subframe.

[0141] In the false alarm probability obtaining module 004 in this embodiment, the expression of the false alarm probability is:

[0142]

[0143] In the expression, I(·) is an incomplete gamma function; is the variance of the phase correlation accumulation result in the subframe; and T is a detection threshold.

[0144] In the closed expression of the detection probability obtaining module 005 in this embodiment, the closed expression of the detection probability is:

[0145]

[0146] In the expression, z h is the hybrid accumulation result of the subframe; and σ 2 is the variance of the signal component and the noise component.

[0147] It should be noted that the information interaction and execution process between the modules of the system described above are based on the same concept as the method embodiment in Embodiment 1 of the present application, and the technical effects brought by them are the same as those of the method embodiment of the present application. For specific content, refer to the description in the method embodiment of the present application described above, which will not be repeated here.

[0148] Embodiment 3

[0149] Embodiment 3 of the present application provides a non-transitory computer readable storage medium, wherein a program code of a radar weak target hybrid accumulation detection performance analysis method is stored in the computer readable storage medium, and the program code comprises instructions for executing the radar weak target hybrid accumulation detection performance analysis method of embodiment 1 or any possible implementation manner thereof.

[0150] The computer readable storage medium can be any available medium or a data storage device such as a server, data center, etc. integrated with one or more available medium sets that can be accessed by a computer. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)), etc.

[0151] Embodiment 4

[0152] Embodiment 4 of the present application provides an electronic device, comprising a memory and a processor.

[0153] The processor and the memory complete mutual communication through a bus; the memory stores program instructions that can be executed by the processor, and the processor calling the program instructions can execute the radar weak target hybrid accumulation detection performance analysis method of embodiment 1 or any possible implementation manner thereof.

[0154] Specifically, the processor can be implemented by hardware or software, when implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor can be a general-purpose processor, and the processor is implemented by reading software code stored in the memory, and the memory can be integrated in the processor or located outside the processor and independently exist.

[0155] In the embodiments described above, all or some of the modules / units can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or some of the modules / units can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded into and executed by a computer, all or some of the procedures or functions as described in the embodiments of the present application are generated. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable system. The computer instructions can be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through a wired (for example, coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (for example, infrared, wireless, microwave, etc.) manner.

[0156] It is obvious that those skilled in the art should understand that the modules or steps of the present application described above can be implemented by a general computing system, which can be concentrated on a single computing system or distributed on a network composed of multiple computing systems, and optionally, they can be implemented by program codes executable by a computing system, so that they can be stored in a storage system and executed by a computing system, and in some cases, the steps shown or described can be executed in different order, or they can be made into individual integrated circuit modules, or multiple modules or steps can be made into a single integrated circuit module. Thus, the present application is not limited to any particular combination of hardware and software.

[0157] Although the present application has been described in detail by the above general description and specific embodiments, some modifications or improvements can be made on the basis of the present application, which is obvious to those skilled in the art. Therefore, these modifications or improvements made on the basis of not deviating from the spirit of the present application are within the scope of the present application.

Claims

1. A radar weak target mixed accumulation detection performance analysis method, characterized in that: include: Dividing the radar echo into a plurality of subframes according to a moderate undulation Rayleigh model; each subframe includes a plurality of pulses; Obtaining an accumulated total pulse number by calculating the subframe and the pulse; performing coherent accumulation processing on the plurality of subframes to obtain coherent accumulation results of the plurality of subframes; performing non-coherent accumulation processing on the coherent accumulation results of the plurality of subframes to obtain mixed accumulation results of the plurality of subframes; Analyzing the distribution of the subframe mixed accumulation results under the target absence condition to obtain the false alarm probability; According to the false alarm probability, the detection threshold is obtained by reverse calculation; Analyzing the distribution of the subframe mixed accumulation results under the condition of target presence according to the detection threshold to obtain a closed expression for the detection probability; The performance of hybrid accumulation in detecting medium-fluctuation Rayleigh targets is analyzed by using a closed-form expression for the detection probability, and a positive correlation coefficient between the optimal subframe length and the total number of accumulated pulses is obtained; Calculating the optimal subframe length based on the positive correlation coefficient and the accumulated total number of pulses to achieve optimal detection performance; The expression of the false alarm probability is: The closed form expression of the detection probability is: Where I(·) is the incomplete gamma function; is the variance after coherent accumulation within the subframe; T is the detection threshold; N s is the number of subframes; z h is the sub-frame mixed accumulation result; σ 2 is the variance of the signal component and the noise component.

2. The radar weak target mixed accumulation detection performance analysis method according to claim 1 is characterized in that: The moderate fluctuation Rayleigh model expression is: Where, is the variance of the signal sampling s; ρ is the correlation coefficient, which indicates the actual output of the correlation degree of RCS between adjacent pulses; N is the number of pulses.

3. The radar weak target mixed accumulation detection performance analysis method according to claim 2 is characterized in that: In the process of performing coherent accumulation processing on a plurality of the subframes to obtain the coherent accumulation results of the plurality of the subframes, the expression of the subframe coherent accumulation results is: Where z k is the subframe; i is the i-th subframe; N b The number of pulses contained in each subframe.

4. The radar weak target mixed accumulation detection performance analysis method according to claim 3 is characterized in that: In the process of performing non-coherent accumulation processing on the coherent accumulation results of the plurality of sub-frames to obtain the mixed accumulation results of the plurality of sub-frames, the expression of the mixed accumulation results of the sub-frames is: Where, The result is accumulated for subframe coherence.

5. A radar faint target mixed accumulation detection performance analysis device, using a radar faint target mixed accumulation detection performance analysis method according to any one of claims 1 to 4, characterized in that: include: A radar echo division processing module, configured to divide the radar echo into a plurality of subframes according to a medium undulation Rayleigh model; each subframe includes a plurality of pulses; Obtaining an accumulated total pulse number by calculating the subframe and the pulse; A coherent accumulation processing module, configured to perform coherent accumulation processing on the plurality of subframes to obtain coherent accumulation results of the plurality of subframes; a non-coherent accumulation processing module, configured to perform non-coherent accumulation processing on the coherent accumulation results of the sub-frames to obtain mixed accumulation results of the sub-frames; a false alarm probability acquisition module, configured to analyze the distribution of the subframe mixed accumulation results under target absence conditions to obtain a false alarm probability; A detection probability closed expression acquisition module is used to reversely calculate and obtain a detection threshold based on the false alarm probability; Analyzing the distribution of the subframe mixed accumulation results under the condition of target presence according to the detection threshold to obtain a closed expression for the detection probability; An optimal subframe length acquisition module is used to analyze the performance of hybrid accumulation detection of medium-fluctuation Rayleigh targets through a closed expression of the detection probability, and obtain a positive correlation coefficient between the optimal subframe length and the total number of accumulated pulses; Calculating the optimal subframe length based on the positive correlation coefficient and the accumulated total number of pulses to achieve optimal detection performance; In the false alarm probability acquisition module, the expression of the false alarm probability is: In the detection probability closed expression acquisition module, the closed expression of the detection probability is: Where I(·) is the incomplete gamma function; is the variance after coherent accumulation within the subframe; T is the detection threshold; N s is the number of subframes; z h is the sub-frame mixed accumulation result; σ 2 is the variance of the signal component and the noise component.

6. The radar weak target mixed accumulation detection performance analysis device according to claim 5, characterized in that: In the coherent accumulation processing module, in the process of performing coherent accumulation processing on a plurality of the subframes to obtain a plurality of the subframe coherent accumulation results, the expression of the subframe coherent accumulation result is: Where z k is the subframe; i is the i-th subframe; N b The number of pulses contained in each subframe.

7. The radar weak target mixed accumulation detection performance analysis device according to claim 6, characterized in that: In the non-coherent accumulation processing module, in the process of performing non-coherent accumulation processing on the coherent accumulation results of the plurality of sub-frames to obtain the mixed accumulation results of the plurality of sub-frames, the expression of the mixed accumulation results of the sub-frames is: Where, The result is subframe coherent accumulation.

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