Radar weak target mixed accumulation detection performance analysis method and device

Abstract

The invention discloses a radar weak target mixed accumulation detection performance analysis method and device, and the method comprises the steps: dividing a radar echo into a plurality of subframes according to a medium fluctuation Rayleigh model; each sub-frame comprises a plurality of pulses, and calculating to obtain an accumulated total pulse number; performing coherent accumulation processing on the plurality of subframes to obtain a coherent accumulation result of the plurality of subframes; performing non-coherent accumulation processing on the coherent accumulation result of the plurality of subframes to obtain a mixed accumulation result of the plurality of subframes; respectively analyzing the distribution of the sub-frame mixed accumulation results under the conditions of target absence and target existence to obtain closed expressions of false alarm probability and detection probability; through analysis, the positive correlation coefficient of the optimal subframe length and the accumulated total pulse number is obtained, and the optimal subframe length is obtained through calculation according to the positive correlation coefficient, so that the optimal detection performance is achieved. The method can be widely applied to radar and sonar signal processing.

Description

Technical Field

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

[0002] Long-term integration algorithm is an effective method to improve the signal-to-noise ratio in radar weak target detection. Most of the existing long-term integration algorithms have an implicit assumption that the radar cross section (RCS) does not fluctuate during the coherent processing interval (CPI). However, in practical applications, amplitude and phase fluctuations of RCS during observation are almost inevitable. Especially in the case of long observation time, the target echo may be partially correlated, so a more general fluctuation model should be adopted, called the medium fluctuation target model. Then for the medium fluctuation model, there is a lack of a more general and accurate closed analytical formula to evaluate the hybrid accumulation detection performance and guide the hybrid accumulation subframe length selection problem.

[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, a closed expression of the mixed accumulation detection performance is obtained, and subframes are divided based on this to obtain the optimal detection performance.

[0005] In order 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 the medium fluctuation Rayleigh model, the radar echo is divided into a plurality of subframes; each of the subframes contains a plurality of pulses; and the total number of accumulated pulses is obtained by calculating according to 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, the detection threshold is obtained by reverse calculation; according to the detection threshold, the distribution of the subframe mixed accumulation result under the condition of the target existence is analyzed to obtain a closed expression of the detection probability;

[0011] The performance of mixed accumulation detection of medium-fluctuation Rayleigh targets is analyzed through the closed expression of the detection probability, and the positive correlation coefficient between the optimal subframe length and the total number of accumulated pulses is obtained; 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.

[0012] As a preferred solution of a radar weak target mixed accumulation detection performance analysis method, the medium fluctuation Rayleigh model expression is:

[0013]

[0014] In the formula, 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.

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

[0016]

[0017] In the formula, z k is a subframe; i is the ith subframe; N b The number of pulses contained in each subframe.

[0018] As a preferred solution of a radar weak target mixed accumulation detection performance analysis method, in the process of performing non-coherent accumulation processing on a plurality of sub-frame coherent accumulation results to obtain a plurality of sub-frame mixed accumulation results, the expression of the sub-frame mixed accumulation result is:

[0019]

[0020] Where N s is the number of subframes; z ci The results are accumulated for subframe coherence.

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

[0022]

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

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

[0025]

[0026] In the formula, 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] The radar echo division processing module is used to divide the radar echo into a number of subframes according to the medium fluctuation Rayleigh model; each of the subframes contains a number of pulses; and the total number of accumulated pulses is calculated based on the subframes and the pulses;

[0029] A coherent accumulation processing module, used for performing coherent accumulation processing on a plurality of said subframes to obtain a plurality of subframe coherent accumulation results;

[0030] A non-coherent accumulation processing module, used for performing 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 is used to analyze the distribution of the subframe mixed accumulation results under the target absence condition to obtain the false alarm probability;

[0032] A detection probability closed expression acquisition module is used to reversely calculate and obtain a detection threshold according to the false alarm probability; according to the detection threshold, the distribution of the subframe mixed accumulation result under the condition of the target existence is analyzed to obtain a closed expression of 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] In the formula, 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.

[0037] As a preferred solution of a radar weak target mixed accumulation detection performance analysis device, 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:

[0038]

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

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

[0041]

[0042] Where N s is the number of subframes; The results are accumulated for subframe coherence.

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

[0044]

[0045] Where, I(·) is the incomplete gamma function; is the variance after coherent accumulation within the subframe; T is the detection threshold.

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

[0047]

[0048] In the formula, z h is the sub-frame mixed accumulation result; σ 2 is the variance of the signal component and the noise component.

[0049] The present invention has the following advantages: according to the medium fluctuation Rayleigh model, the radar echo is divided into a plurality of subframes; each of the subframes contains a plurality of pulses; the total accumulated pulse number is calculated according to the subframes and the pulses; a plurality of subframes are subjected to coherent accumulation processing to obtain a plurality of subframe coherent accumulation results; a plurality of subframe coherent accumulation results are subjected to non-coherent accumulation processing to obtain a plurality of subframe mixed accumulation results; the distribution of the subframe mixed accumulation results under the condition of target absence is analyzed to obtain the false alarm probability; according to the false alarm probability, the detection threshold is obtained by reverse calculation; according to the detection threshold, the distribution of the subframe mixed accumulation results under the condition of target presence is analyzed to obtain the closed expression of the detection probability; the performance of mixed accumulation in detecting medium fluctuation Rayleigh targets is analyzed by the closed expression of the detection probability to obtain the positive correlation coefficient between the optimal subframe length and the total accumulated pulse number; according to the positive correlation coefficient and the total accumulated pulse number, the optimal subframe length is calculated to achieve the best detection performance. The method and device for analyzing the mixed accumulation detection performance of a radar weak target provided by the present invention are more general, and can analyze the fluctuation models of Swilling I type and Swilling II type as well as those between the two, and obtain the closed analytical expression of the mixed accumulation detection performance of a medium fluctuation Rayleigh target, and can numerically obtain the optimal subframe length to achieve the optimal detection performance. The present invention can be widely used in the processing of radar and sonar signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0051] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment of size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0052] Figure 1 A schematic flow chart of a radar weak target mixed accumulation detection performance analysis method provided in Example 1 of the present invention;

[0053] Figure 2A schematic diagram of a process flow for evaluating mixed accumulation detection performance of medium-fluctuation Rayleigh targets in a radar weak target mixed accumulation detection performance analysis method provided in Example 1 of the present invention;

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

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

[0056] Figure 5 Schematic diagram of the optimal subframe length analysis result in a radar weak target mixed accumulation detection performance analysis method provided in Example 1 of the present invention; wherein a is the optimal subframe length for different correlation coefficients; b is the optimal subframe length for different total accumulated pulse numbers;

[0057] Figure 6 This is a schematic diagram of the architecture of a radar weak target mixed accumulation detection performance analysis device provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0058] The following is a description of the implementation of the present invention by specific embodiments. People familiar with the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Example 1

[0060] See also Figure 1 and Figure 2 Embodiment 1 of the present invention provides a radar weak target mixed accumulation detection performance analysis method, comprising the following steps:

[0061] S1. According to the medium fluctuation Rayleigh model, the radar echo is divided into a plurality of subframes; each of the subframes contains a plurality of pulses; and the total number of accumulated pulses is calculated based on the subframes and the pulses;

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

[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, analyzing the distribution of the subframe mixed accumulation results under the target absence condition to obtain a false alarm probability;

[0065] S5. According to the false alarm probability, reverse calculation is performed to obtain a detection threshold; according to the detection threshold, the distribution of the subframe mixed accumulation result under the condition that the target exists is analyzed to obtain a closed expression of 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, and obtain the positive correlation coefficient between the optimal subframe length and the total number of accumulated pulses; calculate and obtain 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, according to the medium fluctuation Rayleigh model, the radar echo is divided into a number of subframes; each of the subframes contains a number of pulses; the total number of accumulated pulses is calculated based on the subframes and the pulses;

[0068] Specifically, assuming the radar echo Satisfy the medium fluctuation Rayleigh model. According to the medium fluctuation 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 medium-fluctuation 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 sample, 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, with variance 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 a 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] In the formula, z k is a subframe; i is the ith subframe; N b The number of pulses contained in each subframe.

[0083] In this embodiment, in step S3, a non-coherent accumulation process is performed on the coherent accumulation results of the plurality of sub-frames to obtain a plurality of mixed accumulation results of the 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 results are accumulated for subframe coherence.

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

[0089] Specifically, the subframe mixed accumulation result z h The distribution under the condition of target absence H0 is analyzed to 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 the modulus value, z h |H0 is subject to 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] 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, according to the false alarm probability, the detection threshold is obtained by reverse calculation; according to the detection threshold, the distribution of the subframe mixed accumulation result under the condition of the target existence is analyzed to obtain a closed expression of the detection probability;

[0102] Specifically, according to the false alarm probability P obtained by S4 FA , inversely deduce the detection threshold T, and then analyze the condition that the target exists under H1. h Distribution of

[0103] Under the H1 condition, the initial echo z contains both signal and noise. The noise term is independent of the signal term, so they can be considered separately. After coherent integration 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 integration 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. Substituting C into the above formula, we have:

[0106]

[0107] Combining the signal component and the noise component, z ci |H1 follows a zero-mean complex Gaussian distribution with a variance of In order to get P D The analytical expression of z is obtained by using an approximate method, assuming that the coherent accumulation results of different subframes are completely decorrelated. Therefore, after taking the square sum of the modulus value, z h |H1 is subject to the parameter 2N s and σ 2 / 2. Then z h |The probability density function of 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, for z h The probability density function of H1 is integrated from the threshold T to positive infinity to obtain the detection P D The probability of , that is:

[0113]

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

[0115]

[0116] When ρ = 0, it can be degenerated into the Sweelin II type detection probability:

[0117]

[0118] P D Monte Carlo simulation verification was performed, with the total number of accumulated pulses set to 4096, the correlation coefficient set to 0.99, and the false alarm probability set to 10. -8 , change the input signal-to-noise ratio 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 size 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 of C are generated. Then the noise sequence and the signal sequence are summed to obtain the pulse sequence z. Next, different subframe lengths are used for mixed accumulation to obtain the result z h . h By comparing with the threshold, it can be determined whether the target is detected. This process is repeated 1000 times to obtain the statistical results of the detection probability. Similarly, the input signal-to-noise ratio is fixed to -18dB, and the detection performance curves under different false alarm probabilities are generated. Figure 4 As shown, the solid line is the result obtained by the above formula, and the marked line is the result obtained by Monte Carlo simulation. The agreement between the two proves the correctness of the theoretical derivation.

[0119] In this embodiment, in step S6, the performance of mixed accumulation detection of medium-fluctuation Rayleigh targets is analyzed 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; 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.

[0120] Specifically, according to the detection probability P obtained in step S5 D From the formula, we can see that the detection probability is affected by the subframe length, correlation coefficient, total accumulated pulse number, false alarm probability and input signal-to-noise ratio. In order to maximize the detection probability, it is very important to choose the appropriate subframe length. Figure 4 It can be seen that although there are intersections between the curves, no matter how the input signal-to-noise ratio and false alarm probability change, the optimal subframe length remains unchanged. Therefore, although the input signal-to-noise ratio and false alarm probability have an impact on the selection of subframe length, it is not significant and can be ignored. Then analyze the correlation coefficient and the impact of the total number of accumulated pulses on the optimal subframe length. Set the total number of accumulated pulses to 4096 and the false alarm probability to 10-8 , the input signal-to-noise ratio is -16.4dB, and the optimal subframe length under different correlation coefficient values ​​is calculated. Similarly, the correlation coefficient is set to 0.99, and other parameters remain unchanged, and the optimal subframe length under different accumulated total pulse numbers is calculated. Figure 5 As shown, the optimal subframe length when the detection probability is maximized is positively correlated with the total number of accumulated pulses and the correlation coefficient. After the correlation coefficient of the total number of accumulated pulses and the echo is known, the optimal subframe length can be determined according to the present invention to achieve the best detection performance.

[0121] In summary, the present invention divides radar echoes into a number of subframes according to a medium fluctuation Rayleigh model; each of the subframes contains a number of pulses; the total accumulated pulse number is calculated according to the subframes and the pulses; a coherent accumulation process is performed on the subframes to obtain a number of subframe coherent accumulation results; a non-coherent accumulation process is performed on the coherent accumulation results of the subframes to obtain a number of subframe mixed accumulation results; the distribution of the subframe mixed accumulation results under the condition of target absence is analyzed to obtain the false alarm probability; according to the false alarm probability, the detection threshold is obtained by reverse calculation; according to the detection threshold, the distribution of the subframe mixed accumulation results under the condition of target presence is analyzed to obtain a closed expression of the detection probability; the performance of mixed accumulation in detecting medium fluctuation Rayleigh targets is analyzed through the closed expression of the detection probability to obtain the positive correlation coefficient between the optimal subframe length and the total accumulated pulse number; according to the positive correlation coefficient and the total accumulated pulse number, the optimal subframe length is calculated to achieve the best detection performance. The method and device for analyzing the mixed accumulation detection performance of a radar weak target provided by the present invention are more general, and can analyze the fluctuation models of Swilling I type and Swilling II type as well as those between the two, and obtain the closed analytical expression of the mixed accumulation detection performance of a medium fluctuation Rayleigh target, and can numerically obtain the optimal subframe length to achieve the optimal detection performance. The present invention can be widely used in the processing of radar and sonar signals.

[0122] It should be noted that the method of the embodiment of the present disclosure 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 the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete the described method.

[0123] It should be noted that the above describes some embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0124] Example 2

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

[0126] The radar echo division processing module 001 is used to divide the radar echo into a number of subframes according to the medium fluctuation Rayleigh model; each of the subframes contains a number of pulses; and the total number of accumulated pulses is calculated based on the subframes and the pulses;

[0127] A coherent accumulation processing module 002 is used to perform coherent accumulation processing on a plurality of said subframes to obtain a plurality of subframe coherent accumulation results;

[0128] A non-coherent accumulation processing module 003 is used to perform non-coherent accumulation processing on the coherent accumulation results of the sub-frames to obtain mixed accumulation results of the sub-frames;

[0129] The false alarm probability acquisition module 004 is used to analyze the distribution of the subframe mixed accumulation results under the target absence condition to obtain the false alarm probability;

[0130] The detection probability closed expression acquisition module 005 is used to reversely calculate and obtain the detection threshold according to the false alarm probability; according to the detection threshold, the distribution of the subframe mixed accumulation result under the condition of the target existence is analyzed to obtain the closed expression of the detection probability;

[0131] The optimal subframe length acquisition module 006 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.

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

[0133]

[0134] In the formula, 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.

[0135] In this embodiment, in the coherent accumulation processing module 002, 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:

[0136]

[0137] In the formula, z k is a subframe; i is the ith subframe; N b The number of pulses contained in each subframe.

[0138] In this embodiment, in the non-coherent accumulation processing module 003, in the process of performing non-coherent accumulation processing on a number of the sub-frame coherent accumulation results to obtain a number of the sub-frame mixed accumulation results, the expression of the sub-frame mixed accumulation result is:

[0139]

[0140] Where N s is the number of subframes; z ci The results are accumulated for subframe coherence.

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

[0142]

[0143] Where, I(·) is the incomplete gamma function; is the variance after coherent accumulation within the subframe; T is the detection threshold.

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

[0145]

[0146] In the formula, z h is the sub-frame mixed accumulation result; σ 2 is the variance of the signal component and the noise component.

[0147] It should be noted that the information interaction, execution process and other contents between the modules of the above-mentioned system are based on the same concept as the method embodiment in Example 1 of the present application, and the technical effects they bring are the same as those of the method embodiment of the present application. For specific contents, please refer to the description in the method embodiment shown above in the present application, and will not be repeated here.

[0148] Example 3

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

[0150] The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0151] Example 4

[0152] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0153] The processor and the memory communicate with each other via a bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute a radar weak target mixed accumulation detection performance analysis method of embodiment 1 or any possible implementation thereof.

[0154] Specifically, the processor can be implemented by hardware or by 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 implemented by reading software codes stored in a memory. The memory can be integrated in the processor or can be located outside the processor and exist independently.

[0155] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part 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 and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable systems. The computer instructions can be stored in a computer-readable storage medium, or transmitted from a computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center.

[0156] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing system, they 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 a program code executable by a computing system, so that they can be stored in a storage system and executed by the computing system, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0157] Although the present invention has been described in detail above by general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made to the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. A radar weak target mixed accumulation detection performance analysis method, characterized in that: include: According to the medium fluctuation Rayleigh model, the radar echo is divided into a plurality of subframes; each of the subframes includes a plurality of pulses; Obtaining the total accumulated pulse number according to the subframe and the pulse calculation; 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, a detection threshold is obtained by reverse calculation; According to the detection threshold, analyzing the distribution of the subframe mixed accumulation result under the condition of target existence, and obtaining a closed expression of the detection probability; The performance of mixed accumulation in detecting medium-fluctuation Rayleigh targets is analyzed by using the closed expression of the detection probability, and the positive correlation coefficient between the optimal subframe length and the total number of accumulated pulses is obtained; The optimal subframe length is calculated based on the positive correlation coefficient and the accumulated total pulse number to achieve the best detection performance.

2. A radar weak target mixed accumulation detection performance analysis method according to claim 1, characterized in that: The medium fluctuation Rayleigh model expression is: In the formula, 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. A radar weak target mixed accumulation detection performance analysis method according to claim 2, characterized in that: In the process of performing coherent accumulation processing on a plurality of the subframes to obtain coherent accumulation results of the plurality of the subframes, the expression of the subframe coherent accumulation results is: In the formula, z k is a subframe; i is the ith 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 a plurality of sub-frame coherent accumulation results to obtain a plurality of sub-frame mixed accumulation results, the expression of the sub-frame mixed accumulation result is: Where N s is the number of subframes; The results are accumulated for subframe coherence.

5. A radar weak target mixed accumulation detection performance analysis method according to claim 4, characterized in that: The expression of the false alarm probability is: Where, I(·) is the incomplete gamma function; is the variance after coherent accumulation within the subframe; T is the detection threshold.

6. A radar weak target mixed accumulation detection performance analysis method according to claim 5, characterized in that: The closed form expression of the detection probability is: In the formula, z h is the sub-frame mixed accumulation result; σ 2 is the variance of the signal component and the noise component.

7. A radar weak target mixed accumulation detection performance analysis device, using a radar weak target mixed accumulation detection performance analysis method according to any one of claims 1 to 6, characterized in that: include: A radar echo division processing module, used for dividing the radar echo into a number of subframes according to a medium fluctuation Rayleigh model; each of the subframes contains a number of pulses; Obtaining the total accumulated pulse number according to the subframe and the pulse calculation; A coherent accumulation processing module, used for performing coherent accumulation processing on a plurality of said subframes to obtain a plurality of subframe coherent accumulation results; A non-coherent accumulation processing module, used for performing 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 is used to analyze the distribution of the subframe mixed accumulation results under the target absence condition to obtain the 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; According to the detection threshold, analyzing the distribution of the subframe mixed accumulation result under the condition of target existence, and obtaining a closed expression of the detection probability; An 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 a positive correlation coefficient between the optimal subframe length and the total number of accumulated pulses; The optimal subframe length is calculated based on the positive correlation coefficient and the accumulated total pulse number to achieve the best detection performance.

8. The radar weak target mixed accumulation detection performance analysis device according to claim 7, 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: In the formula, z k is a subframe; i is the ith subframe; N b The number of pulses contained in each subframe.

9. The radar weak target mixed accumulation detection performance analysis device according to claim 8, characterized in that: In the non-coherent accumulation processing module, in the process of performing non-coherent accumulation processing on a plurality of sub-frame coherent accumulation results to obtain a plurality of sub-frame mixed accumulation results, the expression of the sub-frame mixed accumulation result is: Where N s is the number of subframes; The results are accumulated for subframe coherence.

10. The radar weak target mixed accumulation detection performance analysis device according to claim 9 is characterized in that: In the false alarm probability acquisition module, the expression of the false alarm probability is: Where I(·) is the incomplete gamma function; is the variance after coherent accumulation within the subframe; T is the detection threshold.

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