Repeated forwarding interference waveform generation method, device, electronic device and storage medium

Abstract

The present invention provides a method, device, electronic device and storage medium for generating a repeated forwarding interference waveform, the method comprising: determining a forwarding configuration of non-uniform intermittent sampling repeated forwarding interference; initializing parameters of a genetic algorithm; generating an initial population, using a fitness function to calculate the optimal fitness and the first optimal individual of the initial population; using a genetic algorithm to perform iterative generation according to parameter configuration on the individuals in the initial population to obtain the next generation population, wherein the iterative generation includes selection, crossover and mutation processing; calculating the optimal fitness of the next generation population, determining the second optimal individual according to the optimal fitness of the next generation population; calculating the average fitness of the population, terminating the iteration according to the average fitness and the end condition, obtaining the third optimal individual, and determining the interference waveform generation result according to the third optimal individual. The beneficial effects of the present invention are: improving the interference efficiency and generation efficiency of the interference waveform.

Description

Technical Field

[0001] The present invention relates to the field of radar jamming technology, and in particular to a method, device, electronic device and storage medium for generating a repeated forwarding jamming waveform. Background Art

[0002] In the early days of radar development, fixed carrier frequency pulses were used, and their distance resolution was inversely proportional to the transmitted pulse width. In order to increase the effective range, it is necessary to increase the transmitted pulse width, which will inevitably lead to a decrease in distance resolution. With the development of radar technology, pulse compression radar came into being. It increases the radar signal-to-interference ratio and effective range by transmitting a large time-width signal to increase the transmission power, while compressing the narrow pulse to improve the detection accuracy. Among them, Linear Frequency Modulated (LFM) radar is the most widely used and mature due to its advantages of easy generation and processing. It uses coherence to deal with interference signals that do not match the radar waveform, and its anti-interference ability has been greatly enhanced.

[0003] The prior art is a method for generating non-uniform intermittent sampling repeated forwarding interference waveforms based on reinforcement learning. This method first encodes the non-uniform intermittent sampling repeated forwarding interference waveform, optimizes the encoding design using DQN (Deep Q-Network), and uses the ratio of the standard deviation of the interference waveform amplitude after pulse compression to the mean as a reward function to evaluate the interference effect. However, this method cannot directly characterize the radar interference effect, the interference effect of the optimized interference waveform is poor, and the DQN network training requires a large amount of data and calculations, which takes up a lot of computing resources and consumes more time. Summary of the invention

[0004] The main purpose of the embodiments of the present invention is to provide a method, device, electronic device and storage medium for generating a repeated forwarding interference waveform, which improves the generation efficiency of the interference waveform and improves the interference effect of the interference waveform.

[0005] An aspect of the present invention provides a method for generating a repeated forwarding interference waveform, comprising:

[0006] Determine a forwarding configuration of non-uniform intermittent sampling repeated forwarding interference according to an interference waveform generation request, wherein the forwarding configuration includes a process code and a coding sequence time width;

[0007] Initialize the parameters of the genetic algorithm and determine the parameter configuration of the genetic algorithm;

[0008] Generate an initial population according to the forwarding configuration, calculate the optimal fitness of the initial population using a fitness function, and determine a first optimal individual according to the optimal fitness of the initial population;

[0009] Using a genetic algorithm to perform iterative generation on individuals in the initial population according to the parameter configuration to obtain the next generation population, wherein the iterative generation includes selection, crossover and mutation processing;

[0010] After each iteration generates the next generation population, the optimal fitness of the next generation population is calculated, and the second best individual is determined based on the optimal fitness of the next generation population;

[0011] In each iteration, the average fitness of the population is calculated, and the iteration is terminated according to the average fitness and the end condition to obtain the third optimal individual, and the interference waveform generation result is determined according to the third optimal individual.

[0012] According to the repeated forwarding interference waveform generation method, determining the forwarding configuration of non-uniform intermittent sampling repeated forwarding interference according to the interference waveform generation request includes:

[0013] The process coding includes a sampling operation "0" and a forwarding operation "1", and the coding sequence time width is a minimum sampling time unit;

[0014] The non-uniform intermittent sampling repeated forwarding interference for:

[0015]

[0016] in, is the impulse function, It is The code element corresponds to the short pulse transmitted, and for:

[0017]

[0018] Indicates that the current Sub-sampling operation,

[0019]

[0020] represents a rectangular pulse signal,

[0021]

[0022] in, is the length of the non-uniform intermittent sampling repeated forwarding interference coding sequence, For the intercepted radar signal, is the minimum sampling time unit, is the number of "0"s in the string of consecutive "0"s before the code element when the code element is "1", When the code element is "1", this code element is located in the current string of "1" On the seat, For the The code element on the bit, where , The value range is 0 or 1, and satisfy ,in is the pulse width of the intercepted radar signal, is the rectangular window function, and t is the time.

[0023] According to the method for generating a repeated forwarding interference waveform, the parameter configuration includes chromosome and population configuration, wherein the chromosome is a non-uniform intermittent sampling repeated forwarding interference coding sequence; wherein the population configuration includes the number of individuals , Iterations , Algebraic Counter , crossover probability and mutation probability ,in .

[0024] According to the repeated forwarding interference waveform generation method, generating an initial population according to the forwarding configuration includes:

[0025] The number of individuals is randomly generated according to the forwarding configuration The chromosomes of binary code constitute the initial population, and each chromosome has a length of , the first bit of each non-uniform intermittent sampling repeated forwarding interference coding sequence is "0", that is, the sampling operation is performed first, and then the forwarding operation is performed.

[0026] According to the repeated forwarding interference waveform generation method, the optimal fitness of the initial population is calculated using a fitness function, including:

[0027] The fitness function for

[0028]

[0029] in is the number of false targets generated by the jamming signal, is the interference-to-signal ratio, where the interference-to-signal ratio is the ratio of the interference signal to the real signal power. is the weight of the number of false targets, is the weight of the interference-to-signal ratio, and It is used to balance the number of false targets and the level of interference-to-signal ratio, and is adjusted according to the interference intensity.

[0030] The individuals in the initial population are iteratively generated using a genetic algorithm according to the parameter configuration to obtain the next generation population, wherein the iterative generation includes selection, crossover and mutation processing, including:

[0031] The selection roulette operator performs selection on individuals in the initial population, including calculating the fitness of all individuals in the current generation according to the fitness function ,in , the selection probability of each individual is calculated by the fitness value for

[0032]

[0033] is the minimum fitness of all individuals in the current generation;

[0034] The crossover operation is based on the probability judgment Whether to perform crossover. If so, randomly select a point on the chromosome to perform single-point crossover on the two chromosomes.

[0035] The mutation operation is based on probability Determine whether to proceed. If mutation is to be performed, randomly select a point on the chromosome for mutation, wherein the mutation is to invert the code element at the corresponding position of the non-uniform intermittent sampling repeated forwarding interference coding sequence.

[0036] According to the method for generating a repeated forwarding interference waveform, the method further includes:

[0037] Get the optimal fitness of the generated population at each iteration and the optimal fitness of the newly generated population ,like , then the best individual in the generated population is replaced by the best individual in the new population, otherwise, the best individual in the generated population is retained.

[0038] Another aspect of an embodiment of the present invention provides a repeated forwarding interference waveform generating device, including:

[0039] The first module is used to determine a forwarding configuration of non-uniform intermittent sampling repeated forwarding interference according to an interference waveform generation request, wherein the forwarding configuration includes a process code and a coding sequence time width;

[0040] The second module is used to initialize the parameters of the genetic algorithm and determine the parameter configuration of the genetic algorithm;

[0041] A third module is used to generate an initial population consisting of binary code sequences according to the forwarding configuration, calculate the optimal fitness of the initial population using a fitness function, and determine a first optimal individual according to the optimal fitness of the initial population;

[0042] The fourth module is used to perform iterative generation on individuals in the initial population using a genetic algorithm according to the parameter configuration to obtain a next generation population, wherein the iterative generation includes selection, crossover and mutation processing;

[0043] The fifth module is used to calculate the optimal fitness of the next generation population after each iteration to determine the second best individual according to the optimal fitness of the next generation population;

[0044] The sixth module is used to calculate the average fitness of the population in each iteration, end the iteration according to the average fitness and the end condition, obtain the third optimal individual, and determine the interference waveform generation result according to the third optimal individual.

[0045] Another aspect of an embodiment of the present invention provides an electronic device, including a processor and a memory;

[0046] The memory is used to store programs;

[0047] The processor executes the program to implement the method described above.

[0048] The embodiment of the present invention also discloses a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device can read the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method described above.

[0049] The beneficial effects of the present invention are as follows: by encoding the non-uniform intermittent sampling repeated forwarding interference, the interference waveform optimization design problem is transformed into the problem of solving the optimal coding sequence, which is convenient for optimization using the optimization algorithm. The number of false targets generated by the interference waveform and the interference-to-signal ratio are used as the fitness function, and the weights of the two can be freely adjusted according to the needs, which can better characterize the interference effect of the interference waveform on the radar; through the powerful global search capability of the genetic algorithm, parallel calculation can be performed, which can effectively avoid the problem of local optimal solution, and can meet the needs of real-time processing, thereby improving the interference efficiency and generation efficiency of the interference waveform. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0051] Figure 1 It is a schematic diagram of a linear frequency modulation pulse compression radar countermeasure scenario according to an embodiment of the present invention.

[0052] Figure 2This is a step diagram of a method for generating a non-uniform intermittent sampling repeated forwarding interference waveform based on a genetic algorithm in an embodiment of the present invention.

[0053] Figure 3 Schematic diagram of a non-uniform intermittent sampling repeated forwarding interference coding method according to an embodiment of the present invention, wherein (a) represents a radar signal Time-varying graph, (b) shows the coding sequence diagram, and (c) shows the sampling signal Time-varying graph, (d) represents the forwarding signal Graph of changes over time.

[0054] Figure 4 It is a flow chart of the CA-CFAR detection algorithm of an embodiment of the present invention.

[0055] Figure 5 This is a graph showing how the average fitness and optimal fitness of individuals in each generation change with the number of iterations during the iteration of the genetic algorithm of an embodiment of the present invention.

[0056] Figure 6 It is a time domain waveform comparison diagram of the radar echo signal, non-uniform intermittent sampling repeated forwarding interference, and intermittent sampling forwarding interference according to an embodiment of the present invention, wherein (a) represents the waveform diagram of the radar echo signal changing in the time domain, (b) represents the waveform diagram of the non-uniform intermittent sampling repeated forwarding interference signal changing in the time domain, and (c) represents the waveform diagram of the intermittent sampling forwarding interference signal changing in timing.

[0057] Figure 7 It is a comparison diagram of radar echo signal, non-uniform intermittent sampling repeated forwarding interference, and intermittent sampling forwarding interference pulse compression in an embodiment of the present invention.

[0058] Figure 8 1 is a diagram of CFAR detection results of non-uniform intermittent sampling repeated forwarding interference and intermittent sampling forwarding interference according to an embodiment of the present invention, (a) shows a CFAR detection result change diagram of non-uniform intermittent sampling repeated forwarding interference, and (b) shows a CFAR detection result change diagram of intermittent sampling forwarding interference.

[0059] Fig. 9 It is a schematic diagram of a non-uniform intermittent sampling repeated forwarding interference waveform generation device based on a genetic algorithm in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. In the subsequent description, the use of suffixes such as "module", "component" or "unit" used to represent elements is only for the purpose of facilitating the description of the present invention, and has no specific meaning in itself. Therefore, "module", "component" or "unit" can be used in a mixed manner. "First", "second" and the like are only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features or implicitly indicating the order of the indicated technical features. In this subsequent description, the continuous numbering of the method steps is for the convenience of review and understanding. In combination with the overall technical solution of the present invention and the logical relationship between the various steps, adjusting the implementation order between the steps will not affect the technical effect achieved by the technical solution of the present invention. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0061] refer to Figure 1 , Figure 1 The figure is a schematic diagram of a linear frequency modulation pulse compression radar countermeasure scenario according to an embodiment of the present invention. The linear frequency modulation pulse compression radar transmits an LFM signal, generates an echo after detecting a target, and the jammer on the target intercepts the radar signal and processes it to generate a jammer signal, and then transmits the jammer signal to the radar. The radar receiver receives the echo signal and the jammer signal, performs pulse compression on the signal, and then performs CFAR detection.

[0062] The linear frequency modulation signal is:

[0063]

[0064] in, is the signal amplitude, is the carrier center frequency, B is the signal bandwidth, is the pulse width, is the frequency modulation slope. The essence of pulse compression is to make the LFM signal pass through a matched filter and use the linear relationship between frequency and time delay to achieve pulse compression of the signal. According to the matched filter theory, the unit impulse response of the matched filter is .

[0065] in, is a constant, is the additional delay that can be physically realized by the matching filter, and the pulse compression signal is .

[0066] Figure 2This is a step diagram of a method for generating a non-uniform intermittent sampling repeated forwarding interference waveform based on a genetic algorithm according to an embodiment of the present invention, which includes but is not limited to steps S100 to S600:

[0067] S100, determining a forwarding configuration of non-uniform intermittent sampling repeated forwarding interference according to an interference waveform generation request, wherein the forwarding configuration includes a process code and a coding sequence time width.

[0068] In some embodiments, the sampling and forwarding process of non-uniform intermittent sampling and repeated forwarding interference is coded and defined, "0" represents a sampling operation, "1" represents a forwarding operation, and a fixed minimum sampling time unit is used as the duration of the coding sequence.

[0069] refer to Figure 3 The schematic diagram of the non-uniform intermittent sampling repeated forwarding interference coding method is shown. Figure 3 (a) represents the radar signal Time-varying graph; (b) shows the schematic diagram of the coding sequence, where "0" in (b) represents the sampling operation and "1" represents the forwarding operation; (c) shows the sampling signal Time-varying graph; (d) represents the forwarding signal Graph of changes over time.

[0070] Non-uniform intermittent sampling repeated forwarding interference expression for,

[0071]

[0072] It is The code element corresponds to the short pulse transmitted. is the impulse function,

[0073]

[0074] Indicates that the current Sub-sampling operation,

[0075]

[0076] represents a rectangular pulse signal,

[0077]

[0078] is the length of the non-uniform intermittent sampling repeated forwarding interference coding sequence, For the intercepted radar signal, is the minimum sampling time unit, is the number of "0"s in the string of consecutive "0"s before the codeword when the codeword is "1", When the code element is "1", this code element is located in the current string of "1" On the seat, For the Codewords on bits , The value range is 0 or 1. is the rectangular window function, and t is the time.

[0079] Non-uniform intermittent sampling repeated forwarding interference coding sequence length The pulse width of the intercepted radar signal and minimum sampling time unit In the embodiment of the present invention, the interference coding sequence length for

[0080] .

[0081] S200, initializing parameters of the genetic algorithm and determining parameter configuration of the genetic algorithm.

[0082] In some embodiments, the number of individuals in a population is set , number of iterations , algebraic counter , crossover probability , mutation probability , the chromosome is a non-uniform intermittent sampling repeated forwarding interference coding sequence.

[0083] S300, generating an initial population according to the forwarding configuration, calculating the optimal fitness of the initial population using a fitness function, and determining a first optimal individual according to the optimal fitness of the initial population.

[0084] In some embodiments, a randomly generated The coding sequences form the initial population of binary codes, and the length of each coding sequence is ,In particular, the first bit of each coding sequence is “0”, i.e., it is sampled first and then forwarded.

[0085] S400, using a genetic algorithm to perform iterative generation on individuals in the initial population according to parameter configuration to obtain a next generation population, wherein the iterative generation includes selection, crossover and mutation processing.

[0086] In some embodiments, the roulette operator is used to perform the selection, firstly calculating the fitness of all individuals in the current generation according to the fitness function , the selection probability of each individual is calculated by the fitness value,

[0087]

[0088] is the minimum fitness of all individuals in the current generation.

[0089] The selection operator is a key step in determining which individuals can enter the next generation of the population. It simulates the principle of "survival of the fittest" in nature and probabilistically selects individuals for reproduction by evaluating their fitness. The selection process aims to retain individuals with strong adaptability and promote the overall evolution of the population towards a better solution. Determine whether to perform crossover. If crossover is performed, randomly select a point on the chromosome to perform single-point crossover on the two chromosomes. The value range is (0.4, 0.6). The crossover operation is the core of the genetic algorithm, which simulates the gene recombination in the biological genetic process and generates new offspring by exchanging some genes of the parent individuals. The appropriate crossover probability can effectively combine the advantages of different individuals and promote the evolution of the population.

[0090] Among them, the mutation operation is based on probability Determine whether to proceed. If mutation is to be performed, a point on the chromosome is randomly selected for mutation. Specifically, the code element at the corresponding position of the coding sequence is inverted, and the value range of the mutation operation is (0.2, 0.35). Mutation is a key mechanism for introducing new genetic materials and ensures the exploration ability of the algorithm. A higher mutation probability can increase the diversity of the population and help to jump out of the local optimum, but too high a mutation probability may cause the search process to be too random and reduce the efficiency of the algorithm. If the mutation probability is too low, it may cause the population to evolve slowly and easily fall into the local optimal solution.

[0091] In some embodiments, it is assumed that the target is a target that is misjudged as a real target when detecting radar received signals using the CA-CFAR algorithm. The more false targets there are, the stronger the deceptive interference effect on the radar, and the larger the interference-to-signal ratio, the stronger the suppressive interference effect on the radar.

[0092] For example, reference Figure 4 The CA-CFAR detection algorithm flow chart shown in FIG. 1 is a flow chart showing a CA-CFAR detection algorithm. The CFAR detector generally includes a detection unit. and The protection units are evenly distributed on both sides of the detection unit and are mainly used in single-target situations to prevent target energy from leaking to the reference unit and affecting the detection effect. Assume the reference threshold level is .

[0093]

[0094] in, For an estimate of the total clutter power level, is the threshold factor, when , it is believed that there is a goal; otherwise, it is believed that there is no goal.

[0095] In the CA-CFAR algorithm,

[0096]

[0097] in, is the expected false alarm probability.

[0098] The sum of the reference cells is averaged, and its expression is,

[0099]

[0100] The signal-to-difference expression is:

[0101]

[0102] in, is the interference signal power, is the real signal power. Signal power Using the 2-norm calculation,

[0103]

[0104] in, is the 2-norm of the signal, is the signal length.

[0105] S500, after each iteration to generate the next generation population, the optimal fitness of the next generation population is calculated, and the second optimal individual is determined according to the optimal fitness of the next generation population.

[0106] S600, in each iteration, the average fitness of the population is calculated, and the iteration is ended according to the average fitness and the end condition to obtain the third optimal individual, and the interference waveform generation result is determined according to the third optimal individual.

[0107] It can be understood that the end condition is the number of iterations shown in the above embodiment. .

[0108] In some embodiments, reference Figure 5 The average fitness and optimal fitness comparison diagram shown in the figure, where the average fitness is used to indicate whether the iteration is stable. Or when the average fitness changes little and converges, the iteration can be ended to determine the interference waveform generation result.

[0109] Specifically, calculate the average fitness of the new population and optimal fitness , the fitness of the previous optimal individual is ,like , the best individual in the new population replaces the previous best individual, otherwise, the best individual remains unchanged.

[0110] In some embodiments, each time the algebraic counter is repeated ,until Reached the number of iterations , end the iteration and get the optimal individual.

[0111] The simulated radar signal parameters in the embodiment of the present invention are shown in Table 1.

[0112] Table 1 Simulated radar signal parameters

[0113]

[0114] Non-uniform intermittent sampling repeated forwarding interference minimum sampling time unit .

[0115] The expected false alarm probability of the CA-CFAR detection algorithm is 0.01, and the number of reference units is 16.

[0116] The genetic algorithm parameters in the embodiment of the present invention are shown in Table 2.

[0117] Table 2 Genetic algorithm parameters

[0118]

[0119] refer to Figure 5 , Figure 5 The average fitness and optimal fitness of each generation of individuals change with the number of iterations when the genetic algorithm is iterated. Figure 5 The optimal fitness converges to 5.7778. When it iterates to 1000 generations, the optimal fitness has tended to converge.

[0120] refer to Figure 6 The radar echo signal, non-uniform intermittent sampling repeated forwarding interference signal, and intermittent sampling forwarding interference signal time domain waveform comparison are shown. Specifically, Figure 6 (a) shows the waveform of the radar echo signal changing in the time domain, (b) shows the waveform of the non-uniform intermittent sampling and repeated forwarding interference signal changing in the time domain, and (c) shows the waveform of the intermittent sampling and repeated forwarding interference signal changing in the timing sequence.

[0121] Figure 7The intermittent sampling and forwarding interference signal waveform is obtained by intermittent sampling and forwarding the radar echo signal, the non-uniform intermittent sampling and repeated forwarding interference signal, and the intermittent sampling and forwarding interference waveform, that is, Figure 7 It is the result of compressing the three signal time domain waveform pulses, combined with Figure 6 and Figure 7 It can be seen that the number of amplitude peaks generated by the non-uniform intermittent sampling and repeated forwarding interference signal on the range axis is greater than that of the intermittent sampling and forwarding interference signal, and the number of false targets formed is greater, which causes greater interference to the radar in distinguishing real targets.

[0122] The radar is interfered with by non-uniform intermittent sampling repeated forwarding interference and intermittent sampling forwarding interference respectively, and the CFAR detection results of non-uniform intermittent sampling repeated forwarding interference and intermittent sampling forwarding interference are obtained as follows Figure 8 As shown, Figure 8 (a) shows the change diagram of CFAR detection results of non-uniform intermittent sampling and repeated forwarding interference, (b) shows the change diagram of CFAR detection results of intermittent sampling and forwarding interference, Figure 8 Each distance unit is 15m (meters), that is, each scale is 50*15=750m. Non-uniform intermittent sampling repeated forwarding interference produces a total of 12 false targets, while intermittent sampling forwarding interference produces a total of 9 false targets. Therefore, the deceptive interference effect of non-uniform intermittent sampling repeated forwarding interference is stronger. The interference-to-signal ratio of non-uniform intermittent sampling repeated forwarding interference is 0.6945, while the interference-to-signal ratio of intermittent sampling forwarding interference is 0.6925. Therefore, the suppression interference effect of non-uniform intermittent sampling repeated forwarding interference is also slightly stronger.

[0123] Fig. 9 1 is a diagram of a device for generating and analyzing repeated forwarding interference waveforms according to an embodiment of the present invention. The device includes a first module 910 , a second module 920 , a third module 930 , a fourth module 940 , a fifth module 950 and a sixth module 960 .

[0124] Among them, the first module is used to determine the forwarding configuration of non-uniform intermittent sampling repeated forwarding interference according to the interference waveform generation request, wherein the forwarding configuration includes the process code and the coding sequence time width; the second module is used to initialize the parameters of the genetic algorithm and determine the parameter configuration of the genetic algorithm; the third module is used to generate an initial population composed of binary coding sequences according to the forwarding configuration, calculate the optimal fitness of the initial population using the fitness function, and determine the first optimal individual according to the optimal fitness of the initial population; the fourth module is used to perform iterative generation on the individuals in the initial population according to the parameter configuration using the genetic algorithm to obtain the next generation population, wherein the iterative generation includes selection, crossover and mutation processing; the fifth module is used to calculate the optimal fitness of the next generation population after each iteration to generate the next generation population, and determine the second optimal individual according to the optimal fitness of the next generation population; the sixth module is used to calculate the average fitness of the population in each iteration, end the iteration according to the average fitness and the end condition, obtain the third optimal individual, and determine the interference waveform generation result according to the third optimal individual.

[0125] Exemplarily, with the cooperation of the first module, the second module, the third module, the fourth module, the fifth module and the sixth module in the device, the embodiment device can implement any of the aforementioned repeated forwarding interference waveform generation methods, that is, according to the interference waveform generation request, determine the forwarding configuration of the non-uniform intermittent sampling repeated forwarding interference, wherein the forwarding configuration includes the process coding and the coding sequence time width; initialize the parameters of the genetic algorithm and determine the parameter configuration of the genetic algorithm; according to the forwarding configuration, generate an initial population, use the fitness function to calculate the optimal fitness of the initial population, and determine the first optimal individual according to the optimal fitness of the initial population; use the genetic algorithm to perform iterative generation on the individuals in the initial population according to the parameter configuration to obtain the next generation population, wherein the iterative generation includes selection, crossover and mutation processing; after each iteration of generating the next generation population, calculate the optimal fitness of the next generation population, and determine the second optimal individual according to the optimal fitness of the next generation population; in each iteration, calculate the average fitness of the population, end the iteration according to the average fitness and the end condition, obtain the third optimal individual, and determine the interference waveform generation result according to the third optimal individual. The beneficial effects of the present invention are as follows: by encoding the non-uniform intermittent sampling repeated forwarding interference, the interference waveform optimization design problem is transformed into the problem of solving the optimal coding sequence, which is convenient for optimization using the optimization algorithm. The number of false targets generated by the interference waveform and the interference-to-signal ratio are used as the fitness function, and the weights of the two can be freely adjusted according to the needs, which can better characterize the interference effect of the interference waveform on the radar; through the powerful global search capability of the genetic algorithm, parallel calculation can be performed, which can effectively avoid the problem of local optimal solution, and can meet the needs of real-time processing, thereby improving the interference efficiency and generation efficiency of the interference waveform.

[0126] An embodiment of the present invention further provides an electronic device, the electronic device comprising a processor and a memory;

[0127] The memory stores a program;

[0128] The processor executes a program to execute the aforementioned method for generating a repeated forwarding interference waveform; the electronic device has the function of carrying and running the software system for generating a repeated forwarding interference waveform provided in an embodiment of the present invention, for example, a personal computer, a minicomputer, a main frame, a workstation, a network or a distributed computing environment, a separate or integrated computer platform, or communicating with a charged particle tool or other imaging device, etc.

[0129] An embodiment of the present invention further provides a computer-readable storage medium, wherein the storage medium stores a program, and the program is executed by a processor to implement the method for generating a repeated forwarding interference waveform as described above.

[0130] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part for which is described as a larger operation is performed independently.

[0131] The embodiment of the present invention also discloses a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device can read the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the aforementioned repeated forwarding interference waveform generation method.

[0132] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features described may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present invention. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional skills of the engineer. Therefore, those skilled in the art can implement the present invention set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0133] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0134] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0135] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0136] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0137] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0138] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0139] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the described embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for generating a repeated forwarding interference waveform, characterized in that: include: Determine a forwarding configuration of non-uniform intermittent sampling repeated forwarding interference according to an interference waveform generation request, wherein the forwarding configuration includes a process code and a coding sequence time width; Initialize the parameters of the genetic algorithm and determine the parameter configuration of the genetic algorithm; Generate an initial population according to the forwarding configuration, calculate the optimal fitness of the initial population using a fitness function, and determine a first optimal individual according to the optimal fitness of the initial population; Using a genetic algorithm to perform iterative generation on individuals in the initial population according to the parameter configuration to obtain the next generation population, wherein the iterative generation includes selection, crossover and mutation processing; After each iteration generates the next generation population, the optimal fitness of the next generation population is calculated, and the second best individual is determined based on the optimal fitness of the next generation population; In each iteration, the average fitness of the population is calculated, and the iteration is ended according to the average fitness and the end condition to obtain the third optimal individual, and the interference waveform generation result is determined according to the third optimal individual; The adopting of a fitness function to calculate the optimal fitness of the initial population includes: The fitness function for in is the number of false targets generated by the jamming signal, is the interference-to-signal ratio, where the interference-to-signal ratio is the ratio of the interference signal to the real signal power. is the weight of the number of false targets, is the weight of the interference-to-signal ratio, and It is used to balance the number of false targets and the level of interference-to-signal ratio, and is adjusted according to the interference intensity.

2. The method for generating a repeated forwarding interference waveform according to claim 1, characterized in that: The step of generating a request according to an interference waveform and determining a forwarding configuration of non-uniform intermittent sampling repeated forwarding interference includes: The process coding includes a sampling operation "0" and a forwarding operation "1", and the coding sequence time width is the minimum sampling time unit; The non-uniform intermittent sampling repeated forwarding interference for: in, is the impulse function, It is The code element corresponds to the short pulse transmitted, and for: Indicates that the current Sub-sampling operation, represents a rectangular pulse signal, in, is the length of the non-uniform intermittent sampling repeated forwarding interference coding sequence, For the intercepted radar signal, is the minimum sampling time unit, is the number of "0"s in the string of consecutive "0"s before the codeword when the codeword is "1", When the code element is "1", this code element is located in the current "1" string. On the seat, For the The code element on the bit, where , The value range is 0 or 1, and satisfy ,in is the pulse width of the intercepted radar signal, is the rectangular window function, and t is the time.

3. The method for generating a repeated forwarding interference waveform according to claim 1, characterized in that: The parameter configuration includes chromosome and population configuration, wherein the chromosome is a non-uniform intermittent sampling repeated forwarding interference coding sequence; wherein the population configuration includes the number of individuals , Iterations , Algebraic Counter , crossover probability and mutation probability ,in .

4. The method for generating a repeated forwarding interference waveform according to claim 3, characterized in that: The generating an initial population according to the forwarding configuration includes: The number of individuals is randomly generated according to the forwarding configuration chromosomes, forming the initial population of binary code, each chromosome length is , the first bit of each non-uniform intermittent sampling repeated forwarding interference coding sequence is "0", that is, the sampling operation is performed first, and then the forwarding operation is performed.

5. The method for generating a repeated forwarding interference waveform according to claim 1, characterized in that: The individuals in the initial population are iteratively generated using a genetic algorithm according to the parameter configuration to obtain the next generation population, wherein the iterative generation includes selection, crossover and mutation processing, including: The selection roulette operator performs selection on individuals in the initial population, including calculating the fitness of all individuals in the current generation according to the fitness function ,in , the selection probability of each individual is calculated by the fitness value , for is the minimum fitness of all individuals in the current generation; The crossover operation is based on the probability Determine whether to perform crossover. If crossover is performed, randomly select a point on the chromosome to perform single-point crossover on the two chromosomes. The mutation operation is based on probability Determine whether to proceed. If mutation is to be performed, randomly select a point on the chromosome for mutation, wherein the mutation is to invert the code element at the corresponding position of the non-uniform intermittent sampling repeated forwarding interference coding sequence.

6. The method for generating a repeated forwarding interference waveform according to claim 1, characterized in that: The method further comprises: Get the optimal fitness of the generated population at each iteration and the optimal fitness of the newly generated population ,like , then the best individual in the generated population is replaced by the best individual in the new population, otherwise, the best individual in the generated population is retained.

7. A repeated forwarding interference waveform generating device, characterized in that: include: The first module is used to determine a forwarding configuration of non-uniform intermittent sampling repeated forwarding interference according to an interference waveform generation request, wherein the forwarding configuration includes a process code and a coding sequence time width; The second module is used to initialize the parameters of the genetic algorithm and determine the parameter configuration of the genetic algorithm; A third module is used to generate an initial population consisting of binary code sequences according to the forwarding configuration, calculate the optimal fitness of the initial population using a fitness function, and determine a first optimal individual according to the optimal fitness of the initial population; The fourth module is used to perform iterative generation on individuals in the initial population using a genetic algorithm according to the parameter configuration to obtain a next generation population, wherein the iterative generation includes selection, crossover and mutation processing; The fifth module is used to calculate the optimal fitness of the next generation population after each iteration to determine the second best individual according to the optimal fitness of the next generation population; The sixth module is used to calculate the average fitness of the population in each iteration, end the iteration according to the average fitness and the end condition, obtain the third optimal individual, and determine the interference waveform generation result according to the third optimal individual; The adopting of a fitness function to calculate the optimal fitness of the initial population includes: The fitness function for in is the number of false targets generated by the jamming signal, is the interference-to-signal ratio, where the interference-to-signal ratio is the ratio of the interference signal to the real signal power. is the weight of the number of false targets, is the weight of the interference-to-signal ratio, and It is used to balance the number of false targets and the level of interference-to-signal ratio, and is adjusted according to the interference intensity.

8. An electronic device, characterized in that: including a processor and a memory; The memory is used to store programs; The processor executes the program to implement the method for generating a repeated forwarding interference waveform according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The storage medium stores a program, and the program is executed by a processor to implement the repeated forwarding interference waveform generation method according to any one of claims 1 to 6.

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