A coherent accumulation method of echo energy of high-speed maneuvering target

Abstract

This invention relates to the field of radar signal processing technology, and particularly to a coherent accumulation method for the echo energy of high-speed maneuvering targets. The method includes: removing range curvature from the echoes of high-speed maneuvering targets using a second-order Keystone transform; estimating acceleration using a genetic algorithm to compensate for the quadratic phase; then applying another second-order Keystone transform to correct range travel; estimating velocity ambiguity numbers using a genetic algorithm to compensate for ambiguity phase; and finally coherently accumulating multiple pulse echoes to achieve target detection. The genetic algorithm includes: determining the search range for acceleration and ambiguity numbers; initializing the population and calculating fitness values; updating the population through genetic operator operations to obtain the maximum fitness value and the corresponding optimal individual, thus obtaining the optimal solution to the problem.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and in particular to a coherent accumulation method for the echo energy of high-speed maneuvering targets. Background Technology

[0002] In recent years, with the development of aerospace technology, various high-speed maneuvering targets, such as hypersonic missiles, fighter jets, and drones, have emerged in large numbers. To improve radar's target detection capabilities, long-term coherent accumulation techniques are typically used to enhance the signal-to-noise ratio. However, as the accumulation time increases, range travel and Doppler frequency shift phenomena also occur, making it difficult for traditional accumulation algorithms like Moving Target Detection (MTD) to effectively improve the accumulation gain of the echo signal. Therefore, it is necessary to appropriately process the echo signal to eliminate the effects of range travel and Doppler frequency shift, thereby achieving effective pulse accumulation.

[0003] For the detection of high-speed maneuvering targets with uniformly accelerated motion models, many coherent accumulation methods have been proposed. J. Su et al. proposed a KT-DP-based coherent accumulation algorithm, which first corrects first-order range migration using KT, and then uses DP to estimate the target acceleration and compensate for phase differences to eliminate Doppler migration. XLLi et al. proposed a KT-FRFT-based coherent accumulation algorithm, which uses FRFT operations to eliminate Doppler frequency migration and coherently accumulates the target energy. X. Rao et al. proposed an IAR-FRFT coherent accumulation algorithm, which uses IAR to correct first-order range migration. However, all of the above algorithms neglect the influence of second-order range migration and can only correct first-order range migration caused by target velocity. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a coherent accumulation method for the echo energy of high-speed maneuvering targets, comprising the following steps:

[0005] S1: Acquire the raw echo signal of a high-speed maneuvering target;

[0006] S2: Perform a Fourier transform on the original echo signal in the fast time dimension to obtain the distance frequency-slow time dimension signal;

[0007] S3: An echo pulse compressed signal is obtained by pulse compression of the distance-frequency-slow time dimension signal;

[0008] S4: Perform the first second-order Keystone transform on the echo pulse compression signal in the slow time dimension to obtain the first second-order Keystone transform signal;

[0009] S5: Estimate the acceleration of the high-speed maneuvering target using a genetic algorithm, and establish a first compensation function to compensate for the phase of the quadratic term of the acceleration. Process the first second-order Keystone transform signal using the first compensation function to obtain the first compensation signal.

[0010] S6: Perform a second second-order Keystone transform on the first compensation signal in the slow time dimension to obtain the second second-order Keystone transform signal.

[0011] Furthermore, after step S6, the following is also included:

[0012] S7: Use a genetic algorithm to estimate the velocity ambiguity number of the high-speed maneuvering target, and establish a second compensation function to compensate for the velocity ambiguity phase. Use the second compensation function to process the second second-order Keystone transform signal to obtain the second compensation signal.

[0013] S8: The coherent accumulation of the echo energy of the high-speed maneuvering target is completed by performing the Fourier transform on the second compensation signal in the slow time dimension.

[0014] Preferably, step S1 further includes:

[0015] S11: The high-speed maneuvering target receives a transmitted signal using a linear frequency modulated pulse signal. The transmitted signal uses a linear frequency modulated pulse signal, and its time-domain expression is:

[0016]

[0017] in, For the amplitude of the transmitted signal, For carrier frequency, For frequency modulation slope, The imaginary unit,

[0018]

[0019] ,

[0020] The echo signal after the transmitted signal is reflected by the high-speed maneuvering target is represented as follows:

[0021]

[0022] in, Echo amplitude, For fast time, T is the pulse width. For carrier frequency, For frequency modulation slope, The imaginary unit, For rectangular window functions, For slow time, It is a pulse sequence. The pulse repetition period, For echo delay, Let c be the instantaneous distance between the high-speed maneuvering target and the radar, and c be the propagation speed of electromagnetic waves. satisfy:

[0023] ;

[0024] S12: Calculate the motion model of the high-speed maneuvering target relative to the radar by establishing the motion model of the target. Specifically:

[0025]

[0026] in, The initial distance between the high-speed maneuvering target and the radar is given. Let α represent the initial velocity of the high-speed maneuvering target, and let α represent the acceleration.

[0027] Preferably, step S2 further includes:

[0028] S21: Discretize the original echo signal in the fast time dimension according to the sampling frequency and number of sampling points preset by the pulse Doppler radar to obtain the discrete signal after discretization.

[0029] S22: Perform the Fourier transform on the discrete signal quickly to obtain the distance-frequency-slow time dimension signal.

[0030] Preferably, step S3 further includes:

[0031] The distance-frequency-slow-time dimension signal is multiplied by the pulse compression reference signal to obtain the echo pulse compression signal in the distance-frequency-slow-time two-dimensional plane.

[0032] Preferably, step S4 further includes:

[0033] The transformation scale of the first second-order Keystone transform is:

[0034]

[0035] in This represents the distance frequency corresponding to a fast time. For carrier frequency, For slow time, i.e., the first slow time variable, It is the transformed slow time, i.e., the second slow time variable.

[0036] Preferably, step S5 further includes:

[0037] S51: The search acceleration is binary encoded to obtain the encoded acceleration, and the encoded acceleration is converted into the first chromosome composed of genes in the genetic space;

[0038] S52: The acceleration value is estimated by using the genetic algorithm based on the first chromosome;

[0039] S53: Substitute the estimated acceleration value into the first compensation function to construct a quadratic phase compensation term for compensating the phase of the quadratic term.

[0040] Preferably, step S6 further includes:

[0041] The transformation scale of the second second-order Keystone transform is:

[0042]

[0043] in It is the second slow time variable The transformed slow time is the third slow time variable.

[0044] Preferably, step S7 further includes:

[0045] S71: The search speed fuzzy number is binary encoded to obtain the encoded speed fuzzy number, and the speed fuzzy number is converted into a second chromosome composed of genes in the genetic space;

[0046] S72: The genetic algorithm is used to estimate the value of the velocity fuzzy number based on the second chromosome, i.e., to estimate the velocity fuzzy value;

[0047] S73: Substitute the estimated velocity fuzzy value into the second compensation function to construct a fuzzy phase compensation term for compensating the fuzzy phase.

[0048] Preferably, when using the genetic algorithm to iteratively search the fuzzy numbers of the search acceleration and the search speed, the crossover probability is taken as follows: The mutation probability is taken as .

[0049] The genetic algorithm terminates its operation under the following conditions:

[0050] Case 1: The genetic algorithm operation ends when the number of iterations reaches a predetermined value;

[0051] Case 2: The genetic algorithm operation ends when the fitness of the individual after iteration, i.e., a certain value of the search acceleration or a certain value of the search speed fuzzy number, reaches a set threshold.

[0052] Case 3: After several iterations, the population fitness region, i.e., the number of generations in which the search acceleration or the search speed fuzzy number is stable, exceeds a predetermined value.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] 1) This invention corrects the distance movement caused by target acceleration by using a second-order Keystone transform, then compensates for the quadratic phase of the target echo by estimating the target acceleration, then performs another second-order Keystone transform, and then compensates for the ambiguity phase of the target echo by estimating the target ambiguity number. This corrects the distance curvature caused by acceleration while taking into account the influence of Doppler frequency ambiguity.

[0055] 2) This invention optimizes the acceleration and fuzzy number search process by introducing a genetic algorithm. During the optimization process, it automatically captures and accumulates knowledge about the parameter space and adaptively controls the search process to obtain the global optimal solution. It eliminates blind velocity sidelobe interference and reduces the algorithm complexity. Attached Figure Description

[0056] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0057] Figure 1 This is a flowchart of a method for coherent accumulation of echo energy from a high-speed maneuvering target according to the present invention;

[0058] Figure 2 This is a flowchart illustrating the search acceleration range for a coherent accumulation method for echo energy of a high-speed maneuvering target according to the present invention.

[0059] Figure 3 This is a diagram showing the main radar parameters of a coherent accumulation method for the echo energy of a high-speed maneuvering target according to the present invention.

[0060] Figure 4 The image shows the first iteration process and search results of the coherent accumulation method for echo energy of high-speed maneuvering targets according to the present invention.

[0061] Figure 5 The image shows the first iteration process and search results of the search fuzzy number for the coherent accumulation method of echo energy of a high-speed maneuvering target according to the present invention.

[0062] Figure 6 This is a diagram illustrating the coherent accumulation process of a coherent accumulation method for echo energy of a high-speed maneuvering target according to the present invention. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. Obviously, the described embodiments are only some, not all, of the embodiments described in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without creative effort are within the scope of protection of this application.

[0064] Those skilled in the art will understand that, unless otherwise stated, the singular forms “a” and “an” used herein, and “the”, may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0065] The technical terms involved in this invention are defined as follows:

[0066] An individual's fitness refers to the degree of an individual's advantage in the survival of a population, and is used to distinguish between "good" and "bad" individuals.

[0067] Fitness is calculated using a fitness function, also called an evaluation function, which primarily determines an individual's fitness based on its characteristics.

[0068] Example 1

[0069] Please see Figure 1 As shown in the figure, this embodiment provides a coherent accumulation method for the echo energy of a high-speed maneuvering target, which includes the following steps:

[0070] S1: Acquire the raw echo signal of a high-speed maneuvering target;

[0071] S2: Perform a Fourier transform on the original echo signal in the fast time dimension to obtain the distance-frequency-slow time dimension signal;

[0072] S3: An echo pulse-compressed signal is obtained by pulse compression of the distance-frequency-slow-time dimension signal. Specifically, in this embodiment, pulse compression of the distance-frequency-slow-time dimension signal can be expressed as:

[0073]

[0074] in, The amplitude of the pulse pressure signal. For pulse pressure gain, Let be the echo amplitude, and c be the propagation speed of the electromagnetic wave. For faster maintenance, For signal bandwidth, The imaginary unit, For carrier frequency, The instantaneous distance between a high-speed maneuvering target and the radar. For slow time, It is a pulse sequence. The pulse repetition period;

[0075] S4: Perform the first second-order Keystone transform on the echo pulse compression signal in the slow time dimension to obtain the first second-order Keystone transform signal;

[0076] S5: Use a genetic algorithm to estimate the acceleration of a high-speed maneuvering target, and establish a first compensation function to compensate for the phase of the quadratic term of the acceleration. Use the first compensation function to process the first second-order Keystone transform signal to obtain the first compensation signal.

[0077] S6: Perform a second second-order Keystone transform on the first compensated signal in the slow time dimension to obtain the second second-order Keystone transform signal.

[0078] Furthermore, after step S6, the following is also included:

[0079] S7: Use a genetic algorithm to estimate the velocity ambiguity number of the high-speed maneuvering target, and establish a second compensation function to compensate for the velocity ambiguity phase. Use the second compensation function to process the second second-order Keystone transform signal to obtain the second compensation signal.

[0080] S8: Coherent accumulation of echo energy of high-speed maneuvering targets is achieved by performing Fourier transform on the second compensation signal in the slow time dimension.

[0081] Preferably, step S1 further includes:

[0082] S11: The high-speed maneuvering target receives a transmitted signal using linear frequency modulation (LFM) pulse signals. The time-domain expression of the transmitted signal is:

[0083]

[0084] in, For the amplitude of the transmitted signal, For carrier frequency, For frequency modulation slope, The imaginary unit,

[0085]

[0086] ,

[0087] If the echo signal after the transmitted signal is reflected by a high-speed maneuvering target is represented as:

[0088]

[0089] in, Echo amplitude, For fast time, T is the pulse width. For carrier frequency, B is the frequency modulation slope, and B is the signal bandwidth. The imaginary unit, For rectangular window functions, For slow time, It is a pulse sequence. The pulse repetition period, For echo delay, Let c be the instantaneous distance between the high-speed maneuvering target and the radar, and let c be the propagation speed of electromagnetic waves. satisfy:

[0090]

[0091] Specifically, in this embodiment, if That is, the above formula can be used to calculate the m-th echo signal received by the radar.

[0092] S12: Calculation by establishing a motion model of a high-speed maneuvering target Specifically:

[0093]

[0094] in, The initial distance between the high-speed maneuvering target and the radar. Let α represent the radial initial velocity of the high-speed maneuvering target, and let α represent the radial acceleration. Specifically, in this embodiment, the radar is located at the origin of the reference frame, and there exists a target point M in space, i.e., the high-speed maneuvering target. The instantaneous distance between the radar and the target point M is denoted by α. express, For slow time, For a high-speed maneuvering target with radially uniform acceleration, given the pulse repetition period, Let α represent the initial radial velocity of the high-speed maneuvering target, and let α represent the radial acceleration.

[0095] Preferably, step S2 further includes:

[0096] S21: Discretize the original echo signal in the fast time dimension according to the preset sampling frequency and number of sampling points of the pulse Doppler radar to obtain the discrete signal after discretization.

[0097] S22: Perform a fast Fourier transform on the discrete signal to obtain a distance-frequency-slow time dimension signal.

[0098] Preferably, step S3 further includes:

[0099] Multiplying the range-frequency-slow-time dimension signal by the pulse compression reference signal yields the echo pulse compression signal in the range-frequency-slow-time two-dimensional plane. Specifically, in this embodiment, through fast time... Performing a Fourier transform on Equation 1 yields the pulse compression reference signal in the two-dimensional plane of distance-frequency-slow time dimension. for:

[0100]

[0101] in, It is the amplitude of the signal after Fourier transform. For rectangular window functions, This represents the distance frequency corresponding to a fast time. For signal bandwidth, The imaginary unit, For carrier frequency.

[0102] Due to the high speed of maneuvering targets and the low pulse repetition frequency of radar, Doppler undersampling often occurs. In this case, the velocity of a high-speed maneuvering target can be expressed as:

[0103]

[0104] in, This is the fuzzy number (also known as the folding factor). The actual speed of the high-speed maneuvering target. Indicates blind speed, For wavelength, The pulse repetition period, Represents unambiguous velocity and satisfies .

[0105] Motion model of a high-speed maneuvering target with radial uniform acceleration v0 represents the initial radial velocity of the high-speed maneuvering target. This indicates radial acceleration, when the velocity of the high-speed maneuvering target is radial. Substituting the pulse compression reference signal yields the echo pulse compression signal. :

[0106] ,

[0107] The exponent term in the above formula The distance term represents the target's position in the distance direction; the exponent term... The Doppler term is related to the speed of the high-speed maneuvering target; the exponential term is also relevant. The term is the Doppler frequency modulation term caused by the radial acceleration of a high-speed maneuvering target; the exponential term is also included. For the blurred phase term under undersampling, the slow time term is one of the last three exponential terms. The exponential term is related to the distance frequency. The presence of coupling will cause range travel and range curvature in the echo envelope, and simultaneously, the third exponential term... This will cause a Doppler shift.

[0108] Preferably, step S4 further includes:

[0109] The transformation scale of the first second-order Keystone transform is:

[0110] ,

[0111] in This represents the distance frequency corresponding to a fast time. For carrier frequency, For slow time, i.e., the first slow time variable, This is the transformed slow time, i.e., the second slow time variable. Specifically, in this embodiment, the first second-order Keystone transform signal is:

[0112] .

[0113] Preferably, step S5 further includes:

[0114] S51: The search acceleration is binary encoded to obtain the encoded acceleration, and the encoded acceleration is converted into the first chromosome composed of genes in the genetic space. Specifically, in this embodiment, the range of the search acceleration is determined, and the search acceleration is assumed to be p.

[0115] S52: The acceleration value is estimated based on the first chromosome using a genetic algorithm. Specifically, in this embodiment, a quadratic phase compensation function, i.e., the first compensation function, is constructed. When the search acceleration equals the acceleration of the high-speed maneuvering target, the quadratic phase is compensated, leaving only the linear phase. At this point, the acceleration is estimated. :

[0116] .

[0117] The population is subjected to "selection," "crossover," and "mutation" operations according to a set probability, so that the first chromosome of the population will gradually adapt to the environment and continue to evolve, eventually converging to the individual that is most adapted to the environment, i.e., one chromosome of the first chromosome, thus obtaining the optimal solution to the problem.

[0118] refer to Figure 2 As shown, the search range of acceleration specifically involves applying selection operators, crossover operators, and mutation operators to the population with a certain probability, causing individuals to update and iterate, thus generating new acceleration parameters.

[0119] Selection operator: Selects superior individuals from the current population to be passed on as parents to the next generation. The selection operation uses the fitness of individuals as the evaluation criterion; individuals with higher fitness have a greater probability of being passed on to the next generation.

[0120] Crossover operator: Crossover is the core operation to improve search capabilities, which involves exchanging and recombinating parts of the chromosomes of two parent individuals to generate new individuals;

[0121] Mutation operator: The individual to be mutated randomly selects gene values ​​at certain loci for mutation.

[0122] Preferably, when using a genetic algorithm to iteratively search for the fuzzy numbers of search acceleration and search speed, the crossover probability is taken as follows: The mutation probability is taken as .

[0123] S53: Substitute the estimated acceleration value into the first compensation function to construct a second-phase compensation term for compensating the phase of the second-phase term. Specifically, in this embodiment, Substitution This signal is then multiplied by the first second-order Keystone transform signal to obtain the first compensated signal:

[0124] .

[0125] Preferably, step S6 further includes:

[0126] The transformation scale of the second second-order Keystone transform is:

[0127]

[0128] in It is the second slowest time variable The transformed slow time, also known as the third slow time variable, specifically, in this embodiment, the second second-order Keystone transform signal is:

[0129] .

[0130] Preferably, step S7 further includes:

[0131] S71: Binary encoding is performed on the search speed fuzzy number to obtain the encoded speed fuzzy number, and the speed fuzzy number is converted into a second chromosome composed of genes in the genetic space;

[0132] S72: The velocity fuzzy number is estimated using a genetic algorithm based on the second chromosome, i.e., the velocity fuzzy value is estimated. Specifically, in this embodiment, the process of estimating the velocity fuzzy number using a genetic algorithm is similar to the process of estimating the search acceleration using a genetic algorithm. Assuming the search folding factor is q, a fuzzy phase compensation function, i.e., the second compensation function, is constructed. When the folding factor of the search equals the actual folding factor of the target, the fuzzy phase is compensated, and the estimated velocity fuzzy value is then obtained. ;

[0133] S73: Substitute the estimated velocity ambiguity value into the second compensation function to construct a ambiguity phase compensation term for compensating for the ambiguity phase. Specifically, in this embodiment, Substitute into the second compensation function Then, multiply it with the second second-order Keystone transform signal to obtain the compensated second signal: .

[0134] More preferably, in step S8, the second compensation signal is subjected to a Fourier transform in the slow time dimension as follows:

[0135] .

[0136] The genetic algorithm terminates its operation under the following conditions:

[0137] Case 1: The genetic algorithm terminates when the number of iterations reaches a predetermined value;

[0138] Case 2: The genetic algorithm operation ends when the fitness of the individual after iteration, i.e., a certain value of the search acceleration or a certain value of the search speed fuzzy number, reaches a set threshold.

[0139] Case 3: After several iterations, the population fitness region, i.e., the number of generations in which the search acceleration or search speed is stationary, exceeds a predetermined value.

[0140] Example 2

[0141] This embodiment provides an initial position of a high-speed target moving with uniform acceleration relative to the radar as follows: The radial velocity is The radial acceleration is Specific implementation examples.

[0142] refer to Figure 3 As shown, the main parameters of the radar provided in this embodiment include the center frequency, signal bandwidth, and sampling frequency.

[0143] After processing the data provided above, a first second-order Keystone transform is performed on the echo pulse compression signal in the slow time dimension to eliminate the distance curvature caused by radial acceleration.

[0144] The acceleration of a high-speed maneuvering target is estimated using a genetic algorithm. The search acceleration range is [0, 200]. A compensation function is constructed using the estimated search acceleration to compensate for the phase of the quadratic term caused by the acceleration.

[0145] refer to Figure 4 As shown, the iteration of the search acceleration tends to stabilize after less than 20 iterations. Since the preset "stagnant generation" is 50, the search process terminates after less than 70 iterations. At this time, the best individual (search acceleration) is 50 m / s2, which is consistent with the actual acceleration. This process is the first iteration process and search result of the genetic algorithm for searching acceleration.

[0146] A second second-order Keystone transform is performed on the first compensation signal in the slow time dimension to eliminate distance travel caused by unambiguous velocity.

[0147] A genetic algorithm is used to estimate the velocity ambiguity number, with a search range of [0, 300]. A compensation function is constructed using the estimated ambiguity number to compensate for the ambiguity phase.

[0148] refer to Figure 5 As shown, the iteration count for searching fuzzy numbers tends to stabilize when it is less than 20. When the "iteration count" is set to 18, the best individual (search fuzzy number) is 133, which is consistent with the actual fuzzy number. This process is the second iteration process and search result of the genetic algorithm for searching fuzzy numbers.

[0149] refer to Figure 6 As shown, after the distance travel and Doppler frequency shift of the pulse compression echo signal are eliminated, coherent accumulation is performed on it. Figure (a) shows the result after compensating for the phase of the quadratic term, Figure (b) shows the result after performing the second Keystone transform, Figure (c) shows the result after compensating for the fuzzy phase, and Figure (d) shows the final coherent accumulation result.

[0150] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for coherent accumulation of echo energy of a high-speed maneuvering target, characterized in that, Includes the following steps: S1: Acquire the raw echo signal of a high-speed maneuvering target; S2: Perform a Fourier transform on the original echo signal in the fast time dimension to obtain the distance frequency-slow time dimension signal; S3: An echo pulse compressed signal is obtained by pulse compression of the distance-frequency-slow time dimension signal; S4: Perform the first second-order Keystone transform on the echo pulse compression signal in the slow time dimension to obtain the first second-order Keystone transform signal; S5: Estimate the acceleration of the high-speed maneuvering target using a genetic algorithm, and establish a first compensation function to compensate for the phase of the quadratic term of the acceleration. Process the first second-order Keystone transform signal using the first compensation function to obtain the first compensation signal. S6: Perform a second second-order Keystone transform on the first compensation signal in the slow time dimension to obtain a second second-order Keystone transform signal; S7: The genetic algorithm is used to estimate the velocity ambiguity number of the high-speed maneuvering target, and a second compensation function is established to compensate for the velocity ambiguity phase. The second compensation function is used to process the second second-order Keystone transform signal to obtain the second compensation signal. S8: The coherent accumulation of the echo energy of the high-speed maneuvering target is completed by performing the Fourier transform on the second compensation signal in the slow time dimension.

2. The method according to claim 1, wherein, Step S1 further includes: S11: The high-speed maneuvering target receives a transmitted signal using a linear frequency modulated pulse signal, and the echo signal after the transmitted signal is reflected by the high-speed maneuvering target is represented as: in, Echo amplitude, For fast time, T is the pulse width. For carrier frequency, For frequency modulation slope, The imaginary unit, For rectangular window functions, For slow time, It is a pulse sequence. The pulse repetition period, For echo delay, Let c be the instantaneous distance between the high-speed maneuvering target and the radar, and c be the propagation speed of electromagnetic waves. satisfy: ； S12: calculating the target's velocity by establishing a motion model of the high-speed maneuvering target relative to the radar , specifically: wherein, is the initial distance of the high-speed maneuvering target, is the slow time, denotes the initial velocity of the high-speed maneuvering target, and a denotes the acceleration.

3. The method of claim 2, wherein, Step S2 further includes: S21: Discretize the original echo signal in the fast time dimension according to the sampling frequency and number of sampling points preset by the pulse Doppler radar to obtain the discrete signal after discretization. S22: Perform the Fourier transform on the discrete signal quickly to obtain the distance-frequency-slow time dimension signal.

4. The method of claim 3, wherein, Step S3 further includes: The distance-frequency-slow-time dimension signal is multiplied by the pulse compression reference signal to obtain the echo pulse compression signal in the distance-frequency-slow-time two-dimensional plane.

5. The method of claim 4, wherein, Step S4 further includes: The transformation scale of the first second-order Keystone transform is: in This represents the distance frequency corresponding to a fast time. For carrier frequency, For slow time, i.e., the first slow time variable, It is the transformed slow-time variable, i.e., the second slow-time variable.

6. The method of claim 5, wherein, Step S5 further includes: S51: The search acceleration is binary encoded to obtain the encoded acceleration, and the encoded acceleration is converted into the first chromosome composed of genes in the genetic space; S52: The acceleration value is estimated by using the genetic algorithm based on the first chromosome; S53: Substitute the estimated acceleration value into the first compensation function to construct a quadratic phase compensation term for compensating the phase of the quadratic term.

7. The method of claim 6, wherein the high-speed maneuvering target echo energy coherent accumulation method is characterized in that, Step S6 further includes: The transformation scale of the second second-order Keystone transform is: wherein is the second slow time variable the transformed slow time, i.e. a third slow time variable.

8. The coherent accumulation method for echo energy of a high-speed maneuvering target according to claim 7, characterized in that, Step S7 further includes: S71: The search speed fuzzy number is binary encoded to obtain the encoded speed fuzzy number, and the speed fuzzy number is converted into a second chromosome composed of genes in the genetic space; S72: The genetic algorithm is used to estimate the value of the velocity fuzzy number based on the second chromosome, i.e., to estimate the velocity fuzzy value; S73: Substitute the estimated velocity ambiguity value into the second compensation function to construct an ambiguity phase compensation term for compensating the velocity ambiguity phase.

9. The coherent accumulation method for echo energy of a high-speed maneuvering target according to claim 8, characterized in that, When using the genetic algorithm to iteratively search the search acceleration and the fuzzy number of the search speed, the crossover probability is taken as follows: The mutation probability is taken as .

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