Ultra-high-speed target detection simulation system and method based on a calibration algorithm

Abstract

The present invention relates to a super-high-speed target detection simulation system and method based on a calibration algorithm, including three major modules: long-time coherent integration based on the calibration algorithm, target feature extraction, and calibration algorithm performance evaluation. It presents the improvement of the long-time coherent integration effect based on the calibration algorithm, completes the comprehensive evaluation of the long-time coherent integration effect, and the system can provide a good verification platform for the analysis and verification of the calibration algorithm. The present invention is reasonably designed and convenient to use.

Description

Technical Field

[0001] The present invention relates to a hypersonic target detection simulation system and method based on a calibration algorithm. Background Art

[0002] With the upgrading of weapons, the detection performance of radar has encountered unprecedented challenges. In particular, hypersonic aircraft have severely tested the long-time coherent integration ability of radar. Therefore, the radar has adopted corresponding calibration algorithms to improve the long-time coherent integration effect and detection range in the face of hypersonic aircraft. With the increasing diversification of radar calibration algorithms, there is an urgent need for a scientific evaluation index system for the long-time coherent integration effect of radar based on calibration algorithms to accurately reflect the long-time coherent integration effect based on calibration algorithms under different noise backgrounds, which is the key to studying the long-time coherent integration method of hypersonic aircraft.

[0003] Affected by many factors such as the actual working environment, equipment, and cost, the demand for evaluating the systematic long-time coherent integration effect is becoming more and more prominent. At present, the research on the evaluation of the long-time coherent integration effect of radar based on calibration algorithms is still relatively scarce, lacking a scientific evaluation system.

[0004] The calibration algorithm is an important means to solve the problem of the decline in the long-time coherent integration performance of hypersonic targets and improve the radar's ability to detect weak hypersonic targets. At present, the evaluation of the long-time coherent integration effect of radar based on calibration algorithms is one-sided and has poor visibility, lacking a systematic and holistic evaluation system. Summary of the Invention

[0005] Generally speaking, the technical problem to be solved by the present invention is to provide a hypersonic target detection simulation system and method based on a calibration algorithm. Based on the coherent integration working system of modern radar, the present invention designs a radar long-time coherent integration effect evaluation simulation system based on the processing of echo signals by a calibration algorithm. First, distance dimension calibration is performed on the echo signal to make the echo envelope centers between different scans concentrate on the initial position; then, Doppler dimension calibration is performed to keep the echo phases in a clear phase relationship; secondly, coherent integration of the echo is performed on the basis of the calibration algorithm, so that good coherent integration effects can still be achieved even in the face of cross-range gates and cross-Doppler gates brought by hypersonic aircraft; finally, the technical indicators of the long-time coherent integration performance of the radar based on the calibration algorithm are evaluated. This system can provide a good verification platform for the verification of the implementation technology of the long-time coherent integration of radar.

[0006] To solve the above problems, the technical solutions adopted by the present invention are as follows:

[0007] Based on the working system of modern early warning radars, the present invention designs and implements a simulation system for evaluating the long-time coherent integration effect based on a calibration algorithm. The system includes three major modules: long-time coherent integration based on the calibration algorithm, target feature extraction, and calibration algorithm performance evaluation. It presents the improvement of the long-time coherent integration effect based on the calibration algorithm, completes a comprehensive evaluation of the long-time coherent integration effect, and can provide a good verification platform for the analysis and verification of the calibration algorithm.

[0008] The present invention is reasonably designed, low in cost, sturdy and durable, safe and reliable, simple to operate, time-saving and labor-saving, cost-saving, compact in structure and convenient to use. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is the early warning effect evaluation system diagram of the present invention.

[0010] Figure 2 is the functional architecture diagram of the effect evaluation system of the present invention.

[0011] Figure 3 is the coherent integration simulation evaluation flowchart based on the calibration algorithm of the present invention.

[0012] Figure 4 is the interface schematic diagram of the system of the present invention.

[0013] Figure 5 is the schematic diagram of the present invention without using the calibration algorithm.

[0014] Figure 6 is the schematic diagram of the present invention using the calibration algorithm.

[0015] Figure 7 is the measurement accuracy schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] As Figures 1-7 , the ultra-high-speed target detection simulation system and method based on the calibration algorithm of this embodiment perform the following steps:

[0017] S1. Technically process the echo signal through the calibration algorithm of the radar;

[0018] S1.1. Calibrate the range dimension;

[0019] Assume that the radar transmission signal form is a linear frequency modulation wave, then its form expression during one scan is as follows:

[0020] s(t) = b(t - mT r )exp[j2πf c (t - mT r )] (1);

[0021] Where: b(t) is the baseband signal of the chirp signal, T r is the pulse repetition period of the radar; f c is the carrier frequency of the radar transmitted signal; m is the pulse sequence number during one scan of the radar;

[0022] The parameter j is the imaginary part flag; K f is the chirp rate of the chirp signal s(t);

[0023] Then, the frequency domain form of the radar echo after down-conversion and pulse compression is:

[0024]

[0025] Where: t m = mT r , which is called the slow time; τ = t - t m , which is called the fast time; a is the acceleration of the target moving in a uniform straight line, t m is the slow time dimension t m = mT r , m is the pulse sequence number, T r is the pulse repetition period; v t is the target radial velocity, f c is the carrier frequency of the radar chirp signal, f o = f c ; R o is the initial distance of the target, c is the speed of light, and B is the bandwidth of the chirp signal;

[0026] Secondly, it is deduced from formula (2) that the movement of the envelope center in the distance dimension is due to the scale transformation effect of the slow time dimension on the frequency, and the keystone algorithm performs a variable substitution of t m as t om = f / (f + f c )t m , and the echo form becomes:

[0027]

[0028] t om is the slow time dimension after scale transformation, and τ is the fast time dimension; then it is deduced from formula (3) that the envelope center of the echo is centralized by the keystone algorithm;

[0029] S1.2, Calibration through the Doppler dimension algorithm

[0030] First, based on the discovery from equation (3) that the range - dimension walk is due to the existence of the second - order phase term in the slow - time dimension exp(), therefore, only by compensating the second - order phase term can the Doppler - dimension walk be corrected. Thus, the Doppler - dimension correction problem is transformed into a second - order term parameter - estimation problem. The HAF algorithm defines the second - order instantaneous moment:

[0031]

[0032] Calculated through the second - order instantaneous moment:

[0033] x k (t;t0)=Aexp(j2π(b1t + b0)) (5)

[0034] where: b1=-2t0a / λ, where λ is the radar signal wavelength, x1(t), x2(t) are the defined first - order moment and second - order moment, which are mathematical representation forms. b1 is the carrier frequency of the second - order moment, b0 is the initial phase of the second - order moment; t0 is a delay time defined according to the operation, and in this system, it takes 0.2. Again, the HAF algorithm transforms the second - order term parameter - estimation problem into a point - frequency signal frequency - measurement problem through the operation of the second - order instantaneous moment, thereby realizing the correction of the hypersonic target echo.

[0035] S2. Design a long - time coherent integration effect evaluation system

[0036] S2.1. Coherent integration effect evaluation system based on the correction algorithm

[0037] The radar long - time coherent integration effect evaluation system based on the correction algorithm includes the echo signal correction ability and the target detection ability. Among them, in the part of the echo signal correction ability, it includes the range - dimension correction deviation range, Doppler - dimension parameter - estimation error, and echo signal correction time; in the part of the target detection ability, it includes the signal - to - noise ratio improvement value, detection power change, number of false and real targets, and target acquisition probability, which reflect the improvement of the long - time coherent integration effect after the correction algorithm.

[0038] S2.2. Design the system function

[0039] As Figure 2 shown, the early - warning effect simulation evaluation system based on the correction algorithm includes

[0040] The long - time coherent integration simulation part based on the correction algorithm, which is used to generate the motion parameters of the specified simulated target or randomly generate target parameters, and generate the corresponding radar echo signal, add it to the radar receiver and add the specified amplitude and category or randomly generated system noise. After the radar signal processing of quadrature down - conversion and pulse compression, the range - dimension correction is carried out by the selected implementation method of the keystone algorithm and the Doppler - dimension correction by the HAF algorithm, and coherent integration is carried out on the basis of the correction.

[0041] The simulation part of target feature extraction is used to perform constant false alarm detection on the coherent accumulation results of the long-time coherent accumulation simulation part based on the calibration algorithm, automatically generate a detection threshold according to the signal input, search for targets. If a target is determined to exist, the target motion state is extracted through the characteristic parameters of the calibrated echo signal, where the radial initial velocity of the target is extracted through the Doppler frequency shift of the calibrated echo; the radial acceleration of the target is extracted through the parameter estimation of the HAF algorithm; the distance of the target is extracted from the delay of the calibrated echo, and the influence of the target is removed using the clear algorithm, and the system transfers to the next round of target search until no target is determined or the exit operation is executed;

[0042] The performance evaluation part of the long-time coherent accumulation effect based on the calibration algorithm is used to calculate the changes in the detection level of the radar for hypersonic targets after calibration, such as the improvement value of the signal-to-noise ratio, the change in detection power, the number of false alarm targets, and the target capture probability, and to determine the accuracy of target parameter extraction.

[0043] S2.3, System execution workflow

[0044] According to the working process of the long-time coherent accumulation effect based on the calibration algorithm, a simulation system for evaluating the long-time coherent accumulation effect of a radar based on the calibration algorithm is constructed. The simulation system for evaluating the long-time coherent accumulation effect of a radar establishes a dynamic closed-loop simulation environment for detecting simulated targets by the radar transceiver signals through simulating the signal processing process of the airborne radar and target generation functional modules, with a single scan interval as the single simulation time unit. The workflow design of the simulation system for evaluating the early warning effect of a radar based on the calibration algorithm is as Figure 3 shown.

[0045] First, the system generates corresponding echo signals according to the specified target parameters or randomly generated target parameters and inputs them into the radar receiving channel; then, after the echo signals enter the radar receiving channel, internal noise with a specified amplitude or randomly generated by the system is added, and quadrature down-conversion and matched filtering are performed; secondly, pulse compression is carried out; thirdly, range dimension calibration is implemented according to the selected implementation method of the keystone algorithm, and the implementation methods include Sinc interpolation method, DFT-IFFT transformation method, or Charp-Z; subsequently, on the basis of range dimension calibration, the HAF algorithm is used for Doppler dimension calibration and coherent accumulation. After coherent accumulation is completed, the targets are searched according to the threshold automatically determined by the system, and the target motion state is extracted; afterwards, the coherent accumulation performances of the radar with and without the calibration algorithm are compared to evaluate the effect of the calibration algorithm, providing a basis for the improvement and verification of the calibration algorithm.

[0046] 2.4 System interface design

[0047] As Figure 4As shown in the figure, the interface design of the system includes 4 major sections, namely the simulated target parameter section, the calibration algorithm selection section, the noise parameter setting section, and the effect evaluation section;

[0048] The 10 interfaces for human-computer interaction are respectively the pop-up menu for the target generation method in the simulated target parameter section, the input boxes for target distance, target speed, and target acceleration; the pop-up menu for the range dimension calibration method and the input box for the delay coefficient of the HAF algorithm in the calibration algorithm selection section; the pop-up menu for the noise type and the input box for the input signal-to-noise ratio in the noise parameter setting section; the radar display screen and the target acquisition probability button in the effect evaluation section.

[0049] Each module is independent of each other, and parameters such as the signal parameters and false alarm rate of the radar can be modified in the background program.

[0050] The simulated target parameter module is responsible for generating corresponding simulated targets according to the specified number of targets, speed, and acceleration. When the generation method is selected as random generation, the system generates simulated targets randomly with a uniform distribution according to the target distance ranging from 30 km to 80 km, the target speed from 0 m / s to 6000 m / s, and the target acceleration from 0 m / s 2 to 6000 m / s 2

[0051] The calibration algorithm selection section performs range dimension calibration according to the specified calibration algorithm and Doppler dimension calibration according to the input value of the delay coefficient of the HAF algorithm; the calibration algorithms include the Sinc interpolation method, the DFT-IFFT transformation method, and the Charp-Z transformation method;

[0052] The noise parameter setting section sets the noise type according to the specified one. When the generation method is selected as random generation, the system randomly selects one of the above noise types and adds noise according to the specified input signal-to-noise ratio; the noise types include Gaussian white noise, exponential distribution noise, Poisson distribution noise, uniform distribution noise, and Rayleigh distribution noise.

[0053] The effect evaluation section is used to display the numerical values of various indicators of the radar warning after the calibration algorithm, and the corresponding pictures or data can be viewed through the radar display screen and the target acquisition probability button;

[0054] S3. Simulation analysis

[0055] S3.1 Performance analysis of calibration algorithms

[0056] First, the condition settings are as follows: the radar transmitting signal is a linear frequency modulation signal, the internal noise of the system is Gaussian white noise, the input signal-to-noise ratio of the system is -35 dB, the pulse repetition frequency of the radar is 2000 Hz, the number of pulses accumulated between one scan is 256, the initial target speed is set to 3000 m / s, and the target acceleration is 100 m / s 2 ​, The initial distance is 40 km. Figure 5 , Figure 6 They are the processing results of the simulation system without the correction algorithm and under the signal processing flow shown in Figure 3 respectively.

[0057] Then, Figure 7 The accuracy of the acceleration measurement value and the accuracy of the distance measurement value obtained through 100 Monte Carlo experiments by controlling different signal-to-noise ratios for different input signal-to-noise ratios are shown. Among them, the accuracy of the acceleration measurement value is more than 98% when the input signal-to-noise ratio is greater than -35 dB, and the accuracy of the distance measurement value is more than 98% when the input signal-to-noise ratio is greater than -38 dB. Then, when the signal-to-noise ratio is greater than -35 dB, the improvement value of the signal-to-noise ratio compared to without correction is more than 19.15 dB, and the detection power is increased by 301.21%.

[0058] S3.2 Algorithm Complexity Comparative Analysis

[0059] Table 1 lists the multiplication and addition operation amounts of three correction algorithms in the distance dimension, where N is the number of pulse accumulations between one scan, and M is the number of sampling points of the echo signal in the fast time dimension. In S3.1, N is 256 and M is 5001. From the data in Table 1, it can be obtained that the Charp-Z transform method has obvious advantages in terms of algorithm complexity compared with the other two algorithms, and the more the number of pulse accumulations, the more obvious the advantage. Taking the simulation data in 3.1 as an example, the multiplication complexity of the Sinc interpolation method is 3.27×10 8 , and the addition complexity is 3.26×10 8 ; the multiplication complexity of the Charp-Z transform method is 4.48×10 7 , and the addition complexity is 4.35×10 7 .

[0060] Table 1 Algorithm Complexity Comparison

[0061]

[0062]

[0063] In view of the one-sidedness of the evaluation of the long-time coherent accumulation effect of the radar based on the correction algorithm, the present invention proposes a radar long-time coherent accumulation effect evaluation system. On the basis of the principle of the correction algorithm optional in the system, an evaluation system with the target detection ability as the core, including elements such as the signal-to-noise ratio improvement value and the detection power transformation, is established. The reliability of the system is verified through simulation, and the effects of the early warning system based on the correction algorithm are compared through the simulation system. The improvement of the long-time coherent accumulation effect based on the correction algorithm is given, and the all-round evaluation of the long-time coherent accumulation effect is completed, providing a good verification platform for the analysis and verification of the correction algorithm.

Claims

1. A super-high-speed target detection simulation method based on a calibration algorithm, characterized in that: Execute the following steps: S1. Technically process the echo signal through the calibration algorithm of the radar; S1.

1. Calibrate the range dimension; First, assume that the radar transmitted signal form is a linear frequency modulation wave, then its form expression during one scan is as follows: （1）； In the formula: is the baseband signal of the chirp signal, ; is the pulse repetition period of the radar; t is the time variable, and Tp is the pulse width; is the carrier frequency of the radar transmitted signal; m is the pulse sequence number during one scan of the radar; The parameter j is the imaginary part flag; K f is the frequency modulation rate of the linear frequency modulation wave s(t); Then, the frequency domain form of the radar echo after down-conversion and pulse compression is derived as: （2） In the formula: , which is called slow time; , which is called fast time; a is the target acceleration of uniform linear motion, t m is the slow time dimension t m = mT r , where m is the pulse sequence number and T r is the pulse repetition period; v t is the target radial velocity, f c is the carrier frequency of the radar chirp signal, f o = f c ; R o is the target initial distance, c is the speed of light, and B is the bandwidth of the chirp signal; Secondly, it is deduced from formula (2) that the movement of the envelope center in the range dimension is due to the scaling effect of the slow time dimension on the frequency, and the Keystone algorithm performs variable substitution on to change the echo form to: ​ （3）； t om is the slow time dimension after scale transformation, is the fast time dimension; then it is deduced from formula (3) that the envelope center of the echo is concentrated by the keystone algorithm; S1.

2. Calibrate through the Doppler dimension algorithm; First, based on the discovery from equation (3) that the range dimension walk is due to the existence of the second-order phase term in the slow time dimension, compensate for the second-order phase term to correct the Doppler dimension walk; then, transform the Doppler dimension calibration problem into a second-order term parameter estimation problem. The HAF algorithm defines the second-order instantaneous moment: （4）； Second, calculate through the second-order instantaneous moment: （5）； Wherein: , where is the radar signal wavelength, x1(t) and x2(t) are the defined first-order moment and second-order moment, which are mathematical representation forms, b1 is the carrier frequency of the second-order moment, b0 is the initial phase of the second-order moment; t0 is a delay time defined according to the operation, and in this system, it is taken as 0.2; Third, the HAF algorithm transforms the second-order term parameter estimation problem into a point-frequency signal frequency measurement problem through the operation of the second-order instantaneous moment, thereby realizing the calibration of the hypersonic target echo; S2. Design a long-time coherent integration effect evaluation system; S2.

1. Establish a coherent integration effect evaluation system based on the calibration algorithm; Among them, the long-time coherent integration effect evaluation system of the radar based on the calibration algorithm includes an echo signal calibration ability part and a target detection ability part; among them, The echo signal calibration ability part includes the range dimension calibration deviation range, Doppler dimension parameter estimation error, and echo signal calibration time; The target detection ability part includes the signal-to-noise ratio improvement value, detection power change, number of false and real targets, and target acquisition probability, to reflect the improvement of the long-time coherent integration effect after the calibration algorithm; S2.

2. According to S2.1, design an early warning effect simulation evaluation system based on the calibration algorithm Among them, the early warning effect simulation evaluation system based on the calibration algorithm includes The long-time coherent integration simulation part based on the calibration algorithm, which is used to generate the motion parameters of a specified simulated target or randomly generate target parameters, and generate the corresponding radar echo signal, add it to the radar receiver and add the specified amplitude and category or randomly generated system noise, and perform range dimension calibration and Doppler dimension calibration of the HAF algorithm by the implementation method of the selected keystone algorithm after radar signal processing such as quadrature down-conversion and pulse compression, and perform coherent integration on the basis of calibration; The target feature extraction simulation part, which is used to perform constant false alarm detection on the coherent integration result of the long-time coherent integration simulation part based on the calibration algorithm, automatically generate a detection threshold according to the signal input, search for the target, and if it is determined that there is a target, extract the target motion state through the characteristic parameters of the calibrated echo signal, where the radial initial velocity of the target is extracted through the Doppler frequency shift of the calibrated echo; the radial acceleration of the target is extracted through the parameter estimation of the HAF algorithm; the distance of the target is extracted by the delay of the calibrated echo, use the clear algorithm to eliminate the influence of this target, and transfer to the next round of target search until it is determined that there is no target or the exit operation is executed; The part of performance evaluation of long-time coherent integration effect based on the calibration algorithm is used to calculate the change in the detection level of hypersonic targets by the radar after calibration, including the improvement value of signal-to-noise ratio, the change in detection power, the number of false alarm targets, and the target capture probability, and to judge the accuracy of target parameter extraction.

2. The ultra-high-speed target detection simulation method based on a calibration algorithm according to claim 1, characterized in that: S2.3, design the system execution workflow; On the premise that, according to the working process of the long-time coherent integration effect based on the calibration algorithm, a simulation system for evaluating the long-time coherent integration effect of the radar based on the calibration algorithm is constructed. The simulation system for evaluating the long-time coherent integration effect of the radar simulates the signal processing process of the airborne radar and target generation functional modules, and takes one scan interval as the single simulation time unit to establish a dynamic closed-loop simulation environment for the radar transceiver signal to detect the simulated target; First, the system generates the corresponding echo signal according to the specified target parameters or randomly generated target parameters and inputs it into the radar receiving channel; Then, after the echo signal enters the radar receiving channel, internal noise with a specified amplitude or randomly generated by the system is added, and quadrature down-conversion and matched filtering are performed; secondly, pulse compression is carried out; thirdly, range dimension correction is implemented according to the selected implementation method of the keystone algorithm, and the implementation methods include Sinc interpolation method, DFT-IFFT transformation method or Charp-Z; subsequently, on the basis of range dimension correction, the HAF algorithm is used for Doppler dimension correction and coherent integration. After completing the coherent integration, the target is searched according to the threshold automatically determined by the system, and the target motion state is extracted; after that, the radar coherent integration performance with and without the calibration algorithm is compared to evaluate the effect of the calibration algorithm and provide a basis for the improvement and verification of the calibration algorithm.

3. The super-high-speed target detection simulation method based on a calibration algorithm according to claim 2, wherein: S2.4 Design the interface of the simulation evaluation system for early warning effect based on the calibration algorithm; among them, the modules of the simulation evaluation system for early warning effect based on the calibration algorithm include the simulated target parameter section, the calibration algorithm selection section, the noise parameter setting section and the effect evaluation section; the human-computer interaction interfaces are respectively the pop-up menu of the target generation method in the simulated target parameter section, the input boxes for target distance, target speed and target acceleration; the pop-up menu of the range dimension correction method and the input box of the delay coefficient of the HAF algorithm in the calibration algorithm selection section; the pop-up menu of the noise type and the input box of the input signal-to-noise ratio in the noise parameter setting section; the radar display screen and the target capture probability button in the effect evaluation section; Each module is independent of each other, and the signal parameters of the radar and the parameters of the false alarm rate are modified in the background program; The simulation target parameter module is responsible for generating corresponding simulation targets according to the specified target quantity, speed, and acceleration. When the generation method is selected as random generation, the system randomly generates simulation targets with a target distance ranging from 30 km to 80 km, a target speed from 0 m / s to 6000 m / s, and a target acceleration from 0 m / s 2 to 6000 m / s 2 and randomly generates simulation targets in a uniform distribution; The calibration algorithm selection section performs range dimension correction according to the specified calibration algorithm and Doppler dimension correction according to the input value of the delay coefficient of the HAF algorithm; the calibration algorithms include Sinc interpolation method, DFT-IFFT transformation method and Charp-Z transformation method; The noise parameter setting section, according to the specified noise type, when the selection generation method is randomly generated, the system will randomly select one of the above noise types and add noise according to the specified input signal-to-noise ratio; the noise types include Gaussian white noise, exponential distribution noise, Poisson distribution noise, uniform distribution noise, Rayleigh distribution noise; An effect evaluation section for displaying the numerical values of various indicators of the radar warning after the calibration algorithm, and the corresponding pictures or data can be viewed through the radar display screen and the target acquisition probability button.

4. The ultra-high speed target detection simulation method based on the calibration algorithm according to claim 3, characterized in that: S3. Simulation analysis; S3.

1. Performance analysis of the calibration algorithm; First, set the conditions: The radar transmitting signal is a linear frequency modulation signal, the internal noise of the system is Gaussian white noise, the input signal-to-noise ratio of the system is -35 dB, the pulse repetition frequency of the radar is 2000 Hz, the number of pulses accumulated between one scan is 256, the initial velocity of the target is set to 3000 m / s, and the target acceleration is 100 m / s 2 , and the initial distance is 40 km; Then, the accuracy of the acceleration measurement value and the accuracy of the distance measurement value obtained through 100 Monte Carlo experiments by controlling different signal-to-noise ratios under different input signal-to-noise ratio backgrounds; S3.2 Comparative analysis of algorithm complexity; First, the multiplication and addition operation amounts of the three calibration algorithms in the range dimension, Sinc interpolation method, its multiplication , its addition ; DFT-IFFT transformation method , its addition ; Charp-Z transform method , its addition ; where N is the number of pulse accumulations between scans, and M is the number of sampling points of the echo signal in the fast time dimension. In S3.1, N is 256 and M is 5001; Then, it is obtained through comparison that the Charp-Z transform method has advantages in terms of algorithm complexity compared with the other two algorithms, and the more the number of pulse accumulations, the more obvious the advantages.

5. A super-high-speed target detection simulation system based on a calibration algorithm, characterized in that: For implementing the ultra-high-speed target detection simulation method described in any one of claims 1-4; the system includes a radar long-time coherent accumulation effect evaluation system based on the calibration algorithm and a warning effect simulation evaluation system based on the calibration algorithm; The radar long-time coherent accumulation effect evaluation system based on the calibration algorithm includes an echo signal calibration ability part and a target detection ability part; among them, The echo signal calibration ability part includes the calibration deviation range in the range dimension, the parameter estimation error in the Doppler dimension, and the echo signal calibration time; The target detection ability part includes the signal-to-noise ratio improvement value, the change in detection power, the number of false and real targets, and the target acquisition probability to reflect the improvement of the long-time coherent accumulation effect after the calibration algorithm; The warning effect simulation evaluation system based on the calibration algorithm includes The long-time coherent accumulation simulation part based on the calibration algorithm, which is used to generate the motion parameters of the specified simulated target or randomly generate target parameters, and generate the corresponding radar echo signal, add it to the radar receiver and add the specified amplitude and category or randomly generated system noise, and perform range dimension calibration and Doppler dimension calibration of the HAF algorithm by using the implementation method of the selected keystone algorithm after radar signal processing such as quadrature down-conversion and pulse compression, and perform coherent accumulation on the basis of calibration; The target feature extraction simulation part, which is used to perform constant false alarm detection on the coherent accumulation result of the long-time coherent accumulation simulation part based on the calibration algorithm, automatically generate a detection threshold according to the signal input, search for the target, and if it is determined that there is a target, extract the target motion state through the characteristic parameters of the calibrated echo signal, where the radial initial velocity of the target is extracted through the Doppler frequency shift of the calibrated echo; the radial acceleration of the target is extracted through the parameter estimation of the HAF algorithm; the distance of the target is extracted by the delay of the calibrated echo, use the clear algorithm to eliminate the influence of this target, and transfer to the next round of target search until it is determined that there is no target or the exit operation is executed; The part for evaluating the performance of long-time coherent integration based on the calibration algorithm is used to calculate the changes in the detection level of hypersonic targets by the radar after calibration, including the improvement value of signal-to-noise ratio, the change in detection power, the number of false alarm targets, and the target capture probability, and to determine the accuracy of target parameter extraction.

6. The ultra-high-speed target detection simulation system based on a calibration algorithm according to claim 5, characterized in that: According to the working process of long-time coherent integration based on the calibration algorithm, a simulation system for evaluating the long-time coherent integration effect of the radar based on the calibration algorithm is constructed. The simulation system for evaluating the long-time coherent integration effect of the radar simulates the signal processing process of the airborne radar and the target generation function module, and takes one scan interval as the single simulation time unit to establish a dynamic closed-loop simulation environment for the radar transceiver signal to detect the simulated target. First, the system generates corresponding echo signals according to the specified target parameters or randomly generated target parameters and inputs them into the radar receiving channel. Then, after the echo signal enters the radar receiving channel, internal noise with a specified amplitude or randomly generated by the system is added, and quadrature down-conversion and matched filtering are performed. Secondly, pulse compression is carried out. Thirdly, range dimension calibration is implemented according to the selected implementation method of the keystone algorithm, namely the transformation method, and the implementation methods include Sinc interpolation method, DFT-IFFT transformation method, or Charp-Z. Subsequently, on the basis of range dimension calibration, the HAF algorithm is used for Doppler dimension calibration and coherent integration. After completing coherent integration, the target is searched according to the threshold automatically determined by the system, and the target motion state is extracted. After that, the coherent integration performance of the radar with and without the calibration algorithm is compared to evaluate the effect of the calibration algorithm and provide a basis for the improvement and verification of the calibration algorithm.

7. The super-high-speed target detection simulation system based on a calibration algorithm according to claim 6, characterized in that: The system includes designing the interface of the simulation evaluation system for the early warning effect based on the calibration algorithm. Among them, the modules of the simulation evaluation system for the early warning effect based on the calibration algorithm include the simulated target parameter section, the calibration algorithm selection section, the noise parameter setting section, and the effect evaluation section. The human-computer interaction interfaces are respectively the pop-up menu for the target generation method in the simulated target parameter section, the input boxes for target distance, target speed, and target acceleration; the pop-up menu for the range dimension calibration method and the input box for the delay coefficient of the HAF algorithm in the calibration algorithm selection section; the pop-up menu for the noise type and the input box for the input signal-to-noise ratio in the noise parameter setting section; the radar display screen and the target capture probability button in the effect evaluation section. Each module is independent of each other, and the signal parameters of the radar and the parameters of the false alarm rate are modified in the background program. The simulated target parameter module is responsible for generating corresponding simulated targets according to the specified target quantity, speed, and acceleration. When the generation method is selected as random generation, the system randomly generates simulated targets with a target distance ranging from 30 km to 80 km, a target speed ranging from 0 m / s to 6000 m / s, and a target acceleration ranging from 0 m / s 2 to 6000 m / s 2 in a uniform distribution; In the calibration algorithm selection section, range dimension calibration is carried out according to the specified calibration algorithm and Doppler dimension calibration is carried out according to the input value of the delay coefficient of the HAF algorithm. The calibration algorithms include Sinc interpolation method, DFT-IFFT transformation method, and Charp-Z transformation method. In the noise parameter setting section, according to the specified noise type, when the selection generation method is random generation, the system will randomly select one of the above noise types and add noise according to the specified input signal-to-noise ratio. The noise types include Gaussian white noise, exponential distribution noise, Poisson distribution noise, uniform distribution noise, and Rayleigh distribution noise. The effect evaluation section is used to display the numerical values of various indicators of the radar warning after the calibration algorithm, and the corresponding pictures or data can be viewed through the radar display screen and the target acquisition probability button.

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