A target tracking method based on coherent accumulation of multi-pulse response signals

Abstract

The present application relates to a kind of target tracking methods based on the coherent accumulation of multiple pulse response signals, the method includes calibration and official work two modes: in calibration mode, active target is fixed in known position, receives multiple pulse response signals emitted by it, estimates the frequency difference and initial phase difference between response signal and ground radar transmission signal;In official work mode, receive multiple pulse response signals emitted by active target, according to frequency difference and initial phase difference, carry out frequency and initial phase compensation to pulse response signal, then carry out matched filtering to obtain distance dimension compression result;The compression result of each pulse is arranged in time sequence to form fast time-slow time two-dimensional data matrix, Fourier transform is carried out to slow time dimension to realize multiple pulse coherent accumulation, and distance-Doppler two-dimensional information is obtained;Finally, the distance scale and Doppler scale of target are determined by peak detection, and the distance and radial velocity of active target are obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of secondary radar signal processing, and particularly relates to a target tracking method based on coherent accumulation of multi-pulse response signals. BACKGROUND

[0002] In a secondary radar system, the core task of target tracking is to extract the motion parameters such as the distance, azimuth / elevation angle and speed of the target from the received signals. However, in existing practical applications, in order to achieve long-distance tracking of active targets, high power or large aperture is required, and the difficulty and cost of engineering implementation are both high. How to achieve long-distance tracking of active targets under the condition of low power or small aperture has always been an important research topic in the field of secondary radar signal processing.

[0003] Traditional secondary radar tracking targets mainly adopts single-pulse processing. In single-pulse processing, the radar transmits a pulse signal, receives the echo signal reflected or responded by the target, and extracts target information by processing a single pulse echo. This method has a simple processing flow and good real-time performance, but has obvious technical defects:

[0004] Firstly, the energy of a single pulse signal is limited. Under the conditions of long-distance detection or low-power transmission, the signal-to-noise ratio of the received signal is low. When the target distance is far or the signal propagation path loss is large, the received signal is easily overwhelmed by noise, resulting in a decrease in target detection probability or even missing detection. In order to ensure the detection performance, the system has to increase the transmission power or increase the antenna array aperture, which not only increases the power consumption and cost of the system, but also puts higher requirements on the design of the transmitter, limiting the application of the system in small and low-power scenarios.

[0005] Secondly, single-pulse processing cannot obtain the Doppler frequency information of the target; the Doppler frequency reflects the radial motion speed of the target relative to the radar and is an important parameter of the target motion state. In single-pulse processing, since there is only one pulse of information, the Doppler frequency cannot be extracted through the phase change between pulses, so the radial speed of the target cannot be directly measured. This causes significant performance loss in applications that require tracking and state estimation of moving targets. The lack of information in the speed dimension affects the smoothness and prediction accuracy of the target track, and may also cause target association errors in a multi-target scenario.

[0006] Thirdly, the anti-interference ability of single-pulse processing is weak. In a complex electromagnetic environment, various electromagnetic interferences, clutter and multipath effects can significantly degrade the signal quality. Single-pulse processing lacks the ability to suppress interference and is difficult to achieve reliable target detection in a strong interference background. In particular, in urban environments, mountainous areas and other scenarios with severe multipath effects, or in hostile environments with intentional interference, the performance of single-pulse processing will decrease dramatically.

[0007] In the field of secondary radar detection, for example, in the L-band high-altitude meteorological detection system, the transponder carried by the sounding balloon transmits a response signal to the ground radar, and the ground radar needs to process these response signals to obtain the position and motion information of the sounding balloon. The existing system usually adopts a monopulse processing method, which only uses a single response pulse for processing, and has all the defects of the monopulse processing method described above. In particular, during the process of the sounding balloon ascending and gradually increasing the distance, the signal-to-noise ratio of the response signal continues to decline, and the monopulse processing method is difficult to ensure the reliability and accuracy of the detection; further, since the Doppler velocity information cannot be obtained, the system cannot accurately estimate the radial velocity of the sounding balloon, affecting the accurate tracking of the balloon trajectory and the measurement accuracy of the high-altitude wind field.

[0008] It is worth noting that the primary radar system uses the scattering signal of the passive target for detection, and the transmission signal and the received signal have good phase correlation in a short time, so the multi-pulse coherent accumulation has been widely used in the primary radar system. However, there is an essential difference between the secondary radar system and the primary radar system: there is a frequency difference and an initial phase difference between the active target response signal received by the ground and the ground radar transmission signal, which results in the incoherence between the received signal and the transmission signal. This incoherence makes the multi-pulse accumulation method of the primary radar system cannot be directly applied to the secondary radar system.

[0009] Therefore, there is an urgent need to design a new multi-pulse response signal target tracking method, which significantly improves the signal-to-noise ratio under the premise of maintaining low transmission power or small aperture antenna array, and realizes the two-dimensional joint measurement of target distance and Doppler velocity, improves the reliability, accuracy and anti-interference ability of target detection, and meets the needs of modern radar systems in long-distance detection, low-power design and complex environment application. SUMMARY

[0010] The application discloses a target tracking method based on multi-pulse response signal coherent accumulation, which aims to solve the technical problems existing in the prior art. The application adopts the following technical scheme:

[0011] In an embodiment of the application, a target tracking method based on multi-pulse response signal coherent accumulation is disclosed, which comprises:

[0012] In the calibration mode, the active target is fixed at a known position, and a plurality of pulse response signals of a known data sequence transmitted by the active target are received, and the frequency difference and the initial phase difference between the response signal and the ground radar transmission signal are estimated;

[0013] In the formal working mode, a plurality of pulse response signals transmitted by the active target are received;

[0014] According to the frequency difference and the initial phase difference, frequency compensation and initial phase compensation are performed on the multiple pulse response signals in the formal working mode;

[0015] The compensated multiple pulse response signals are subjected to matched filtering processing to obtain distance dimension compression results of the pulses;

[0016] The distance dimension compression results are arranged according to the pulse sequence to form a fast-time-slow-time two-dimensional data matrix, wherein the fast time corresponds to the sampling time within a single pulse, and the slow time corresponds to the pulse repetition interval;

[0017] The fast-time-slow-time two-dimensional data matrix is subjected to Fourier transform processing in the slow time dimension to realize coherent accumulation of the multiple pulses and obtain distance-Doppler two-dimensional information;

[0018] The distance-Doppler two-dimensional information is subjected to peak value detection to determine the distance scale and the Doppler scale of the active target, and further obtain the distance and radial velocity of the active target.

[0019] As a preferred technical solution, the known data sequence includes alternately arranged first data packets and second data packets, and the data values carried by the first data packets are different from the data values carried by the second data packets.

[0020] As a preferred technical solution, in the step of estimating the frequency difference and the initial phase difference between the response signal and the ground radar transmission signal, the step includes:

[0021] The received multiple pulse response signals are subjected to frequency down-conversion and analog-to-digital conversion to obtain digitized baseband pulse signals;

[0022] The digitized baseband pulse signals are subjected to matched filtering processing to obtain distance dimension compression results of the pulses;

[0023] The distance dimension compression results are arranged according to the pulse sequence to form a fast-time-slow-time two-dimensional data matrix;

[0024] A data sequence in the slow time dimension corresponding to the fast time sampling point of the known position is extracted;

[0025] The data sequence is subjected to Fourier transform processing;

[0026] The frequency difference is determined by detecting the amplitude peak value position of the Fourier transform result;

[0027] The initial phase difference is determined by extracting the phase value corresponding to the amplitude peak value position.

[0028] As a preferred technical solution, the multiple pulse response signals are N pulse response signals periodically transmitted by the active target according to a fixed pulse repetition interval, wherein N≥2.

[0029] As a preferred technical solution, in the step of receiving a plurality of pulse response signals emitted by the active target, comprising:

[0030] Receiving the radio frequency pulse response signals emitted by the active target through the receiving antenna;

[0031] Down-converting and analog-to-digital converting the radio frequency pulse response signals to obtain digitized baseband pulse response signals.

[0032] As a preferred technical solution, in the step of performing matched filtering processing on the compensated plurality of pulse response signals to obtain the range dimension compression results of each pulse, comprising:

[0033] According to the modulation mode of the pulse response signals emitted by the active target, a reference signal matched with the transmitted signal waveform is constructed;

[0034] Convolution operation is performed on the compensated digitized baseband pulse response signals and the reference signal to obtain the range dimension compression results of each pulse.

[0035] As a preferred technical solution, the modulation mode is linear frequency modulation;

[0036] The reference signal is a time-reversed signal conjugated with the modulation waveform of the transmitted signal.

[0037] As a preferred technical solution, in the step of arranging the range dimension compression results according to the pulse order to form a fast-time-slow-time two-dimensional data matrix, comprising:

[0038] The range dimension compression results of the first pulse to the Nth pulse are arranged in turn as the first column to the Nth column or the first row to the Nth row of the two-dimensional data matrix.

[0039] As a preferred technical solution, the length of the fast-time dimension is the number M of sampling points after matched filtering of a single pulse response signal, and the length of the slow-time dimension is the number N of pulses;

[0040] The dimension of the two-dimensional data matrix is M×N or N×M.

[0041] As a preferred technical solution, in the step of performing Fourier transform processing on the slow-time dimension of the fast-time-slow-time two-dimensional data matrix to realize coherent accumulation of multiple pulses and obtain range-Doppler two-dimensional information, comprising:

[0042] Performing Fourier transform on the slow-time dimension data corresponding to each fast-time sampling point in the fast-time-slow-time two-dimensional data matrix to convert the slow-time domain data into Doppler domain data and obtain range-Doppler two-dimensional information.

[0043] As a preferred technical solution, in the step of performing Fourier transform processing on the slow time dimension of the fast time-slow time two-dimensional data matrix, realizing coherent accumulation of multiple pulses, and obtaining range-Doppler two-dimensional information, the step comprises:

[0044] The Fourier transform is performed on the slow time dimension data corresponding to each fast time sampling point in the fast time-slow time two-dimensional data matrix, and the fast Fourier transform algorithm is used to realize the Fourier transform;

[0045] The frequency resolution of the Doppler domain data is the ratio of the pulse repetition frequency to the number N of pulses.

[0046] As a preferred technical solution, in the step of performing peak value detection on the range-Doppler two-dimensional information, determining the range scale and the Doppler scale of the active target, and then obtaining the range and the radial velocity of the active target, the step comprises:

[0047] The amplitude peak value is searched in the range-Doppler two-dimensional information;

[0048] The range dimension coordinate corresponding to the amplitude peak value is determined as the range scale of the active target, and the Doppler dimension coordinate corresponding to the amplitude peak value is determined as the Doppler scale of the active target;

[0049] The range of the active target is determined according to the range scale, and the radial velocity of the active target is determined according to the Doppler scale.

[0050] An embodiment of the above application has the following advantages or beneficial effects:

[0051] The target tracking method based on coherent accumulation of multiple pulse response signals provided by the application solves the problem that the response signal and the transmitted signal are not coherent in the secondary radar system by estimating the frequency difference and the initial phase difference between the response signal and the transmitted signal in the calibration mode and performing corresponding compensation processing on multiple pulse response signals in the formal working mode, so that coherent accumulation of multiple pulses is realized. Compared with the traditional single pulse detection mode, the method uses the phase coherence of the compensated multiple pulses to realize coherent superposition of energy by performing Fourier transform on the slow time dimension, and theoretically can obtain signal-to-noise ratio gain proportional to the number of pulses, and is especially suitable for long-distance target tracking scenarios under low-power or small-aperture antenna conditions.

[0052] The application adopts a fast time-slow time two-dimensional data matrix processing mode, arranges the range dimension compression results of the pulses according to the pulse sequence, obtains range-Doppler two-dimensional information through Fourier transform on the slow time dimension, and thus extracts the range and the radial velocity of the target at the same time. This processing mode not only can improve the detection sensitivity, but also enriches the target motion information, and provides strong support for target identification and tracking. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments description, which form a part of the present application. The illustrative embodiments of the present application and their descriptions explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0054] Figure 1 The flow chart of the target tracking method based on the coherent accumulation of the multi-pulse response signals in a preferred embodiment disclosed by the embodiments of the present application;

[0055] Figure 2 The schematic diagram of the multiple pulse response signals of the known data sequence in a preferred embodiment disclosed by the embodiments of the present application;

[0056] Figure 3 The frequency domain form schematic diagram of the frequency shift keying combined with the linear frequency modulation spread spectrum in a preferred embodiment disclosed by the embodiments of the present application;

[0057] Figure 4 The flow chart of the target tracking method based on the coherent accumulation of the multi-pulse response signals in a specific embodiment disclosed by the embodiments of the present application;

[0058] Figure 5 The flow chart of the matched filtering in a preferred embodiment disclosed by the embodiments of the present application;

[0059] Figure 6 The flow chart of the multi-pulse slow time dimension FFT in a preferred embodiment disclosed by the embodiments of the present application;

[0060] Figure 7 The use scenario schematic diagram of the new L-band secondary wind measurement radar system in a preferred embodiment disclosed by the embodiments of the present application. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of the present application more clear, the following will combine the specific embodiments of the present application and the corresponding drawings to clearly and completely describe the technical solutions of the present application. In the description of the present application, it should be noted that the term "or" is generally used in the meaning of including "and / or", unless the content is explicitly indicated otherwise. In the description of the present application, the terms "first", "second" and the like are only used for distinguishing description, and cannot be understood as indicating or implying relative importance.

[0062] Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by the person of ordinary skill in the art without making creative labor, belong to the protection scope of the present application.

[0063] Existing secondary radar detection systems rely solely on single-pulse signals for target localization. The target's position is obtained through processing these single pulses. However, single-pulse signals have a low signal-to-noise ratio and are easily overwhelmed by noise, resulting in low communication sensitivity. To ensure communication, the system requires high transmission power. Furthermore, single-pulse signals lack the ability to measure Doppler frequencies, thus missing the target's velocity dimension information.

[0064] refer to Figure 1 To address the technical problems existing in the prior art, this invention provides a target tracking method based on coherent accumulation of multi-pulse response signals, which includes at least steps S110 to S170.

[0065] Step S110: In calibration mode, the active target is fixed at a known position, and multiple pulse response signals of a known data sequence transmitted by the active target are received. The frequency difference and initial phase difference between the response signal and the ground radar transmission signal are estimated.

[0066] like Figure 2 In a preferred embodiment, the known data sequence includes alternating first data packets and second data packets, wherein the data values ​​carried by the first data packets are different from those carried by the second data packets.

[0067] More preferably, the first data packet is a data packet consisting entirely of "1"s and the second data packet consists entirely of "0"s. This alternating data sequence is beneficial for providing stable signal characteristics during the calibration process and facilitates accurate estimation of frequency difference and initial phase difference.

[0068] In calibration mode, the active target is fixed at a known position relative to the ground radar station. This known position can be predetermined through precise measurement or other positioning methods, including information such as the target's distance, azimuth, and elevation relative to the radar station. The purpose of fixing the active target at a known position is to estimate the frequency difference and initial phase difference between the response signal and the ground radar's transmitted signal under known geometric conditions using signal processing methods. These parameters will be used for signal compensation in subsequent formal operating modes.

[0069] In a preferred embodiment, step S110 further includes the following sub-steps:

[0070] Step S111: Down-convert and analog-to-digital convert the received multiple pulse response signals to obtain digitized baseband pulse signals.

[0071] Specifically, the ground radar receiving system receives radio frequency pulse response signals transmitted by active targets through a receiving antenna. After the received radio frequency signal is amplified by low noise, it is mixed with the carrier signal generated by the local oscillator to achieve down-conversion operation, converting the radio frequency signal into an intermediate frequency signal or a baseband signal.

[0072] In one implementation, the down-conversion process includes in-phase and quadrature processing, where the signals are mixed with in-phase and quadrature carriers respectively to obtain dual-channel baseband signals. The down-converted signals are then filtered by a low-pass filter to remove high-frequency components, and then sampled and quantized by an analog-to-digital converter to obtain digitized baseband pulse signals.

[0073] Step S112: Perform matched filtering on the digitized baseband pulse signal to obtain the distance dimension compression result of each pulse.

[0074] Matched filtering is an optimal linear filtering method that maximizes the output signal-to-noise ratio. A reference signal matching the transmitted signal waveform is constructed based on the modulation scheme of the pulse response signal emitted by the active target.

[0075] In one implementation, when the pulse response signal uses linear frequency modulation, the reference signal is a time-reversed signal conjugate to the modulated waveform of the transmitted signal. By convolving the digitized baseband pulse signal with the reference signal, matched filtering is performed to obtain the compression result of each pulse in the distance dimension. After matched filtering, the signal energy is concentrated in the time domain, forming a distinct peak corresponding to the target's distance information.

[0076] Sub-step S113: Arrange the distance dimension compression results in pulse order to form a fast-time-slow-time two-dimensional data matrix.

[0077] In the received multiple pulse response signals, assuming a total of N pulses are received, these N pulses are periodically transmitted according to the pulse repetition interval. The distance dimension compression results of the first to Nth pulses are arranged sequentially to form a two-dimensional data matrix. One dimension of this two-dimensional data matrix corresponds to fast time, i.e., the sampling time within a single pulse, reflecting the target's distance information; the other dimension corresponds to slow time, i.e., the pulse repetition interval, reflecting the temporal evolution of the pulse sequence. The length of the fast time dimension is the number of sampling points after matched filtering of a single pulse signal, and the length of the slow time dimension is the number of pulses N. In this way, the one-dimensional pulse sequence is expanded into a two-dimensional data structure, laying the foundation for subsequent slow time dimension processing.

[0078] Step S114: Extract the data sequence of the fast-time sampling points corresponding to the known locations in the slow-time dimension.

[0079] Since the active target is fixed at a known location, which corresponds to a specific fast-time sampling point in the fast-time-slow-time two-dimensional data matrix, the corresponding fast-time delay can be calculated based on the known distance to the target, thereby determining the index of the corresponding fast-time sampling point. All data from this fast-time sampling point in the slow-time dimension are extracted to form a data sequence of length N. This data sequence reflects the signal characteristics of the fixed-position target within different pulse repetition periods, including the frequency difference and initial phase difference information between the response signal and the ground radar's transmitted signal.

[0080] Step S115: Perform Fourier transform processing on the data sequence.

[0081] The extracted slow-time-dimensional data sequence is subjected to a Fourier Transform (FFT) to convert the time-domain signal into a frequency-domain signal. The Fourier Transform decomposes the signal into different frequency components, allowing the frequency difference information to be presented in the form of peaks in the frequency domain. The resulting spectral data contains amplitude and phase information, providing a basis for subsequent estimation of the frequency difference and initial phase difference.

[0082] Sub-step S116 determines the frequency difference by detecting the position of the amplitude peak of the Fourier transform result.

[0083] In the spectrum obtained by Fourier transform, the maximum value of the search amplitude, i.e., the peak position, corresponds to the frequency difference between the response signal and the ground radar transmitted signal. Since there is a frequency deviation between the response signal and the transmitted signal, this frequency difference will manifest as a linear phase change in the slow time dimension. The Fourier transform can accurately identify this frequency offset.

[0084] Step S117: Determine the initial phase difference by extracting the phase value corresponding to the peak position of the amplitude.

[0085] After determining the position of the spectral peak corresponding to the frequency difference, the complex value at that position is extracted and its phase angle is calculated to obtain the initial phase difference. The initial phase difference reflects the phase shift between the response signal and the ground radar transmission signal at the initial moment.

[0086] In one implementation, when the system operates in dual-carrier mode, i.e., the active target transmits response signals on the first carrier frequency and the second carrier frequency respectively, the above processing needs to be performed separately for the two carrier frequencies.

[0087] Specifically, the slow time-dimensional data sequences corresponding to the two carriers are extracted respectively, and Fourier transform processing is performed on them respectively to obtain the first frequency difference, the first initial phase difference, the second frequency difference, and the second initial phase difference.

[0088] Step S120: In the normal operating mode, receive multiple pulse response signals transmitted by an active target.

[0089] In some implementations, step S120 includes: receiving radio frequency pulse response signals transmitted by an active target via a receiving antenna, wherein the multiple pulse response signals are N pulse response signals periodically transmitted by the active target at fixed pulse repetition intervals, where N≥2. Unlike the calibration mode, the position and motion state of the target are usually unknown in the formal operating mode, requiring detection and tracking through signal processing methods.

[0090] In some implementations, each pulse response signal carries a binary data value, and is preferably a signal obtained by mixing a baseband linear frequency modulated signal with a carrier signal. The frequency of the carrier signal switches between a first carrier frequency and a second carrier frequency according to the binary data value. The frequency interval between the first carrier frequency and the second carrier frequency is preferably not less than twice the preset bandwidth.

[0091] In some implementations, the frequency of the baseband linear frequency modulated signal changes linearly with time within a preset bandwidth. The baseband linear frequency modulated signal can be implemented using an up-sweep method, where the frequency increases linearly from low to high; or it can be implemented using a down-sweep method, where the frequency decreases linearly from high to low.

[0092] In some implementations, the baseband linear frequency modulated signal is represented in complex exponential form, with its real and imaginary parts corresponding to the in-phase and quadrature components, respectively. The phase of the complex exponential signal is a quadratic function of time, and the derivative of the phase with respect to time is the instantaneous frequency, exhibiting a linear relationship.

[0093] In some implementations, when the binary data value is a first logic value, a first carrier frequency is selected to generate a carrier signal; when the binary data value is a second logic value, a second carrier frequency is selected to generate a carrier signal. Optionally, the first logic value can be logic 0, the second logic value can be logic 1, or vice versa.

[0094] In some implementations, when the transmitter mixes the baseband linear frequency modulated (LFM) signal with the carrier signal, it performs a complex multiplication operation on the baseband LFM signal and the carrier signal to obtain a frequency shift keying (FSK) modulated LFM pulse response signal with a center frequency located at the carrier frequency. That is, the communication signal formed by several pulse response signals is a signal combining frequency shift keying and LFM spread spectrum modulation.

[0095] Figure 3The diagram illustrates the frequency domain configuration combining frequency shift keying (FSK) and linear frequency modulation (LFM) spread spectrum. When the binary data value is 0, the baseband LFM signal is shifted to the first carrier frequency f0, forming a LFM pulse response signal with a center frequency of f0 and a bandwidth of B. When the binary data value is 1, the baseband LFM signal is shifted to the second carrier frequency f1, forming a LFM pulse response signal with a center frequency of f1 and a bandwidth of B. The frequency interval between the first carrier frequency f0 and the second carrier frequency f1 is no less than twice the preset bandwidth B, ensuring sufficient spacing between the two signals in the frequency domain and avoiding spectral overlap.

[0096] In some implementations, N pulse response signals are transmitted sequentially in chronological order, with each pulse response signal occupying the duration of one pulse width. Adjacent pulses can be closely connected to form a continuous pulse train; alternatively, a certain guard interval can be set to allow the receiving end to perform pulse synchronization and boundary detection.

[0097] In some implementations, the aforementioned active target refers to a target object capable of actively emitting a pulse response signal. This invention is based on the principle of secondary radar detection. After receiving an interrogation signal emitted by a ground-based radar, the active target is triggered and emits a response signal. For example, in upper-air meteorological detection applications, the active target is a radiosonde transponder mounted on a radiosonde balloon. The response signal emitted by the radiosonde transponder is used by the receiving end to sense the position and motion status information of the radiosonde balloon. Through processing the response signal, the receiving end can achieve tracking and positioning of the radiosonde balloon.

[0098] In some implementations, it is necessary to receive radio frequency pulse response signals transmitted by an active target via a receiving antenna. The receiving antenna can be a single antenna element or an antenna array composed of multiple antenna elements arranged in a specific geometry. In a preferred embodiment, the receiving end includes multiple subarrays, each capable of independently receiving signals and forming a specific beam pattern. By receiving communication signals through multiple subarrays, multiple received signals are obtained.

[0099] In some implementations, the receiver needs to down-convert and analog-to-digital convert the radio frequency (RF) pulse response signal to obtain a digitized baseband pulse response signal. Specifically, the RF signal received by the receiver is first amplified by a low-noise amplifier to improve the signal-to-noise ratio in subsequent processing. The amplified RF signal is then fed into a down-conversion mixer, where it is mixed with a local carrier signal generated by a local oscillator. This frequency shift converts the RF signal into an intermediate frequency (IF) signal or directly into a baseband signal.

[0100] In some implementations, the receiving end performs carrier demodulation on the communication signal to obtain dual-channel baseband signals. Specifically, a local carrier signal corresponding to the first carrier frequency and the second carrier frequency is generated by a digitally controlled oscillator; the communication signal is mixed with the local carrier signal to obtain a first mixed signal and a second mixed signal; the first mixed signal and the second mixed signal are then low-pass filtered to obtain dual-channel baseband signals. This dual-carrier demodulation method can separate the information carried by different carrier frequencies into different signal channels, providing a basis for subsequent parallel processing.

[0101] In some implementations, downconversion is achieved by performing a complex multiplication operation between the radio frequency signal and the local carrier signal. The mixed signal is then subjected to a low-pass filter to remove high-frequency components and noise interference generated during the mixing process, while retaining the baseband signal components. The cutoff frequency of the low-pass filter is set according to the preset bandwidth of the baseband linear frequency modulated signal to ensure that the baseband signal can pass completely while high-frequency noise is effectively suppressed.

[0102] After obtaining the analog baseband signal, the signal is sampled and quantized by an analog-to-digital converter, converting the continuous analog signal into a discrete digital signal. Preferably, the sampling frequency should be no less than twice the signal bandwidth to avoid spectral aliasing.

[0103] In some implementations, the sampled digital signal includes in-phase and quadrature components, forming a complex digital baseband pulse response signal. The digitized baseband pulse response signal can be represented as a discrete-time sequence, providing input data for subsequent frequency compensation, initial phase compensation, and matched filtering. For N consecutively received pulse response signals, after down-conversion and analog-to-digital conversion, N sets of digital baseband pulse response signal sequences are obtained, which are stored sequentially according to the pulse reception time order.

[0104] In a preferred embodiment, digital beamforming processing is performed on the dual baseband signals to obtain sum beam data. Specifically, sum beam data is obtained by weighted synthesis of the dual baseband signals corresponding to multiple received signals. Digital beamforming technology can perform digital domain weighting processing on baseband signals from different subarrays, thereby enhancing the coherent superposition of signals from the target direction while suppressing interference signals from other directions, thus improving the signal-to-noise ratio.

[0105] Step S130: Based on the frequency difference and initial phase difference, perform frequency compensation and initial phase compensation on the multiple pulse response signals received in the formal working mode.

[0106] The frequency difference and initial phase difference estimated in the calibration mode are used to compensate the received pulse response signal in the normal operating mode. The purpose of frequency compensation and initial phase compensation is to eliminate the frequency and phase deviations between the response signal and the ground radar transmission signal, so that the multiple pulse signals after compensation have phase coherence, thereby enabling effective coherent accumulation.

[0107] Specifically, frequency compensation refers to applying a phase correction corresponding to the estimated frequency difference to each pulse response signal. Since the frequency difference causes a linear phase change in the pulse sequence in the slow time dimension, this effect can be counteracted by applying an opposite phase change. In implementation, a corresponding phase compensation amount is applied to the nth pulse (n from 1 to N), which is related to the pulse number n and the estimated frequency difference.

[0108] Initial phase compensation refers to applying a uniform phase correction to all pulse response signals to eliminate the initial phase offset. The initial phase can be aligned by applying a phase value that is equal in magnitude but opposite in sign to the estimated initial phase difference.

[0109] Through frequency compensation and initial phase compensation, multiple pulse response signals that were originally non-coherent due to the difference in oscillator frequency and phase are transformed into coherent signals, creating conditions for subsequent coherent accumulation.

[0110] Step S140: Perform matched filtering on the compensated multiple pulse response signals to obtain the distance dimension compression result of each pulse.

[0111] In a preferred embodiment, step S140 includes: constructing a reference signal matching the waveform of the transmitted signal based on the modulation scheme of the pulse response signal transmitted by the active target; and performing a convolution operation between the digitized baseband pulse response signal (after frequency compensation and initial phase compensation) and the reference signal to obtain the range dimension compression result of each pulse. The modulation scheme is linear frequency modulation; the reference signal is a time-reversed signal conjugate to the modulation waveform of the transmitted signal.

[0112] In a preferred embodiment, the frequency of the linear frequency modulated signal changes linearly with time. Through matched filtering, the received wide pulse response signal can be compressed into a narrow pulse, thereby achieving high range resolution while maintaining transmission energy.

[0113] In some implementations, the construction of the reference signal needs to be designed according to the specific parameters of the transmitted signal. For linear frequency modulated signals, the reference signal should have the same frequency modulation bandwidth and pulse width as the transmitted signal, but the frequency change direction is opposite.

[0114] In some implementations, convolution operations can be performed directly in the time domain or by multiplying in the frequency domain.

[0115] In some implementations, a Fast Fourier Transform (FFT) is used to achieve matched filtering. The specific process includes: performing FFT on the compensated received signal and the reference signal respectively to obtain frequency domain representations; multiplying the two signals in the frequency domain using complex numbers; and performing an inverse FFT on the product to obtain the time-domain matched filter output.

[0116] In some implementations, the output of the matched filter is called the range compression result, where the peak position corresponds to the target's range information. Since the linear frequency modulated signal is compressed into a narrow pulse after matched filtering, the position of the peak reflects the time delay of the target echo, and thus the distance between the target and the receiver can be calculated.

[0117] In some implementations, the distance dimension compression result of each pulse refers to multiple sets of output sequences obtained after performing matched filtering on multiple pulse response signals respectively.

[0118] In a preferred embodiment, for signals modulated by a combination of frequency shift keying (FSK) and linear frequency modulation (LFM), matched filtering processing needs to be performed on the dual baseband signals separately. Specifically, corresponding reference signals are constructed for the dual baseband signals after frequency compensation and initial phase compensation, and matched filtering operations are performed on them separately. The matched filtering results of the two signals can be further synthesized to improve the overall signal-to-noise ratio and processing gain.

[0119] Step S150: Arrange the distance dimension compression results according to the pulse order to form a fast-time-slow-time two-dimensional data matrix, where the fast time corresponds to the sampling time within a single pulse and the slow time corresponds to the pulse repetition interval.

[0120] In a preferred embodiment, step S150 includes: arranging the distance dimension compression results of the first pulse to the Nth pulse sequentially into the first column to the Nth column, or the first row to the Nth row of a two-dimensional data matrix.

[0121] Preferably, the length of the time dimension is M, which is the number of sampling points M after matched filtering of a single pulse response signal, and the length of the slow time dimension is N, which is the number of pulses; the dimension of the two-dimensional data matrix is ​​M×N or N×M.

[0122] Specifically, in radar signal processing, fast time and slow time are two important time concepts. Fast time refers to the time variation within a single pulse, corresponding to the round-trip time delay of the electromagnetic wave from transmission to reception, reflecting the target's range information. Slow time refers to the time interval between different pulses, corresponding to the pulse repetition interval, reflecting the target's motion state within the observation time. By organizing the processing results of multiple pulses into a two-dimensional matrix in chronological order, the target can be analyzed simultaneously in both the range and velocity dimensions.

[0123] In some implementations, the length of the fast time dimension is the number of sampling points after matched filtering of a single pulse response signal, and the length of the slow time dimension is the number of pulses. The dimensions of the two-dimensional data matrix can be either fast time dimension first and slow time dimension second, or slow time dimension first and fast time dimension second, depending on the convenience of subsequent processing. In a preferred implementation, the distance dimension compression result of each pulse is used as a column of the matrix, so that each row of the matrix corresponds to the observation value of the same distance unit at different pulse times.

[0124] In some implementations, the resulting two-dimensional data matrix is ​​preserved in complex form, with each element in the matrix containing amplitude and phase information.

[0125] Step S160: Perform a slow-time dimension Fourier transform on the fast-time-slow-time two-dimensional data matrix to achieve coherent accumulation of multi-pulse data and obtain range-Doppler two-dimensional information.

[0126] In a preferred embodiment, step S140 includes: performing a Fourier transform on the slow-time dimension data corresponding to each fast-time sampling point in the fast-time-slow-time two-dimensional data matrix, converting the slow-time domain data into Doppler domain data, and obtaining distance-Doppler two-dimensional information. The frequency resolution of the Doppler domain data is the ratio of the pulse repetition frequency to the number of pulses N.

[0127] Specifically, the Doppler effect refers to the change in the frequency of the wave received by an observer when there is relative motion between the wave source and the observer. In a radar system, if the target has a radial velocity relative to the receiver, the carrier frequency of the reflected echo will experience a Doppler shift. By coherently processing the echo signals of multiple pulses, this Doppler shift can be detected and estimated, and thus the radial velocity of the target can be calculated.

[0128] In some implementations, a fast Fourier transform is performed on each row of the two-dimensional data matrix to obtain the Doppler spectrum of the corresponding distance cell.

[0129] In some implementations, slow-time Fourier transforms enable coherent accumulation of multiple pulses. Coherent accumulation refers to the phase-coherent superposition of the echo signals from multiple pulses, which enhances the accumulated signal energy from the same target while suppressing random noise due to its irregular phase variation. The processing gain of coherent accumulation is proportional to the number of pulses; the more pulses, the more significant the improvement in signal-to-noise ratio and the stronger the target detection capability.

[0130] In a preferred embodiment, for signals modulated using a combination of frequency shift keying (FSK) and linear frequency modulation (LFM), it is necessary to form fast-time and slow-time two-dimensional data matrices for each of the two baseband signals, and then perform slow-time Fourier transform processing on each. The range-Doppler information obtained after processing the two signals can be used for energy synthesis or coherent synthesis to obtain a higher signal-to-noise ratio and more accurate target parameter estimation.

[0131] Step S170: Peak detection is performed on the range-Doppler two-dimensional information to determine the range scale and Doppler scale of the active target, thereby obtaining the range and radial velocity of the active target.

[0132] In a preferred embodiment, step S150 includes: searching for amplitude peaks in the range-Doppler two-dimensional information; determining the range dimension coordinates corresponding to the amplitude peaks as the range scale of the active target, and determining the Doppler dimension coordinates corresponding to the amplitude peaks as the Doppler scale of the active target; determining the range of the active target based on the range scale, and determining the radial velocity of the active target based on the Doppler scale.

[0133] In some implementations, peak detection first requires amplitude calculation of the range-Doppler two-dimensional information. Since the data after Fourier transform is in complex form, containing real and imaginary parts, its magnitude needs to be calculated to obtain the amplitude information. The amplitude information reflects the energy intensity of each range-Doppler cell; locations with high energy intensity may correspond to the presence of a target.

[0134] In some implementations, the search for amplitude peaks can employ a global search or a local search strategy.

[0135] In some implementations, to improve detection reliability, peak detection needs to be combined with threshold decision. The threshold can be set to a fixed value or adaptively adjusted according to the background noise level. Only when the detected peak value exceeds the set threshold is it considered a valid target. The threshold setting needs to balance the detection probability and the false alarm probability. If the threshold is too low, it will lead to an increase in false alarms, while if the threshold is too high, it may miss weak targets.

[0136] In some implementations, the range coordinates and Doppler coordinates corresponding to the detected amplitude peaks are referred to as the range scale and the Doppler scale, respectively. The range scale is an integer index representing the target's position in the range array; the Doppler scale is also an integer index representing the target's position in the Doppler frequency array. These scale values ​​are discrete numerical representations and require further conversion to obtain physically meaningful range and velocity values.

[0137] In some implementations, determining the distance to an active target based on a distance scale requires considering the sampling rate and signal propagation speed; determining the radial velocity of an active target based on a Doppler scale requires considering the Doppler frequency resolution and carrier frequency. Specifically, by multiplying the distance scale by the physical size of the distance cell, an estimate of the target's distance relative to the receiver can be obtained. By converting the Doppler scale to the Doppler frequency and then utilizing the Doppler effect principle, the target's radial velocity can be calculated.

[0138] In a preferred embodiment, for signals modulated by a combination of frequency shift keying and linear frequency modulation, the distance-Doppler information of the two signals can be peak detected separately, and then the detection results can be fused.

[0139] In some implementations, the detected range and radial velocity of active targets can be used for subsequent applications such as target tracking, trajectory prediction, and threat assessment. By using detection results from multiple consecutive frames, a target motion model can be established to predict the target's future position. For multi-target scenarios, data association is also required to match targets detected at different times, forming continuous tracks.

[0140] refer to Figure 4 — Figure 6 In one specific embodiment of the present invention, a target tracking method based on coherent accumulation of multi-pulse response signals is provided. The method includes a calibration working mode and a formal working mode. The calibration working mode includes steps S210 to S2110, and the formal working mode includes steps S310 to S3100.

[0141] Step S210: In calibration mode, the active target is fixed at a known position and multiple pulse response signals with known data sequences are transmitted.

[0142] Step S220: The N subarrays of the secondary radar receive signals transmitted by the active target, and perform orthogonal sampling on the received signals at a sampling frequency of... The sampled data is , , … .

[0143] Step S230: Two discrete-time complex exponential signals are generated using a digitally controlled oscillator (NCO), including... and The expressions for the two are as follows:

[0144]

[0145]

[0146] in, Sampling rate, and These are the modulation frequencies for "0" and "1" of the communication signal, respectively.

[0147] Step S240, discrete received signal , , … respectively with and Digital mixing is performed to obtain two baseband signals. , , … and , , … Their mathematical expressions are as follows:

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156] Step S250: Configure a low-pass filter for the baseband signal. , , … and , , … Low-pass filtering is performed separately to obtain new baseband signals. , , … and , , … .

[0157] Step S260, for The baseband signal of each subarray , , … and , , … Digital beamforming (DBF) is performed to combine sampled data from multiple subarrays with beam data. , .

[0158] Step S270, Pair beam data , Perform matched filtering to obtain , .

[0159] Step S280: Process the results of the matched filtering respectively. and Perform multi-pulse slow-time dimension FFT processing.

[0160] Step S290, based on the pulse width T and sampling frequency Calculate the number of sampling points for each pulse. The result of matched filtering , Reorder the pulses, starting from the first pulse, every... Take one point from each point, and keep taking points until... There are points, among which This represents the number of pulses in one frame of data. Finally, we obtain a... Matrix A, with For example, the resulting matrix is ​​as follows:

[0161]

[0162] Step S2100: Calculate the sampling points corresponding to the known target locations. Extract the data corresponding to "0" and "1" in the matrix. Row data, denoted as , ,right and Perform FFT processing separately to obtain and .

[0163] Step S2110, find and The positions of the maximum amplitude are respectively and Then frequency difference , Initial phase difference , ,in, This indicates taking the phase.

[0164] Step S310, switch to normal operating mode, secondary radar Each subarray receives a signal transmitted from an active target and performs orthogonal sampling on the received signal at a sampling frequency of [frequency missing]. The sampled data is , , … .

[0165] Step S320: Two discrete-time complex exponential signals are generated using a digitally controlled oscillator (NCO), including... and The expressions for the two are as follows:

[0166]

[0167]

[0168] in, Sampling rate, and These are the modulation frequencies for "0" and "1" of the communication signal, respectively.

[0169] Step S330, discrete received signal , , … respectively with and Digital mixing is performed to obtain two baseband signals. , , … and , , … Their mathematical expressions are as follows:

[0170]

[0171]

[0172]

[0173]

[0174]

[0175]

[0176]

[0177]

[0178] Step S340: Configure a low-pass filter for the baseband signal. , , … and , , … Low-pass filtering is performed separately to obtain new baseband signals. , , … and , , … .

[0179] Step S350, for The baseband signal of each subarray , , … and , , … Digital beamforming (DBF) is performed to combine sampled data from multiple subarrays with beam data. , .

[0180] Step S360: Based on the frequency difference and the initial phase difference, respectively... and Frequency compensation and initial phase compensation are performed. The process of frequency compensation and initial phase compensation can be represented as follows:

[0181]

[0182]

[0183] Step S370, adjust beam data , Perform matched filtering to obtain , .

[0184] refer to Figure 5 For a signal The preferred method for matched filtering is as described in steps S371 to S373:

[0185] Step S371: Generate the reference signal for matched filtering. And it is discretely sampled, with a sampling frequency of This yields a discrete reference signal. The reference signal is the baseband linear frequency modulated signal in the transmitted signal, and its mathematical expression is:

[0186]

[0187] in, The pulse width. This represents the frequency modulation slope.

[0188] Step S372, for the compensated signal and reference signal Perform Fast Fourier Transform (FFT) processing on each signal, with the FFT length K determined by the signal. The number of sampling points is determined by taking a power greater than the number of sampling points to obtain the frequency domain signal. and .

[0189] Step S373, and The conjugate multiplication is performed, and the result is then subjected to inverse fast Fourier transform (IFFT) to restore the time-domain signal. This completes the matched filtering.

[0190] Step S380: The results of frequency compensation, initial phase compensation, and matched filtering of the first carrier and the second carrier, respectively. and Perform multi-pulse slow-time dimension FFT processing.

[0191] like Figure 6 Step S380 further includes steps S381 to S382.

[0192] Step S381, based on the pulse width T and sampling frequency Calculate the number of sampling points for each pulse. The result of matched filtering , Reorder the pulses, starting from the first pulse, every... Take one point from each point, and keep taking points until... There are points, among which This represents the number of pulses in one frame of data. Finally, we obtain a... Matrix A, with For example, the resulting matrix is ​​as follows:

[0193]

[0194] Step S382: Perform a Fast Fourier Transform (FFT) on each row of the matrix. The FFT length is... greater than A power of two yields a Matrix B.

[0195] Step S390, respectively for and The corresponding matrix B is used for constant false alarm rate (CFAR) detection, and each point in the matrix is ​​compared with its protection scale. outside The signal-to-noise ratio (SNR) is calculated by comparing the average values ​​of each point with the decision threshold. If the SNR exceeds the decision threshold, the target is detected, and the row coordinates at this point are recorded as the distance scale. , Column coordinates are used as Doppler scale. , and the corresponding signal-to-noise ratio and .

[0196] Step S3100: The two distance scales and the Doppler scale are fused together using the following formula:

[0197]

[0198]

[0199] Based on the target tracking method based on coherent accumulation of multi-pulse response signals provided in the above embodiments, the multi-pulse joint processing technology can successfully detect the target through the accumulation of multiple pulses even under low signal-to-noise ratio conditions, thereby reducing the transmission power requirement and improving the communication sensitivity.

[0200] Assuming the power of a single pulse is The power of the noise is Then the signal-to-noise ratio of the single-pulse response signal of the existing secondary radar detection system is: This invention performs coherent accumulation of multiple pulses, assuming the number of pulses is... Since the pulse response signals are coherent, therefore The amplitudes of the pulse response signals are linearly added together, increasing... This doubles the power output, thus increasing the overall efficiency. times, for The noise is incoherent, and its amplitude is not linearly added, so the noise power only increases by a factor of N. Therefore, the signal-to-noise ratio of multi-pulse coherent accumulation is Compared to a single-pulse response signal, the signal-to-noise ratio is improved. For the same signal-to-noise ratio requirement, the transmit power pressure at the transmitting end has decreased by a factor of [number missing]. times.

[0201] The target tracking method based on the coherent accumulation of multi-pulse response signals provided in the above embodiments can be preferably applied to a novel L-band secondary wind measurement radar system. Based on the response signals transmitted by the ground radar and the transponder mounted on the high-altitude sounding balloon, the high-altitude sounding balloon can be located and tracked.

[0202] refer to Figure 7 The new L-band secondary wind measurement radar system mainly consists of two parts: a ground radar and a radiosonde. The ground radar can track the radiosonde balloon and send radiosonde codes. The transponder on the radiosonde sends out response signals carrying temperature, humidity, and air pressure information. Based on the time of the received response signal, the distance between the radiosonde and the radar can be calculated. By decoding the response signal, meteorological information such as temperature, humidity, and air pressure emitted by the radiosonde can be obtained.

[0203] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of this application. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of this application. All such changes and modifications are intended to be included within the scope of this application as claimed in the appended claims.

[0204] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0205] Similarly, it should be understood that, in order to streamline this application and aid in understanding one or more of the various inventive aspects, features of this application may sometimes be grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of this application. However, this approach should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with features fewer than all features of a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0206] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature serving the same, equivalent, or similar purpose.

Claims

1. A target tracking method based on coherent accumulation of multi-pulse response signals, characterized in that, The method includes: In calibration mode, the active target is fixed at a known position, and multiple pulse response signals of a known data sequence transmitted by the active target are received. The frequency difference and initial phase difference between the response signal and the ground radar transmission signal are estimated. In normal operating mode, it receives multiple pulse response signals transmitted by an active target; Based on the frequency difference and the initial phase difference, frequency compensation and initial phase compensation are performed on the multiple pulse response signals in the formal working mode; The compensated pulse response signals are subjected to matched filtering to obtain the distance dimension compression result of each pulse. The distance dimension compression results are arranged in pulse order to form a fast-time-slow-time two-dimensional data matrix, where fast time corresponds to the sampling time within a single pulse and slow time corresponds to the pulse repetition interval. The fast-time-slow-time two-dimensional data matrix is ​​subjected to a slow-time dimension Fourier transform to achieve coherent accumulation of multiple pulses and obtain range-Doppler two-dimensional information. Peak detection is performed on the range-Doppler two-dimensional information to determine the range scale and Doppler scale of the active target, thereby obtaining the range and radial velocity of the active target.

2. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 1, characterized in that, The known data sequence includes alternating first data packets and second data packets, wherein the data values ​​carried by the first data packets are different from those carried by the second data packets.

3. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 1, characterized in that, The step of estimating the frequency difference and initial phase difference between the response signal and the ground radar transmitted signal includes: The received multiple pulse response signals are down-converted and analog-to-digital converted to obtain digitized baseband pulse signals; The digitized baseband pulse signal is subjected to matched filtering to obtain the distance dimension compression result of each pulse; The distance dimension compression results are arranged in pulse order to form a fast-time-slow-time two-dimensional data matrix; Extract the data sequence of the fast-time sampling points corresponding to the known locations in the slow-time dimension; Perform Fourier transform processing on the data sequence; The frequency difference is determined by detecting the position of the amplitude peak of the Fourier transform result; The initial phase difference is determined by extracting the phase value corresponding to the position of the amplitude peak.

4. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 1, characterized in that, The plurality of pulse response signals are N pulse response signals periodically emitted by the active target at fixed pulse repetition intervals, where N≥2.

5. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 4, characterized in that, The step of receiving multiple pulse response signals transmitted by an active target includes: The radio frequency pulse response signal transmitted by the active target is received by the receiving antenna; The radio frequency pulse response signal is down-converted and analog-to-digital converted to obtain a digitized baseband pulse response signal.

6. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 5, characterized in that, The step of performing matched filtering on the compensated multiple pulse response signals to obtain the distance dimension compression result of each pulse includes: Based on the modulation method of the pulse response signal transmitted by the active target, a reference signal matching the waveform of the transmitted signal is constructed; The compensated digitized baseband pulse response signal is convolved with the reference signal to obtain the distance dimension compression result of each pulse.

7. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 6, characterized in that, The modulation method is linear frequency modulation; The reference signal is a time-reversed signal that is conjugate to the modulation waveform of the transmitted signal.

8. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 6, characterized in that, The step of arranging the distance dimension compression results in pulse order to form a fast-time-slow-time two-dimensional data matrix includes: The distance dimension compression results of the first to Nth pulses are arranged sequentially into the first to Nth columns, or the first to Nth rows, of the two-dimensional data matrix.

9. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 8, characterized in that, The length of the fast time dimension is M, which is the number of sampling points M after a single pulse response signal is matched and filtered, and the length of the slow time dimension is N, which is the number of pulses. The dimensions of the two-dimensional data matrix are M×N or N×M.

10. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 1, characterized in that, The step of performing a slow-time dimension Fourier transform on the fast-time-slow-time two-dimensional data matrix to achieve coherent accumulation of multiple pulses and obtain range-Doppler two-dimensional information includes: Perform a Fourier transform on the slow-time dimension data corresponding to each fast-time sampling point in the fast-time-slow-time two-dimensional data matrix to convert the slow-time domain data into Doppler domain data, thereby obtaining the distance-Doppler two-dimensional information.

11. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 10, characterized in that, The step of performing a slow-time dimension Fourier transform on the fast-time-slow-time two-dimensional data matrix to achieve coherent accumulation of multiple pulses and obtain range-Doppler two-dimensional information includes: The Fourier transform of the slow-time dimension data corresponding to each fast-time sampling point in the fast-time-slow-time two-dimensional data matrix is ​​performed using the Fast Fourier Transform algorithm. The frequency resolution of the Doppler domain data is the ratio of the pulse repetition frequency to the number of pulses N.

12. The target tracking method based on coherent accumulation of multi-pulse response signals according to claim 10, characterized in that, The step of performing peak detection on the range-Doppler two-dimensional information to determine the range and Doppler scales of the active target, and then obtaining the range and radial velocity of the active target, includes: Search for amplitude peaks in the distance-Doppler two-dimensional information; The distance coordinates corresponding to the amplitude peak are determined as the distance scale of the active target, and the Doppler coordinates corresponding to the amplitude peak are determined as the Doppler scale of the active target; The distance to the active target is determined according to the distance scale, and the radial velocity of the active target is determined according to the Doppler scale.

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