A method and apparatus for processing echoes of uniformly accelerated moving targets and estimating their motion parameters.

Abstract

This invention discloses a method and apparatus for processing echoes and estimating motion parameters of uniformly accelerated moving targets. The method includes: acquiring the frequency-coded target echo signal of a uniformly accelerated moving target; performing baseband echo processing to obtain a pulse-compressed echo; performing range compensation and frequency domain transformation processing to obtain a fast-time Fourier transform echo; performing second-order non-standard Keystone transform processing to obtain a second-order non-standard transform signal; performing acceleration estimation and compensation processing to obtain a compensated echo; performing first-order non-standard Keystone transform processing to obtain a first-order non-standard transform signal; performing echo coherent accumulation processing to obtain a coherently accumulated echo; and performing motion parameter estimation to obtain motion parameter estimation results, including the target's initial range and target velocity. This invention achieves echo processing and motion parameter estimation, improves estimation accuracy, and reduces the computational load. This invention can be widely applied in the field of radar signal processing technology.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and in particular to a method and apparatus for processing echoes of uniformly accelerated moving targets and estimating motion parameters. Background Technology

[0002] Radar, as a radio detection device, plays a crucial role in target detection. To identify the motion state of uniformly accelerating targets during detection, radar systems are designed with frequency-coded integrated detection and identification waveforms to achieve integrated detection and identification functions. Traditional detection and identification methods process target echoes using compressed sensing algorithms to estimate target motion parameters. However, the carrier frequency of the frequency-coded signal constantly changes and there is a range-gate problem, resulting in a large computational load for echo processing and low accuracy in motion parameter estimation.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] This invention provides a method and apparatus for processing echoes of uniformly accelerated moving targets and estimating motion parameters, which effectively improves estimation accuracy and reduces the amount of computation.

[0005] On one hand, embodiments of the present invention provide a method for processing echoes of uniformly accelerated moving targets and estimating motion parameters, including the following steps:

[0006] Acquire the frequency-encoded target echo signal of a uniformly accelerated target;

[0007] The frequency-encoded signal target echo is subjected to baseband echo processing to obtain the pulse-compressed echo;

[0008] The pulse-compressed echo is subjected to distance compensation and frequency domain transformation to obtain the echo after fast time Fourier transform.

[0009] The echo after the fast time Fourier transform is processed by a second-order non-standard Keystone transform to obtain a second-order non-standard transformed signal.

[0010] Based on the second-order non-standard transform signal and the echo after the fast-time Fourier transform, acceleration estimation and compensation processing are performed to obtain the compensated echo.

[0011] The compensated echo is subjected to a first-order non-standard Keystone transform to obtain a first-order non-standard transformed signal.

[0012] The first-order non-standard transformed signal is subjected to echo coherent accumulation processing to obtain the echo after coherent accumulation.

[0013] Based on the echo after coherent accumulation, motion parameters are estimated to obtain motion parameter estimation results, which include the target's initial distance and target velocity.

[0014] In some embodiments, the step of performing baseband echo processing on the target echo of the frequency-coded signal to obtain the pulse-compressed echo includes:

[0015] The frequency-coded signal target echo is subjected to down-conversion low-pass filtering to obtain the baseband echo. The down-conversion low-pass filtering is used to eliminate the high-frequency carrier frequency component in the frequency-coded signal target echo.

[0016] The baseband echo is subjected to frequency domain pulse compression along a fast time path to obtain the pulse-compressed echo.

[0017] In some embodiments, performing distance compensation and frequency domain transformation processing on the pulse-compressed echo to obtain the echo after fast-time Fourier transform includes:

[0018] The pulse-compressed echo is subjected to distance compensation processing to obtain a distance-compensated echo. The distance compensation processing is used to eliminate the phase term in the pulse-compressed echo.

[0019] Based on the correspondence of fast-time sampling points, the distance-compensated echo is subjected to a Fourier transform along the fast time path to obtain the echo after the fast-time Fourier transform.

[0020] In some embodiments, performing a second-order non-standard Keystone transform on the echo after the fast-time Fourier transform to obtain a second-order non-standard transformed signal includes:

[0021] Based on the imaginary unit, reference frequency, frequency jump interval, frequency coding sequence, target radial acceleration, wavelength, and slow time, construct the first fast time frequency-slow time coupling term;

[0022] The first fast-time frequency and slow-time coupling term are decoupled to obtain the first decoupled signal;

[0023] Calculate the first virtual slow time based on the first decoupling signal;

[0024] The second-order non-standard transform signal is calculated based on the first virtual slow time and the echo after the fast-time Fourier transform.

[0025] In some embodiments, the step of performing acceleration estimation and compensation processing based on the second-order non-standard transform signal and the echo after the fast-time Fourier transform to obtain a compensated echo includes:

[0026] Define the acceleration compensation function;

[0027] Calculate the acceleration estimate based on the acceleration compensation function and the second-order non-standard transformation signal;

[0028] Based on the acceleration estimate, a fast-time Fourier compensation function is constructed;

[0029] The echo after the fast-time Fourier transform is compensated based on the fast-time Fourier compensation function and the acceleration estimate to obtain the compensated echo.

[0030] In some embodiments, performing a first-order non-standard Keystone transform on the compensated echo to obtain a first-order non-standard transformed signal includes:

[0031] Based on the imaginary unit, target radial velocity, reference frequency, frequency jump interval, frequency coding sequence, wavelength, and slow time, construct a second fast time frequency-slow time coupling term;

[0032] The second fast-time frequency and slow-time coupling term are decoupled to obtain the second decoupled signal;

[0033] Calculate the second virtual slow time based on the second decoupling signal;

[0034] The first-order non-standard transform signal is calculated based on the second virtual slow time and the compensated echo.

[0035] In some embodiments, the echo coherent accumulation processing of the first-order non-standard transformed signal to obtain the coherently accumulated echo includes:

[0036] The first-order non-standard transformed signal is subjected to inverse Fourier transform along the fast time frequency to obtain the echo after target range migration correction;

[0037] The echo after target distance migration correction is subjected to Fourier transform along virtual slow time to obtain the echo after coherent accumulation.

[0038] In some embodiments, the expression for the echo after coherent accumulation is:

[0039]

[0040] In the formula, The echo after coherent accumulation, where t is the fast time and f is the fast time. b For virtual slow time frequency, T p Let be the pulse width of the linear frequency modulated signal, c be the speed of light, B be the bandwidth of the linear frequency modulated signal, R0 be the initial radial distance of the target, M be the number of coherent accumulations, and T be... r λ is the pulse repetition period, v0 is the target radial velocity, and λ is the wavelength.

[0041] On the other hand, embodiments of the present invention provide a device for processing echoes of uniformly accelerated moving targets and estimating motion parameters, comprising:

[0042] The first module is used to acquire the frequency-coded target echo signal of a uniformly accelerated target.

[0043] The second module is used to perform baseband echo processing on the target echo of the frequency-coded signal to obtain the pulse-compressed echo.

[0044] The third module is used to perform distance compensation and frequency domain transformation processing on the pulse-compressed echo to obtain the echo after fast time Fourier transform.

[0045] The fourth module is used to perform a second-order non-standard Keystone transform on the echo after the fast-time Fourier transform to obtain a second-order non-standard transformed signal.

[0046] The fifth module is used to perform acceleration estimation and compensation processing based on the second-order non-standard transform signal and the echo after the fast-time Fourier transform to obtain the compensated echo.

[0047] The sixth module is used to perform a first-order non-standard Keystone transform on the compensated echo to obtain a first-order non-standard transformed signal.

[0048] The seventh module is used to perform echo coherent accumulation processing on the first-order non-standard transformed signal to obtain the echo after coherent accumulation.

[0049] The eighth module is used to estimate motion parameters based on the echo after coherent accumulation, and obtain motion parameter estimation results, which include the target initial distance and the target velocity.

[0050] On the other hand, embodiments of the present invention provide a computer device, including:

[0051] At least one processor;

[0052] At least one memory for storing at least one program;

[0053] When the at least one program is executed by the at least one processor, the at least one processor implements the method.

[0054] On the other hand, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described thereon.

[0055] The beneficial effects of this invention are as follows:

[0056] This invention first acquires the frequency-coded target echo signal of a uniformly accelerated target. Baseband echo processing is then performed on the frequency-coded target echo signal to obtain a pulse-compressed echo. Next, range compensation and frequency domain transformation processing are performed on the pulse-compressed echo to obtain a fast-time Fourier transform echo. A second-order non-standard Keystone transform is then performed on the fast-time Fourier transform echo to obtain a second-order non-standard transform signal. Acceleration estimation and compensation processing are then performed based on the second-order non-standard transform signal and the fast-time Fourier transform echo to obtain a compensated echo. A first-order non-standard Keystone transform is then performed on the compensated echo to obtain a first-order non-standard transform signal. Echo coherent accumulation processing is then performed on the first-order non-standard transform signal to obtain a coherently accumulated echo. Finally, motion parameter estimation is performed based on the coherently accumulated echo to obtain the motion parameter estimation result. This achieves echo processing and motion parameter estimation, improving estimation accuracy and reducing computational load.

[0057] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description and the drawings. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 This is a flowchart of a method for processing echoes of uniformly accelerated moving targets and estimating motion parameters according to an embodiment of the present invention;

[0060] Figure 2 This is a schematic diagram of the echo result after coherent accumulation according to an embodiment of the present invention;

[0061] Figure 3 This is a schematic diagram of the overall process of echo processing and parameter estimation according to an embodiment of the present invention;

[0062] Figure 4 This is a schematic diagram of the structure of a device for processing echoes of uniformly accelerated moving targets and estimating motion parameters according to an embodiment of the present invention;

[0063] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0065] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0066] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0068] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0069] Non-standard Keystone Transform (NST) is an algorithm used in radar signal processing, primarily for correcting target range migration and improving the accuracy of radar target detection and localization. Its basic principle is to convert the received radar signal from the frequency domain to the Keystone spectrum, and then perform time migration correction to eliminate the effects of range migration.

[0070] The Fourier transform is a mathematical operation with wide applications in mathematics, physics, computer science, engineering, and other fields. It is a generalization of Fourier series and describes the amplitudes of sine or cosine functions of different frequencies contained within a function. Within a specific function space, the Fourier transform of a function possesses desirable properties, such as enabling the conversion between differentials and polynomial products, and between function convolutions and products. Therefore, it can be used to solve partial differential equations, address norm control, and prove inequalities.

[0071] In related technologies, radar, as a radio detection device, possesses advantages such as all-weather, all-time operation, and strong penetration capabilities, playing a crucial role in military, disaster relief, and civilian applications. In modern, technology-driven warfare, radar faces unprecedented and formidable threats. The rapid development of high-sensitivity radar signal interception technology has made most radars vulnerable to detection upon activation, increasing the likelihood of mission failure. Therefore, how to rapidly acquire battlefield intelligence while reducing the probability of friendly radar being detected and intercepted is a pressing issue. Identification Friend or Foe (IFF) is a series of actions undertaken by opposing sides in military operations to obtain information on the type, affiliation, threat level, and friend or foe status of targets on the battlefield in order to control the military's trajectory. With the transformation of military confrontation methods, especially the development of electronic warfare, information warfare, and cyber warfare, the requirements for target IFF are increasing daily. Currently, the overall trend of integrated development of military equipment is prominent and accelerating significantly. The close coupling of detection and identification tasks places higher demands on the integration of the two systems. To alleviate the problem of increasingly scarce spectrum resources, related technologies have proposed the concept of multi-functional integrated systems. With the advancement of electronic information technology, the differences between radar systems and communication systems are gradually diminishing, leading to widespread interest in integrated radar communication systems based on hardware and integrated signals. One effective method for establishing such systems is designing dual-function waveforms. Specifically, for dual-function waveforms where the primary function is radar and the secondary function is communication, time-division multiplexing, frequency-division multiplexing, and code-division multiplexing can achieve the desired result. However, such multiplexing still faces limitations in efficiency and resources for integrated detection and identification systems, making it difficult to fully meet the demands of integrated detection and identification.

[0072] Therefore, traditional methods have designed an integrated detection and identification waveform based on frequency coding. This waveform can embed identification information into the frequency-coded waveform transmitted by the radar through coding rules, thus truly realizing the sharing of detection and identification. The identification device at the target end receives the integrated signal transmitted by the radar, parses its coding rules, extracts the interrogation information from the radar end, generates a corresponding response frequency-coded signal based on the interrogation information, and forwards it. The radar receiver receives the target's scattered echo and the identification forwarded signal, and performs integrated processing, ultimately realizing the integration of detection and identification functions. However, unlike the commonly used single-frequency or linear frequency modulated signals, the frequency jumps of the frequency-coded signal bring difficulties to signal processing, and some commonly used signal processing methods are not applicable, posing challenges in target detection and parameter estimation. Since the target Doppler is related to radial velocity and wavelength, radar frequency jumps affect its continuity in slow time, thus making it impossible to use moving target detection (MTD) for coherent accumulation. For narrowband fixed-carrier-frequency radars, the target echo slow-time signal is approximately a single-frequency signal. For frequency-coded radars, due to the coupling of the coding frequency with the target range and motion parameters, the target echo slow-time signal is complex, making coherent accumulation impossible using Fast Fourier Transform (FFT) or Fractional Fourier Transform (FrFT). From the perspective of target detection, matched filtering is the optimal detection method for known signal forms. Frequency-coded radar target echoes can be interpreted as signals with partially known information (frequency coding is known, target range and motion parameters are unknown). Therefore, a "range-motion parameter" search interval can be set, and a corresponding matched signal can be constructed. By iteratively searching for the maximum correlation peak, coherent accumulation can be achieved. The drawback is the large computational cost of iterative search. These mainstream approaches typically combine various compressed sensing (CS) algorithms to sparsely reconstruct the target, and the constructed atoms are the aforementioned matched signals. Another approach for uniformly moving targets is to separate the echo slow-time signal into range and velocity terms, first compensating for the range term, and then performing a non-uniform Fast Fourier Transform (NUFFT) on the velocity term. However, neither of these approaches considers the range-gate problem that easily occurs with high-speed moving targets. To address this, the Keystone Transform (KT) has been proposed to correct target range migration, but the standard KT virtual slow-time construction is... The carrier frequency is fixed, while the carrier frequency of frequency coding is constantly changing. Therefore, the standard Keystone transform is not suitable for frequency-coded radar. A non-standard Keystone transform needs to be constructed for frequency-coded radar to correct target range migration.

[0073] In view of this, this embodiment addresses the needs of target detection and parameter estimation by performing two non-standard Keystone transformations at the radar receiver based on the characteristics of the frequency-coded signal. This achieves target range migration correction, thereby enabling effective coherent accumulation of the target echo. Furthermore, through a search compensation process, estimated values ​​of parameters such as the target's initial range, velocity, and acceleration are obtained. This achieves echo processing and motion parameter estimation, improving estimation accuracy and reducing the computational load.

[0074] This application provides a method for processing echoes of uniformly accelerated moving targets and estimating motion parameters, relating to the field of radar signal processing technology. This method can be applied to terminals, servers, or software running on either. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the method for processing echoes of uniformly accelerated moving targets and estimating motion parameters, but is not limited to the above forms.

[0075] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0076] The embodiments of this application will be explained in detail below with reference to the accompanying drawings:

[0077] Figure 1 This is an optional flowchart of a method for processing echoes of uniformly accelerated moving targets and estimating motion parameters provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S101 to S108.

[0078] Step S101: Obtain the frequency-encoded signal target echo of the uniformly accelerated target;

[0079] Step S102: Perform baseband echo processing on the frequency-coded signal target echo to obtain the pulse-compressed echo;

[0080] Step S103: Perform distance compensation and frequency domain transformation on the pulse-compressed echo to obtain the echo after fast time Fourier transform.

[0081] Step S104: Perform a second-order non-standard Keystone transform on the echo after the fast-time Fourier transform to obtain a second-order non-standard transform signal.

[0082] Step S105: Based on the second-order non-standard transform signal and the echo after fast-time Fourier transform, perform acceleration estimation and compensation processing to obtain the compensated echo.

[0083] Step S106: Perform a first-order non-standard Keystone transform on the compensated echo to obtain a first-order non-standard transformed signal;

[0084] Step S107: Perform echo coherent accumulation processing on the first-order non-standard transform signal to obtain the echo after coherent accumulation;

[0085] Step S108: Based on the echo after coherent accumulation, perform motion parameter estimation to obtain the motion parameter estimation results, which include the target's initial distance and target velocity.

[0086] Steps S101 to S108 as shown in the embodiments of this application realize echo processing and motion parameter estimation, improve estimation accuracy, and reduce processing computation.

[0087] In step S101 of some embodiments, the frequency-coded signal target echo of a uniformly accelerated moving target can be acquired by radar reception. The frequency-coded signal target echo of a uniformly accelerated moving target can also be acquired by other means, and is not limited thereto. For example, under narrowband conditions, the frequency-coded radar transmits a linear frequency modulation (LFM) pulse signal, and the radar receives the radio frequency echo of a uniformly accelerated moving point target, i.e., the frequency-coded signal target echo modulated by the LFM signal. The expression for the frequency-coded signal target echo is: In the formula, s R The target echo is a frequency-coded signal, where t is the fast time. m =mT r m = 0, 1, ..., M-1, where M is the number of coherent accumulations, and T r For the pulse repetition period, t m For slow time, rect[*] is the unit rectangular function, exp(*) is the exponential function, and T is the time interval. p Let R0 be the initial radial distance to the target, v0 be the radial velocity of the target, a0 be the radial acceleration of the target, and j be the imaginary unit. μ is the frequency modulation slope, B is the bandwidth of the linear frequency modulated signal, c is the speed of light, and f is the speed of light. c As the reference frequency, {c m} represents the frequency coding sequence, and Δf represents the frequency transition interval.

[0088] In some embodiments, step S102, performing baseband echo processing on the target echo of the frequency-coded signal to obtain the pulse-compressed echo, may include, but is not limited to, the following steps:

[0089] The target echo of the frequency-coded signal is down-converted and low-pass filtered to obtain the baseband echo. The down-conversion and low-pass filtering is used to eliminate the high-frequency carrier frequency component in the target echo of the frequency-coded signal.

[0090] The baseband echo is subjected to frequency domain pulse compression along a fast time path to obtain the pulse-compressed echo.

[0091] In some embodiments, the frequency-coded signal target echo can first undergo down-conversion low-pass filtering to obtain the baseband echo. The down-conversion low-pass filtering is used to eliminate the high-frequency carrier frequency component exp(j2π(f) in the frequency-coded signal target echo. c +c m The expression for the baseband echo is: Δf)t). In the formula, s rThis is the baseband echo. Down-conversion low-pass filtering effectively eliminates high-frequency carrier frequency components. Then, the baseband echo is subjected to frequency domain pulse compression along a fast time path to obtain the pulse-compressed echo. For example, when B·T p When >>1, the rectangular pulse echo of a linear frequency modulated signal, after pulse compression, can be approximated as a sinc[*] function. Therefore, the pulse-compressed echo can be approximated as: In the formula, y s The peak position of the sinc[*] function is: (This is the echo after pulse compression) When the movement exceeds one fast sampling period, the target will undergo distance migration.

[0092] In some embodiments, step S103 involves performing distance compensation and frequency domain transformation on the pulse-compressed echo to obtain the echo after fast-time Fourier transform, which may include, but is not limited to, the following steps:

[0093] The echo after pulse compression is processed by distance compensation to obtain the distance-compensated echo. The distance compensation process is used to eliminate the phase term in the echo after pulse compression.

[0094] Based on the correspondence of fast-time sampling points, the distance-compensated echo is processed by Fourier transform along the fast time path to obtain the echo after fast-time Fourier transform.

[0095] In some embodiments, the echo after pulse compression can be first subjected to distance compensation processing to obtain a distance-compensated echo, wherein the distance compensation processing is used to eliminate the defects in the echo after pulse compression. The phase term, the expression for the range-compensated echo, is:

[0096] In the formula, This is the echo after distance compensation. Since the true distance to the target is usually unknown, a distance search is required. And there are [missing information] at fast-time sampling points. The correspondence, the actual distance compensation process can be achieved through Implementation. Based on the correspondence of fast-time sampling points, the distance-compensated echo is subjected to a Fast-Time Fourier Transform (FTFT) to obtain the Fast-Time Fourier Transform (FTFT) echo. The expression for the FTFT echo is: In the formula, β(f,t) m The signal is the echo after the fast-time Fourier transform, and f is the fast-time frequency corresponding to the fast time t. λ is the wavelength.

[0097] In some embodiments, step S104 involves performing a second-order non-standard Keystone transform on the echo after the fast-time Fourier transform to obtain a second-order non-standard transform signal, which may include, but is not limited to, the following steps:

[0098] Based on the imaginary unit, reference frequency, frequency jump interval, frequency coding sequence, target radial acceleration, wavelength, and slow time, construct the first fast time frequency-slow time coupling term;

[0099] The first fast-time frequency and the slow-time coupling term are decoupled to obtain the first decoupled signal;

[0100] Calculate the first virtual slow time based on the first decoupling signal;

[0101] Calculate the second-order non-standard transform signal based on the echoes after the first virtual slow time and fast time Fourier transform.

[0102] In some embodiments, a first fast-time frequency-slow-time coupling term can be constructed based on the imaginary unit, reference frequency, frequency hop interval, frequency coding sequence, target radial acceleration, wavelength, and slow time. For example, for a frequency-coded radar, the expression for the first fast-time frequency-slow-time coupling term containing the acceleration phase is: In the formula, This represents the first fast-time frequency coupled with the slow-time term. Then, the first fast-time frequency coupled with the slow-time term is decoupled to obtain the first decoupled signal, where the expression for the first decoupled signal is: In the formula, This is the first decoupling signal. Based on the first decoupling signal, the first virtual slow time is calculated, where the expression for the first virtual slow time is: In the formula, t a This is the first virtual slow time. It is understandable that... Can be understood as the same signal Discrete sampling sequences obtained at different sampling times, where For equal-interval sampling, the sampling time is t1 = t m , Sampling is performed at unequal intervals, with the sampling time being... Therefore, the fast time frequency and slow time can be decoupled through the approximate form obtained by interpolation, that is: Given the sampling time is signal At sampling time t1 = t m Re-interpolation The result is that t2 is taken as the first virtual slow time. It is understandable that interp[*] is the interpolation symbol, and common interpolation methods include linear interpolation (LI), nearest neighbor interpolation (NNI), cubic spline interpolation (SI), and piecewise cubic Hermite polynomial interpolation (PCHIP). In reality, due to factors such as the time distribution characteristics of the sequence before interpolation, the interpolated sequence will have some error compared to the ideal state, leading to higher sidelobes in the target echo after coherent accumulation. This problem can be mitigated by improving the interpolation algorithm, but it cannot be avoided entirely. It should be noted that the interpolation function in MATLAB software requires the signal time before interpolation to be increasing, but this is affected by the frequency encoding c. m The effect is that t2 is not necessarily increasing. When t2 is non-increasing, it is necessary to... The signals are rearranged according to their time-increasing relationship, and then interpolated. Finally, based on the echoes after the first virtual slow time and the fast-time Fourier transform, the second-order non-standard transform signal is calculated. The expression for the second-order non-standard transform signal is: In the formula, This is a second-order non-standard Keystone transform signal. It is understandable that the second-order non-standard Keystone transform can be achieved through signal interpolation.

[0103] In some embodiments, in step S105, acceleration estimation and compensation processing are performed based on the second-order non-standard transform signal and the echo after fast-time Fourier transform to obtain a compensated echo. This may include, but is not limited to, the following steps:

[0104] Define the acceleration compensation function;

[0105] Calculate the acceleration estimate based on the acceleration compensation function and the second-order non-standard transform signal;

[0106] Based on the acceleration estimate, a fast-time Fourier compensation function is constructed.

[0107] The echo after the fast-time Fourier transform is compensated based on the fast-time Fourier compensation function and the acceleration estimate to obtain the compensated echo.

[0108] In some embodiments, an acceleration compensation function can be defined first, wherein the expression of the acceleration compensation function is: In the formula, Here, a1 is the acceleration compensation function, and a1 is the acceleration value used for search compensation. The search range is [a...]. min ,a max ], a minFor the minimum possible acceleration, a max For the possible maximum acceleration, a1∈[a mun ,a max Then, based on the acceleration compensation function and the second-order non-standard transform signal, the acceleration estimate is calculated. The formula for calculating the acceleration estimate is as follows: In the formula, This is the acceleration estimate. It's important to note that since the target energy is not concentrated in a single range-frequency unit but dispersed throughout the signal bandwidth, acceleration estimation needs to be performed on all range-frequency units within the signal bandwidth, and the average of the obtained accelerations is calculated to obtain the final acceleration estimate. Based on the acceleration estimate, a fast-time Fourier compensation function is constructed, where the expression for the fast-time Fourier compensation function is: In the formula, M a (t m Let be the fast-time Fourier compensation function. Finally, based on the fast-time Fourier compensation function and the acceleration estimate, the echo after the fast-time Fourier transform is compensated to obtain the compensated echo, where the expression for the compensated echo is: In the formula, To compensate for the echo. At this time, the acceleration phase term is compensated, and the resulting compensated echo can be regarded as the echo of a target moving at a constant speed.

[0109] In some embodiments, step S106 involves performing a first-order non-standard Keystone transform on the compensated echo to obtain a first-order non-standard transformed signal, which may include, but is not limited to, the following steps:

[0110] Based on the imaginary unit, target radial velocity, reference frequency, frequency jump interval, frequency coding sequence, wavelength, and slow time, construct a second fast time frequency-slow time coupling term;

[0111] The second fast time frequency and the slow time coupling term are decoupled to obtain the second decoupled signal;

[0112] Calculate the second virtual slow time based on the second decoupling signal;

[0113] Calculate the first-order non-standard transform signal based on the second virtual slow time and the compensated echo.

[0114] In some embodiments, a second fast-time frequency-slow-time coupling term can be constructed first based on the imaginary unit, target radial velocity, reference frequency, frequency jump interval, frequency coding sequence, wavelength, and slow time. The expression for the second fast-time frequency-slow-time coupling term is: In the formula, This is the second fast time frequency coupled with the slow time term. Then, the second fast time frequency coupled with the slow time term is decoupled to obtain the second decoupled signal, where the expression for the second decoupled signal is: In the formula, This is the second decoupling signal. Based on the second decoupling signal, the second virtual slow time is calculated, where the expression for the second virtual slow time is: In the formula, t b This is the second virtual slow time. Understandably, Can be understood as the same signal Discrete sampling sequences obtained at different sampling times, where For equal-interval sampling, the sampling time is t3 = t m , Sampling is performed at unequal intervals, with the sampling time being... Therefore, the fast time frequency and slow time can be decoupled through the approximate form obtained by interpolation, that is: Given the sampling time is signal At sampling time t3 = t m Re-interpolation The result shows that t4 can be used as the second virtual slow time. Finally, based on the second virtual slow time and the compensated echo, the first-order non-standard transform signal is calculated, where the expression for the first-order non-standard transform signal is: In the formula, This is a first-order non-standard Keystone transform signal. It is understandable that the first-order non-standard Keystone transform can be achieved through signal interpolation.

[0115] In some embodiments, step S107 involves performing echo coherent accumulation processing on the first-order non-standard transform signal to obtain the echo after coherent accumulation. This process may include, but is not limited to, the following steps:

[0116] The inverse Fourier transform of the first-order non-standard transform signal along the fast time frequency is performed to obtain the echo after target range migration correction;

[0117] The echo after target range migration correction is subjected to Fourier transform along virtual slow time to obtain the echo after coherent accumulation.

[0118] In some embodiments, the first-order non-standard transformed signal can be first subjected to an inverse Fourier transform along a fast time frequency to obtain the echo after target range migration correction, wherein the expression for the echo after target range migration correction is: In the formula, This is the echo after target range migration correction. Then, a Fourier transform is performed on the target range migration-corrected echo along a virtual slow time path to obtain the echo after coherent accumulation. The expression for the echo after coherent accumulation is: In the formula, The echo is the result of coherent accumulation, where t is the fast time and f is the fast time. b For virtual slow time frequency, T p Let be the pulse width of the linear frequency modulated signal, c be the speed of light, B be the bandwidth of the linear frequency modulated signal, R0 be the initial radial distance of the target, M be the number of coherent accumulations, and T be... r λ is the pulse repetition period, v0 is the target radial velocity, and λ is the wavelength.

[0119] In some embodiments, in step S108, motion parameters can be estimated based on the echo after coherent accumulation to obtain motion parameter estimation results, wherein the motion parameter estimation results include the initial target distance and the target velocity. For example, target detection can be achieved from the result image of the echo after coherent accumulation, where the target peak position in the echo is... The coordinate axes are transformed based on the correspondence to obtain: Therefore, the initial distance and velocity of the target can be obtained from the peak position.

[0120] In some embodiments, experimental analysis can be performed to verify the estimation accuracy of the method in this embodiment using simulation data. Data simulation experiments can be conducted using MATLAB R2024b software. The computer generates a frequency-coded target echo signal modulated by a linearly frequency-modulated signal, and sequentially performs baseband echo processing, range compensation and frequency domain transformation, second-order non-standard Keystone transform, acceleration estimation and compensation, first-order non-standard Keystone transform, echo coherent accumulation and parameter estimation. Finally, the results are plotted and displayed. The simulation parameter settings include: initial radial distance of the target R0 = 1500m, and target radial velocity... The target radial acceleration is The acceleration estimate obtained after acceleration estimation processing is It is close to the actual value a0. A schematic diagram of the echo result after coherent accumulation after simulation is shown below. Figure 2 As shown, the range migration of the target echo is corrected, effective coherent accumulation of the echo is achieved, the target peak is clear, and the parameter estimate corresponding to the target peak is the initial target range. Target speed Both are close to the actual values ​​R0 and v0. Figure 2 The x-coordinate of the target peak position corresponds to the initial distance, and the y-coordinate corresponds to the target velocity. Since this embodiment pre-estimates and compensates for the target acceleration, the target has been simplified to a uniformly moving target. Figure 2The estimated target motion parameters only include the target's initial distance and target velocity.

[0121] In some embodiments, the overall process of echo processing and parameter estimation is as follows: Figure 3 As shown, the frequency-coded target echo of a uniformly accelerated moving target can be acquired first through the radar receiver. Then, baseband echo processing is performed, including down-conversion, low-pass filtering, and pulse compression. Range compensation and frequency domain transformation are performed, including range compensation and fast-time Fourier transform. Second-order non-standard Keystone transform is performed. Velocity estimation and compensation are performed, including acceleration estimation and acceleration compensation. First-order non-standard Keystone transform is performed. Echo coherent accumulation and parameter estimation are performed, including fast-time inverse Fourier transform and slow-time Fourier transform, to obtain the echo after coherent accumulation.

[0122] In some embodiments, this embodiment has a lower computational load compared to the three-dimensional joint search scheme of range-velocity-acceleration, and can better meet the real-time requirements while acquiring target motion parameters. By performing two non-standard Keystone transforms at the radar receiver based on the characteristics of the frequency-coded signal, target echo range migration correction and coherent accumulation are effectively realized, and target detection and motion parameter estimation are completed, effectively solving the problem of echo signal processing and parameter estimation for uniformly accelerated moving targets using frequency-coded signals.

[0123] The beneficial effects of implementing the embodiments of the present invention include: First, the frequency-coded signal target echo of a uniformly accelerated target is acquired. Baseband echo processing is performed on the frequency-coded signal target echo to obtain a pulse-compressed echo. Then, range compensation and frequency domain transformation processing are performed on the pulse-compressed echo to obtain a fast-time Fourier transform echo. Second-order non-standard Keystone transform processing is performed on the fast-time Fourier transform echo to obtain a second-order non-standard transform signal. Acceleration estimation and compensation processing are then performed based on the second-order non-standard transform signal and the fast-time Fourier transform echo to obtain a compensated echo. First-order non-standard Keystone transform processing is performed on the compensated echo to obtain a first-order non-standard transform signal. Echo coherent accumulation processing is performed on the first-order non-standard transform signal to obtain a coherently accumulated echo. Finally, motion parameter estimation is performed based on the coherently accumulated echo to obtain the motion parameter estimation result. This achieves echo processing and motion parameter estimation, improves estimation accuracy, and reduces the computational load.

[0124] like Figure 4 As shown, this embodiment of the invention also provides a device for processing echoes of uniformly accelerated moving targets and estimating motion parameters, comprising:

[0125] The first module 801 is used to acquire the frequency-coded target echo signal of a uniformly accelerated target.

[0126] The second module 802 is used to perform baseband echo processing on the target echo of the frequency-coded signal to obtain the pulse-compressed echo.

[0127] The third module 803 is used to perform distance compensation and frequency domain transformation on the pulse-compressed echo to obtain the echo after fast time Fourier transform.

[0128] The fourth module 804 is used to perform a second-order non-standard Keystone transform on the echo after the fast-time Fourier transform to obtain a second-order non-standard transformed signal.

[0129] The fifth module 805 is used to perform acceleration estimation and compensation processing based on the second-order non-standard transform signal and the echo after fast-time Fourier transform to obtain the compensated echo.

[0130] The sixth module 806 is used to perform a first-order non-standard Keystone transform on the compensated echo to obtain a first-order non-standard transformed signal.

[0131] Module 7, 807, is used to perform echo coherent accumulation processing on the first-order non-standard transform signal to obtain the echo after coherent accumulation.

[0132] The eighth module 808 is used to estimate motion parameters based on the echo after coherent accumulation, and obtain the motion parameter estimation results, which include the target's initial distance and target velocity.

[0133] The content of the above method embodiments is applicable to the device embodiments. The specific functions implemented by the device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0134] like Figure 5 As shown, embodiments of the present invention also provide a computer device, including:

[0135] At least one processor 901;

[0136] At least one memory 902 is used to store at least one program;

[0137] When at least one program is executed by at least one processor, such that at least one processor achieves Figure 1 The method shown.

[0138] The content of the above method embodiments is applicable to the device embodiments. The specific functions implemented by the device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0139] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements... Figure 1 The method shown.

[0140] The content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0141] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for processing echoes of uniformly accelerated moving targets and estimating their motion parameters, characterized in that, Includes the following steps: Acquire the frequency-encoded target echo signal of a uniformly accelerated target; The frequency-encoded signal target echo is subjected to baseband echo processing to obtain the pulse-compressed echo; The pulse-compressed echo is subjected to distance compensation and frequency domain transformation to obtain the echo after fast time Fourier transform. The echo after the fast time Fourier transform is processed by a second-order non-standard Keystone transform to obtain a second-order non-standard transformed signal. Based on the second-order non-standard transform signal and the echo after the fast-time Fourier transform, acceleration estimation and compensation processing are performed to obtain the compensated echo. The compensated echo is subjected to a first-order non-standard Keystone transform to obtain a first-order non-standard transformed signal. The first-order non-standard transformed signal is subjected to echo coherent accumulation processing to obtain the echo after coherent accumulation. Based on the echo after coherent accumulation, motion parameters are estimated to obtain motion parameter estimation results, which include the target's initial distance and target velocity. The step of performing a second-order non-standard Keystone transform on the echo after the fast-time Fourier transform to obtain a second-order non-standard transformed signal includes: Based on the imaginary unit, reference frequency, frequency jump interval, frequency coding sequence, target radial acceleration, wavelength, and slow time, construct the first fast time frequency-slow time coupling term; The first fast-time frequency and slow-time coupling term are decoupled to obtain the first decoupled signal; Calculate the first virtual slow time based on the first decoupling signal; The second-order non-standard transform signal is calculated based on the first virtual slow time and the echo after the fast-time Fourier transform.

2. The method according to claim 1, characterized in that, The process of performing baseband echo processing on the target echo of the frequency-coded signal to obtain the pulse-compressed echo includes: The frequency-coded signal target echo is subjected to down-conversion low-pass filtering to obtain the baseband echo. The down-conversion low-pass filtering is used to eliminate the high-frequency carrier frequency component in the frequency-coded signal target echo. The baseband echo is subjected to frequency domain pulse compression along a fast time path to obtain the pulse-compressed echo.

3. The method according to claim 1, characterized in that, The process of performing distance compensation and frequency domain transformation on the pulse-compressed echo to obtain the echo after fast-time Fourier transform includes: The pulse-compressed echo is subjected to distance compensation processing to obtain a distance-compensated echo. The distance compensation processing is used to eliminate the phase term in the pulse-compressed echo. Based on the correspondence of fast-time sampling points, the distance-compensated echo is subjected to a Fourier transform along the fast time path to obtain the echo after the fast-time Fourier transform.

4. The method according to claim 1, characterized in that, The step of performing acceleration estimation and compensation processing based on the second-order non-standard transform signal and the echo after the fast-time Fourier transform to obtain the compensated echo includes: Define the acceleration compensation function; Calculate the acceleration estimate based on the acceleration compensation function and the second-order non-standard transformation signal; Based on the acceleration estimate, a fast-time Fourier compensation function is constructed; The echo after the fast-time Fourier transform is compensated based on the fast-time Fourier compensation function and the acceleration estimate to obtain the compensated echo.

5. The method according to claim 1, characterized in that, The first-order non-standard Keystone transform processing of the compensated echo to obtain a first-order non-standard transformed signal includes: Based on the imaginary unit, target radial velocity, reference frequency, frequency jump interval, frequency coding sequence, wavelength, and slow time, construct a second fast time frequency-slow time coupling term; The second fast-time frequency and slow-time coupling term are decoupled to obtain the second decoupled signal; Calculate the second virtual slow time based on the second decoupling signal; The first-order non-standard transform signal is calculated based on the second virtual slow time and the compensated echo.

6. The method according to claim 1, characterized in that, The process of performing echo coherent accumulation on the first-order non-standard transformed signal to obtain the coherently accumulated echo includes: The first-order non-standard transformed signal is subjected to inverse Fourier transform along the fast time frequency to obtain the echo after target range migration correction; The echo after target distance migration correction is subjected to Fourier transform along virtual slow time to obtain the echo after coherent accumulation.

7. The method according to claim 1, characterized in that, The expression for the echo after coherent accumulation is: ； In the formula, The echo after coherent accumulation, To save time, For virtual slow time frequency, For linear frequency modulated signal pulse width, At the speed of light, For the bandwidth of a linear frequency modulated signal, The initial radial distance to the target. To accumulate the number of coherents, The pulse repetition period, For the target radial velocity, λ is the wavelength.

8. A device for processing echoes of uniformly accelerated moving targets and estimating motion parameters, characterized in that, include: The first module is used to acquire the frequency-coded target echo signal of a uniformly accelerated target. The second module is used to perform baseband echo processing on the target echo of the frequency-coded signal to obtain the pulse-compressed echo. The third module is used to perform distance compensation and frequency domain transformation processing on the pulse-compressed echo to obtain the echo after fast time Fourier transform. The fourth module is used to perform a second-order non-standard Keystone transform on the echo after the fast-time Fourier transform to obtain a second-order non-standard transformed signal. The fifth module is used to perform acceleration estimation and compensation processing based on the second-order non-standard transform signal and the echo after the fast-time Fourier transform to obtain the compensated echo. The sixth module is used to perform a first-order non-standard Keystone transform on the compensated echo to obtain a first-order non-standard transformed signal. The seventh module is used to perform echo coherent accumulation processing on the first-order non-standard transformed signal to obtain the echo after coherent accumulation. The eighth module is used to estimate motion parameters based on the echo after coherent accumulation, and obtain motion parameter estimation results, which include the target initial distance and the target velocity. The step of performing a second-order non-standard Keystone transform on the echo after the fast-time Fourier transform to obtain a second-order non-standard transformed signal includes: Based on the imaginary unit, reference frequency, frequency jump interval, frequency coding sequence, target radial acceleration, wavelength, and slow time, construct the first fast time frequency-slow time coupling term; The first fast-time frequency and slow-time coupling term are decoupled to obtain the first decoupled signal; Calculate the first virtual slow time based on the first decoupling signal; The second-order non-standard transform signal is calculated based on the first virtual slow time and the echo after the fast-time Fourier transform.

9. A computer device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method as described in any one of claims 1-7.

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