Broadband radar distance extension target detection method and device, terminal and medium

Abstract

The invention discloses a broadband radar distance extension target detection method and device, a terminal and a medium, and relates to the technical field of radar signal processing, and the method comprises the steps: obtaining each linear frequency modulation pulse radio frequency signal transmitted by a radar; in a walking and stopping mode, performing pulse compression on each linear frequency modulation pulse radio frequency signal by adopting pulse dechirp processing, and determining each dechirp processing signal; coherent energy accumulation is carried out according to the dechirp processing signals, and coherent accumulation signals are determined; converting the coherent accumulation signal to a frequency domain, and determining a dechirp pulse amplitude spectrum; and performing target detection according to the dechirp pulse amplitude spectrum, and determining a target detection result. According to the method, pulse dechirp processing and coherent energy accumulation are carried out on each received linear frequency modulation pulse radio frequency signal to obtain a coherent accumulation signal for subsequent target detection, so that the problem that in the prior art, when the signal-to-noise ratio is reduced, better anti-noise performance is difficult to realize with smaller calculation amount can be effectively solved.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and in particular to a broadband radar range-extended target detection method, device, terminal, and medium. Background Technology

[0002] Wideband radar achieves high range resolution due to its large signal bandwidth, decomposing traditional point targets into multiple scattering points; such targets are called range-extended targets. Detection of range-extended targets is achieved by integrating the energy from the target's multiple scattering points and suppressing clutter and noise interference.

[0003] Current wideband radar range-extended target detection methods include the Generalized Likelihood Ratio Test (GLRT), Rao Test, Wald Test, Adaptive Subspace Detector (ASD), Time-Frequency Decomposition (TFD), Nonlocal Nonlinear Compressed Map (NLNSM), Modified Correlation Matrix (MCOM), Maximum Invariant Statistic (MIS), Matched Subspace Detector (MSD), and Singular Value Decomposition (SVD). However, these methods struggle to achieve good noise resistance with minimal computation when the signal-to-noise ratio decreases.

[0004] Therefore, existing technologies still need improvement and development. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a broadband radar range-extended target detection method, device, terminal and medium to address the above-mentioned deficiencies of the prior art, aiming to solve the problem that the prior art is difficult to achieve good anti-noise performance with a small amount of computation when the signal-to-noise ratio is reduced.

[0006] The technical solution adopted by this invention to solve the problem is as follows: In a first aspect, embodiments of the present invention provide a broadband radar range-extended target detection method, wherein the method includes: Acquire the radio frequency signals of each linear frequency modulated pulse transmitted by the radar; In the stop-and-go mode, pulse deskewing is used to compress each of the linear frequency modulated pulse radio frequency signals to determine each deskewing signal. Based on the deskewing signals described above, coherent energy is accumulated to determine the coherent accumulation signal; The coherent accumulated signal is converted to the frequency domain to determine the descrambling pulse amplitude spectrum; Target detection is performed based on the deslanted pulse amplitude spectrum to determine the target detection result.

[0007] In one implementation method, acquiring the radio frequency signals of each linear frequency modulated pulse transmitted by the radar includes: Acquire the linear frequency modulated pulse transmitted by the radar; The carrier frequency signal is modulated based on the pulse complex envelope of the linear frequency modulated pulse to determine the linear frequency modulated pulse radio frequency signal.

[0008] In one implementation, the pulse complex envelope of the linear frequency modulated pulse is represented as: , in, It has a rectangular pulse shape. It is a rectangular pulse function. For the variables of the rectangular pulse function, The pulse width. For phase terms, For frequency modulation slope, For time variables, It is the imaginary unit.

[0009] In one implementation, the linear frequency modulated pulse radio frequency signal is represented as: , in, The linear frequency modulated pulse radio frequency signal is... The carrier frequency signal, To save time, This is the index of the transmitted pulses within a coherent processing interval. For all times, For slow time, This is the pulse repetition interval.

[0010] In one implementation method, in a stop-and-go mode, pulse deskewing processing is used to compress each of the linear frequency modulated pulse radio frequency signals to determine each deskewing processing signal, including: Determine the linear frequency modulated pulse radio frequency signals for each of the described steps in the stop-and-go mode; A local reference signal is acquired, and pulse deskewing is performed on each of the linear frequency modulated pulse radio frequency signals in the walk-stop mode based on the local reference signal to determine each of the deskewing signals.

[0011] In one implementation, each of the linear frequency modulated pulse radio frequency signals in the stop-and-go mode is represented as follows: , in, For slow time The corresponding linear frequency modulated pulse radio frequency signal, The number of scattering points. For the first The scattering coefficient at each scattering point It is additive white Gaussian noise. This is to delay the round-trip time.

[0012] In one implementation, the local reference signal is represented as: , in, For time variables The corresponding local reference signal, Indicates the length of the receiving window.

[0013] In one implementation, the descrambling signal is represented as:

[0014] in, For slow time The corresponding descrambling signal, The signal item corresponding to the descrambling signal. This refers to the noise term corresponding to the descrambling signal.

[0015] In one implementation method, coherent energy accumulation is performed based on each of the desketching signals to determine the coherent accumulation signal, including: Each of the deskewing signals is convolved with the adjacent deskewing signals to determine each energy accumulation signal; The step of iteratively performing a preset number of iterations to convolve each energy accumulation signal with the adjacent energy accumulation signals to obtain each updated energy accumulation signal; The updated energy accumulation signal corresponding to the preset number of iterations is used as the coherent accumulation signal.

[0016] In one implementation, each energy accumulation signal is convolved with an adjacent energy accumulation signal to obtain updated energy accumulation signals, including: The first The energy accumulation signal corresponding to each slow time The adjacent first The energy accumulation signal corresponding to each slow time Perform convolution to obtain the updated energy accumulation signal. , is represented as: , in, This represents the convolution operator. For the signal term corresponding to the updated energy accumulation signal, The noise term corresponding to the updated energy accumulation signal. This represents the current iteration number. This indicates a definition.

[0017] In one implementation, converting the coherent accumulated signal to the frequency domain and determining the descrambling pulse amplitude spectrum includes: Perform a Fourier transform on the coherent accumulated signal to determine the spectrum of the continuous descrambling pulse; The absolute value of the spectrum of the continuous deslope pulse is taken to determine the amplitude spectrum of the deslope pulse.

[0018] In one implementation method, target detection is performed based on the deskewing pulse amplitude spectrum, and the target detection result is determined, including: Construct a binary hypothesis testing model; Target detection is performed based on the deslanted pulse amplitude spectrum and the binary hypothesis testing model to determine the target detection result.

[0019] In one implementation method, the binary hypothesis testing model is expressed as: , in, For likelihood ratio, The descrambled pulse amplitude spectrum, To detect threshold, This indicates that the descrambled pulse amplitude spectrum contains a target. This indicates that the descrambled pulse amplitude spectrum contains only noise. It is a combination of greater than or equal to and less than or equal to.

[0020] Secondly, embodiments of the present invention also provide a broadband radar range-extended target detection device, wherein the broadband radar range-extended target detection device includes: The signal acquisition module is used to acquire the radio frequency signals of each linear frequency modulated pulse transmitted by the radar; The deskewing processing module is used to perform pulse compression on each of the linear frequency modulated pulse radio frequency signals in the stop-and-go mode, and to determine each deskewing processing signal. The coherent accumulation module is used to accumulate coherent energy based on each of the deskewing signals and determine the coherent accumulation signal; The frequency domain conversion module is used to convert the coherent accumulated signal to the frequency domain and determine the descrambling pulse amplitude spectrum; The target detection module is used to perform target detection based on the deslope pulse amplitude spectrum and determine the target detection result.

[0021] In one implementation, the signal acquisition module includes: A linear frequency modulated pulse acquisition unit is used to acquire linear frequency modulated pulses transmitted by the radar. The carrier frequency signal modulation unit is used to modulate the carrier frequency signal based on the pulse complex envelope of the linear frequency modulated pulse to determine the linear frequency modulated pulse radio frequency signal.

[0022] In one implementation, the linear frequency modulated pulse acquisition unit includes a pulse complex envelope representation unit, wherein the pulse complex envelope representation unit includes: , in, It has a rectangular pulse shape. It is a rectangular pulse function. For the variables of the rectangular pulse function, The pulse width. For phase terms, For frequency modulation slope, For time variables, It is the imaginary unit.

[0023] In one embodiment, the carrier signal modulation unit includes a linear frequency modulated pulse radio frequency signal representation unit, the linear frequency modulated pulse radio frequency signal representation unit comprising: , in, The linear frequency modulated pulse radio frequency signal is... The carrier frequency signal, To save time, This is the index of the transmitted pulses within a coherent processing interval. For all times, For slow time, This is the pulse repetition interval.

[0024] In one implementation, the de-skewing processing module includes: A stop-and-go mode signal determination unit is used to determine each of the linear frequency modulated pulse radio frequency signals in the stop-and-go mode; The pulse deskewing processing unit is used to acquire a local reference signal, and to perform pulse compression on each of the linear frequency modulated pulse radio frequency signals in the stop-and-go mode based on the local reference signal to determine each of the deskewing processing signals.

[0025] In one implementation, the stop-and-go mode signal determination unit includes a stop-and-go mode signal representation unit, the stop-and-go mode signal representation unit comprising: , in, For slow time The corresponding linear frequency modulated pulse radio frequency signal, The number of scattering points. For the first The scattering coefficient at each scattering point It is additive white Gaussian noise. This is to delay the round-trip time.

[0026] In one implementation, the pulse de-chewing processing unit includes a local reference signal representation unit, the local reference signal representation unit comprising: , in, For time variables The corresponding local reference signal, Indicates the length of the receiving window.

[0027] In one implementation, the pulse deskewing processing unit includes a deskewing processing signal representation unit, the deskewing processing signal representation unit comprising:

[0028] in, For slow time The corresponding descrambling signal, The signal item corresponding to the descrambling signal. This refers to the noise term corresponding to the descrambling signal.

[0029] In one implementation, the coherent accumulation module includes: An initial convolutional unit is used to convolve each of the deskewing signals with the adjacent deskewing signals to determine each energy accumulation signal; An iterative convolution unit is used to iteratively perform the step of convolving each energy accumulation signal with the adjacent energy accumulation signals for a preset number of iterations to obtain updated energy accumulation signals. The coherent accumulation signal determination unit is used to take the updated energy accumulation signal corresponding to the preset iteration number as the coherent accumulation signal.

[0030] In one implementation, the iterative convolutional unit includes: The updated energy accumulation signal determination unit is used to determine the first... The energy accumulation signal corresponding to each slow time The adjacent first The energy accumulation signal corresponding to each slow time Perform convolution to obtain the updated energy accumulation signal. , is represented as: , in, This represents the convolution operator. For the signal term corresponding to the updated energy accumulation signal, The noise term corresponding to the updated energy accumulation signal. This represents the current iteration number. This indicates a definition.

[0031] In one implementation, the frequency domain conversion module includes: The Fourier transform unit is used to perform Fourier transform on the coherent accumulated signal to determine the spectrum of the continuous descrambling pulse; The absolute value unit is used to take the absolute value of the spectrum of the continuous descrambling pulse to determine the amplitude spectrum of the descrambling pulse.

[0032] In one implementation, the target detection module includes: Binary hypothesis testing model building unit, used to build binary hypothesis testing models; The target detection unit is used to perform target detection based on the deslanted pulse amplitude spectrum and the binary hypothesis testing model, and to determine the target detection result.

[0033] In one implementation method, the binary hypothesis testing model construction unit includes a binary hypothesis testing model representation unit, the binary hypothesis testing model representation unit comprising: , in, For likelihood ratio, The descrambled pulse amplitude spectrum, To detect threshold, This indicates that the descrambled pulse amplitude spectrum contains a target. This indicates that the descrambled pulse amplitude spectrum contains only noise. It is a combination of greater than or equal to and less than or equal to.

[0034] Thirdly, embodiments of the present invention also provide a terminal, the terminal including a memory and one or more processors; the memory stores one or more programs; the programs include instructions for executing the broadband radar range-extended target detection method as described above; the processor is used to execute the programs.

[0035] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a plurality of instructions, wherein the instructions are adapted to be loaded and executed by a processor to implement any of the broadband radar range-extended target detection methods described above.

[0036] The beneficial effects of this invention are as follows: In this embodiment, the invention acquires each linear frequency modulated (LFM) pulse radio frequency (RF) signal transmitted by the radar; in a walk-stop mode, pulse de-chewing processing is used to compress each LFM pulse RF signal to determine each de-chewing processed signal; coherent energy accumulation is performed based on each de-chewing processed signal to determine a coherent accumulated signal; the coherent accumulated signal is converted to the frequency domain to determine the de-chewing pulse amplitude spectrum; target detection is performed based on the de-chewing pulse amplitude spectrum to determine the target detection result. Because this invention performs pulse de-chewing processing and coherent energy accumulation on each received LFM pulse RF signal to obtain a coherent accumulated signal for subsequent target detection, it can effectively solve the problem that existing methods struggle to achieve good noise immunity with minimal computation when the signal-to-noise ratio decreases. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart illustrating the broadband radar range-extended target detection method provided in an embodiment of the present invention.

[0039] Figure 2 This is a schematic diagram of the process for acquiring linear frequency modulated pulse radio frequency signals provided in an embodiment of the present invention.

[0040] Figure 3 This is a schematic diagram of the pulse deskewing process in the stop-go mode provided in an embodiment of the present invention.

[0041] Figure 4 This is a schematic diagram of the process for determining the coherent accumulation signal provided in an embodiment of the present invention.

[0042] Figure 5 This is a schematic diagram illustrating a specific implementation of the coherent accumulation signal determination provided in an embodiment of the present invention.

[0043] Figure 6 This is a schematic diagram of the frequency domain conversion process of the coherent accumulation signal provided in an embodiment of the present invention.

[0044] Figure 7 This is a schematic diagram of the target detection process based on a binary hypothesis testing model provided in an embodiment of the present invention.

[0045] Figure 8 This is a schematic diagram comparing the deskewing pulse amplitude spectrum under different convolution times provided in the embodiments of the present invention.

[0046] Figure 9 This is a schematic diagram comparing the performance of the various methods provided in the embodiments of the present invention under different convolution numbers.

[0047] Figure 10 This is a schematic diagram of the internal modules of the broadband radar range-extended target detection device provided in an embodiment of the present invention.

[0048] Figure 11 This is a schematic diagram of the terminal provided in an embodiment of the present invention. Detailed Implementation

[0049] This invention discloses a broadband radar range-extended target detection method, apparatus, terminal, and medium. To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention.

[0050] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0051] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0052] Wideband radar achieves high range resolution due to its large signal bandwidth, decomposing traditional point targets into multiple scattering points; such targets are called range-extended targets. Detection of range-extended targets is achieved by integrating the energy from the target's multiple scattering points and suppressing clutter and noise interference.

[0053] Current wideband radar range-extended target detection methods include the Generalized Likelihood Ratio Test (GLRT), Rao Test, Wald Test, Adaptive Subspace Detector (ASD), Time-Frequency Decomposition (TFD), Nonlocal Nonlinear Compressed Map (NLNSM), Modified Correlation Matrix (MCOM), Maximum Invariant Statistic (MIS), Matched Subspace Detector (MSD), and Singular Value Decomposition (SVD). However, these methods struggle to achieve good noise resistance with minimal computation when the signal-to-noise ratio decreases.

[0054] To address the aforementioned deficiencies in existing technologies, this invention provides a broadband radar range-extended target detection method. The method acquires each linear frequency modulated (LFM) pulse radio frequency (RF) signal emitted by the radar; in a walk-stop mode, pulse de-chewing processing is used to compress each LFM pulse RF signal to determine each de-chewing processed signal; coherent energy accumulation is performed based on each de-chewing processed signal to determine a coherent accumulated signal; the coherent accumulated signal is converted to the frequency domain to determine the de-chewing pulse amplitude spectrum; and target detection is performed based on the de-chewing pulse amplitude spectrum to determine the target detection result. Because this invention performs pulse de-chewing processing and coherent energy accumulation on each received LFM pulse RF signal to obtain a coherent accumulated signal for subsequent target detection, it effectively solves the problem that existing methods struggle to achieve good noise immunity with minimal computation when the signal-to-noise ratio (SNR) is reduced.

[0055] Exemplary method: like Figure 1 As shown, the method includes: Step S100: Acquire the radio frequency signals of each linear frequency modulated pulse emitted by the radar.

[0056] Linear frequency modulated (LFM) pulse radio frequency signals (radar echoes) are commonly used high-bandwidth signals in radar and communications. Their characteristic is that the instantaneous frequency changes linearly with time, and high-resolution signals with large time and bandwidth can be achieved through pulse compression. The receiver acquires the LFM pulse radio frequency signals corresponding to each moment of radar transmission for subsequent target detection.

[0057] There are two methods for acquiring various linear frequency modulated (LFM) pulse radio frequency (RF) signals: internal synchronous acquisition and external reception acquisition. Internal synchronous acquisition extracts signals from key nodes in the radar transmission link, avoiding space propagation loss. The steps of internal synchronous acquisition are as follows: directly read the baseband complex sampled data of the transmitted signal, transmit and store it at high speed via Ethernet; before frequency conversion at the transmitter, couple the intermediate frequency (IF) signal using a directional coupler, amplify and filter it, and then acquire and store it using a high-speed analog-to-digital converter, ensuring the sampling rate meets the Nyquist criterion; extract the low-power RF signal at the transmit antenna port using a low-loss directional coupler, match it with an attenuator, and then connect it to an oscilloscope / acquisition card to avoid damaging the equipment. External reception acquisition captures the LFM pulses radiated in space through an RF receiving front-end, requiring solutions to the large dynamic range and blind parameter estimation problems. When acquiring signals via external receivers, a matching directional or omnidirectional antenna must be selected based on the radar carrier frequency to ensure coverage of the signal bandwidth; automatic gain control or a programmable attenuator should be used to avoid signal saturation or underamplitude; pulse triggering (such as rising edge triggering) or PPS synchronization should be used to ensure the capture of a complete pulse sequence; time-frequency analysis should be performed on the acquired signal to extract parameters such as carrier frequency, pulse width, and frequency modulation slope to verify whether it is the target LFM signal.

[0058] In one implementation, such as Figure 2 As shown, the radio frequency signals of each linear frequency modulated pulse transmitted by the radar are acquired, including: Step S101: Acquire the linear frequency modulated pulse transmitted by the radar; Step S102: Modulate the carrier frequency signal based on the pulse complex envelope of the linear frequency modulated pulse to determine the linear frequency modulated pulse radio frequency signal.

[0059] A linear frequency modulated (LFM) pulse is a pulse signal with a linearly swept frequency. The pulse complex envelope of an LFM pulse refers to the baseband complex signal after removing the high-frequency components of the carrier wave; it fully describes the amplitude and phase modulation rules of the LFM pulse.

[0060] In one implementation, the pulse complex envelope of the linear frequency modulated pulse is represented as: , in, It has a rectangular pulse shape. It is a rectangular pulse function. For the variables of the rectangular pulse function, The pulse width. For phase terms, For frequency modulation slope, For time variables, It is the imaginary unit.

[0061] Modulating a carrier signal using the pulse complex envelope of a linear frequency modulated (LFM) pulse involves multiplying the baseband complex envelope (containing LFM pulse phase or amplitude information) by the carrier complex exponent, and then taking the real part to obtain the final radio frequency (RF) modulated signal. Essentially, it's the process of loading baseband LFM pulse information onto a high-frequency carrier. The steps for obtaining an LFM pulse RF signal by modulating a carrier signal using the pulse complex envelope of a LFM pulse are as follows: The carrier signal is converted to a complex exponential form, with its real part being a cosine carrier and its imaginary part a sine carrier, generating a high-frequency carrier complex exponential signal; the pulse complex envelope of the LFM pulse is multiplied by the high-frequency carrier complex exponential signal to obtain a complex RF signal, thus loading the LFM pulse information onto the carrier; since antennas cannot radiate complex signals, the real part of the complex RF signal must be taken to obtain the actual transmitted LFM pulse RF signal.

[0062] In one implementation, the linear frequency modulated pulse radio frequency signal is represented as: , in, The linear frequency modulated pulse radio frequency signal is... The carrier frequency signal, To save time, This is the index of the transmitted pulses within a coherent processing interval (CPI). For all times, For slow time, The pulse repetition interval (PRI) is used.

[0063] like Figure 1 As shown, the method further includes the following steps: Step S200: In the stop-and-go mode, pulse deskewing is performed on each of the linear frequency modulated pulse radio frequency signals to compress the pulses and determine each deskewing signal.

[0064] The stop-and-go mode is suitable for high-resolution detection of extended-range targets by broadband radar. Essentially, it eliminates the coupling interference of platform movement on the echo phase by using the discrete timing sequence of the radar platform's movement, stillness, and pulse transmission or reception, simplifying the complexity of subsequent signal processing (such as pulse compression, imaging, and target detection). The stop-and-go mode decomposes the radar platform's movement process into an alternating cycle of moving and stationary phases. During the moving phase, the radar platform moves from its current position to the next observation position without transmitting or receiving signals; during the stationary phase, the radar platform is completely stationary, transmitting a linear frequency modulated pulse and receiving the target echo. At this time, the relative position of the platform and the target is fixed.

[0065] The effectiveness of the stop-and-go mode depends on the assumptions of stillness, far-field, and uniform motion. The stillness assumption states that the transmission-reception duration of a single linear frequency modulated pulse is much shorter than the pulse repetition period, and the displacement of the radar platform during the transmission-reception duration is negligible (approximately stationary). The far-field assumption states that the target is in the radar's far field, the electromagnetic waves emitted by the radar can be considered plane waves, and the echo phase difference between each scattering point of the target is only related to the position of the scattering point. The uniform motion assumption states that the radar platform's movement speed is constant between two adjacent stationary positions, ensuring uniform spatial spacing of the observation positions.

[0066] Pulse deskewing involves mixing the transmitted linear frequency modulated (LFM) pulse RF signal with a local reference signal having the same slope as the emitted LFM pulse RF signal, converting the broadband LFM pulse RF signal into a narrowband single-frequency signal, and then performing compression through Fourier or matched filtering. In this embodiment, under stop-and-go mode, pulse deskewing is used to compress each LFM pulse RF signal, determining each deskewing processed signal (deskewing echo). This retains the high resolution and signal-to-noise ratio advantages of LFM pulse RF signal compression, perfectly adapts to stop-and-go timing, and simultaneously solves the hardware and computing power bottlenecks of broadband signal processing.

[0067] In one implementation, such as Figure 3 As shown, in the stop-and-go mode, pulse de-chewing processing is used to compress each of the linear frequency modulated pulse radio frequency signals to determine each de-chewing processing signal, including: Step S201: Determine each of the linear frequency modulation pulse radio frequency signals in the stop-go mode; Step S202: Obtain the local reference signal and perform pulse deskewing processing. Based on the local reference signal, perform pulse compression on each of the linear frequency modulation pulse radio frequency signals in the stop-and-go mode to determine each of the deskewing processing signals.

[0068] Before performing pulse deskewing on the linear frequency modulated (LFM) pulse radio frequency (RF) signals, each LFM pulse RF signal in the stop-and-go mode is first determined. In one implementation, each of the LFM pulse RF signals in the stop-and-go mode is represented as follows: , in, For slow time The corresponding linear frequency modulated pulse radio frequency signal, The number of scattering points. For the first The scattering coefficient at each scattering point It is additive white Gaussian noise. This is to delay the round-trip time. This is the round-trip time delay, expressed as:

[0069] in, Indicates slow time At that time, radar and the first The distance between each scattering point This indicates the speed at which a signal propagates in a vacuum.

[0070] A local reference signal is generated for de-chirping. In one implementation, the local reference signal is represented as: , in, For time variables The corresponding local reference signal, This indicates the length of the receiving window, which is usually greater than the linear frequency modulation pulse width.

[0071] Multiplying the linear frequency modulated pulse radio frequency signal with the complex conjugate of the local reference signal cancels out the second phase term of the linear frequency modulated pulse radio frequency signal, transforming the original wideband linear frequency modulated pulse radio frequency signal into a single-frequency narrowband intermediate frequency signal, thus obtaining the deskewing processed signal.

[0072] In one implementation, the descrambling signal is represented as:

[0073] in, For slow time The corresponding descrambling signal, The signal item corresponding to the descrambling signal. The noise term corresponding to the descrambling signal. It follows a Gaussian distribution. In the representation of the descrambling signal above, it contains... The exponent term is usually 1, so it is ignored.

[0074] This embodiment employs pulse deskewing processing to compress the linear frequency modulated (LFM) pulse radio frequency (RF) signals in walk-stop mode based on the local reference signal, converting the broadband LFM pulse RF signals into narrowband intermediate frequencies. This reduces the amount of data in the digital-to-analog conversion, thereby reducing hardware and processing pressure. By deskewing, the linear frequency modulation characteristics of the LFM pulse RF signals are canceled, eliminating range and Doppler coupling and effectively improving range resolution. Furthermore, narrowband signals are easier to accumulate through inter-pulse coherence, enhancing the detection capability of weak targets.

[0075] like Figure 1 As shown, the method further includes the following steps: Step S300: Perform coherent energy accumulation based on each of the deskew processing signals to determine the coherent accumulation signal.

[0076] Coherent energy accumulation for each deslant signal involves aligning the phase and frequency between multiple pulses in walk-stop mode. Energy focusing is achieved through phase compensation, inter-pulse coherent superposition, and combined with fast Fourier transform or pulse compression. This can improve the signal-to-noise ratio to approximately N times (where N is the number of accumulated pulses), while also enhancing the accuracy of weak target detection and parameter estimation.

[0077] Coherent energy accumulation based on each deskewing signal may include the following steps: Amplitude normalization is performed on each de-angulation signal to eliminate inter-pulse amplitude fluctuations. Simultaneously, the initial phase of each pulse is recorded using the first pulse phase as a reference for subsequent compensation. Since the error in the de-angulation signal mainly stems from Doppler frequency shift and system phase drift, Doppler frequency shift estimation and compensation are first performed on the de-angulation signal to estimate the target radial velocity, calculate the inter-pulse phase increment, and apply a compensation phase to the nth pulse to counteract the phase rotation caused by Doppler. Then, system phase drift compensation is performed, estimating the inter-pulse phase drift using a reference channel or a target-free region, and outputting a phase-aligned compensation signal based on the compensation formula. The compensation signals are summed to obtain a coherent accumulation signal, achieving target energy superposition and partial cancellation of noise due to randomness.

[0078] This embodiment obtains a coherently accumulated signal by coherently accumulating the energy of each de-skewed signal, which can improve the signal-to-noise ratio and enhance the detection capability of weak targets; energy focusing makes it easier for the target signal to exceed the detection threshold, which is suitable for target detection in complex clutter environments; based on the narrowband signal after de-skewing, coherent accumulation does not require additional high-speed sampling, resulting in low hardware and computational pressure.

[0079] In one implementation, such as Figure 4 As shown, coherent energy accumulation is performed based on each of the deskew processing signals to determine the coherent accumulation signal, including: Step S301: Convolve each of the deskewing signals with the adjacent deskewing signals to determine each energy accumulation signal; Step S302: Iteratively perform a preset number of iterations to convolve each energy accumulation signal with the adjacent energy accumulation signals to obtain each updated energy accumulation signal; Step S303: Use the updated energy accumulation signal corresponding to the preset iteration number as the coherent accumulation signal.

[0080] like Figure 5 As shown, in order to coherently accumulate energy, this embodiment convolves each deskewed signal with its adjacent deskewed signal to obtain each energy accumulation signal. Specifically, the first... Individual deslant processing signal The adjacent first Individual deslant processing signal After performing convolution, the energy accumulation signals can be represented as follows: , in, Represents the convolution operator. Signal term of the energy accumulation signal. Defined as Noise term of energy accumulation signal Defined as superscript This represents the first energy accumulation. Indicates the first Secondary energy accumulation.

[0081] The energy accumulation signals obtained above are convolved again, with each energy accumulation signal convolved with its adjacent energy accumulation signals, to obtain the updated energy accumulation signals, which can be represented as follows: , This indicates the second energy accumulation. Indicates the first An energy accumulation signal, Indicates the first An energy accumulation signal, This indicates the updated energy accumulation signal. The signal term representing the updated energy accumulation signal, This represents the noise term in the updated energy accumulation signal.

[0082] The updated energy accumulation signal is convolved again, with each energy accumulation signal (updated in the previous step) convolved with its neighboring energy accumulation signals (updated in the previous step) to obtain the updated energy accumulation signal. This process of convolving each energy accumulation signal with its neighboring energy accumulation signals is iteratively performed a preset number of times to obtain each updated energy accumulation signal. The updated energy accumulation signal obtained in the last iteration (the preset number of iterations) is taken as the coherent accumulation signal.

[0083] In one implementation, each energy accumulation signal is convolved with its adjacent energy accumulation signals to obtain updated energy accumulation signals, including: The first The energy accumulation signal corresponding to each slow time The adjacent first The energy accumulation signal corresponding to each slow time Perform convolution to obtain the updated energy accumulation signal. , is represented as: , in, This represents the convolution operator. For the signal term corresponding to the updated energy accumulation signal, The noise term corresponding to the updated energy accumulation signal. Indicates definition, The current iteration number or the th iteration Secondary energy accumulation. It's important to note that the above equation neglects the slow-time index. ,because The energy of each pulse has been coherently accumulated into a signal. Assume... To preset the number of iterations, then... As a coherent accumulation signal.

[0084] This embodiment achieves coherent energy accumulation through convolution, which effectively reduces computational complexity. Compared with traditional integral detectors and spatial scattering density detectors, the detection signal-to-noise ratio threshold is reduced by more than 6 dB. Compared with direct temporal superposition, convolutional accumulation has a higher tolerance for system phase errors. Even with small inter-pulse phase fluctuations, effective coherence can still be achieved through weighted superposition of kernel functions, improving the stability of the accumulation results.

[0085] In one implementation, Doppler dimension weighting (such as a two-dimensional matched filter kernel) can be introduced into the convolution kernel, which can simultaneously perform range-direction convolution accumulation and velocity-direction Doppler filtering, outputting a range-velocity two-dimensional spectrum. This can distinguish multiple targets at adjacent ranges or velocities, avoiding mutual masking of target signals.

[0086] Step S400: Convert the coherent accumulation signal to the frequency domain and determine the descrambling pulse amplitude spectrum.

[0087] For the coherent accumulation signal after energy superposition, compression enhancement focusing and parameter calculation can be achieved through frequency domain transformation, thereby obtaining the deskewing pulse amplitude spectrum.

[0088] In one implementation, such as Figure 6 As shown, converting the coherent accumulated signal to the frequency domain and determining the descrambling pulse amplitude spectrum includes: Step S401: Perform a Fourier transform on the coherent accumulated signal to determine the spectrum of the continuous descrambling pulse; Step S402: Take the absolute value of the spectrum of the continuous descrambling pulse to determine the amplitude spectrum of the descrambling pulse.

[0089] For the obtained coherent accumulation signal It can be represented as Perform a Fourier transform on the coherent accumulated signal to obtain A continuous descrambling pulse spectrum : , in, For the frequency domain signal term of the continuous descrambled pulse spectrum, for Frequency domain noise after convolution.

[0090] The obtained continuous deslope pulse spectrum Taking the absolute value yields the descrambled pulse amplitude spectrum. : , in, For the signal term of the descrambled pulse amplitude spectrum, This is the noise term in the descrambled pulse amplitude spectrum.

[0091] Step S500: Target detection is performed based on the deslanted pulse amplitude spectrum to determine the target detection result.

[0092] Target detection based on the descrambled pulse amplitude spectrum involves identifying peaks formed by the focusing of the target signal within the amplitude spectrum, and then distinguishing these peaks from noise or clutter peaks using threshold decision and clutter suppression algorithms. The target signal corresponds to a sharp peak in the descrambled pulse amplitude spectrum, with the peak position corresponding to the intermediate frequency (IF), which can be converted into target distance. The target peak amplitude is significantly higher than the background noise amplitude; if multiple targets are present, the descrambled pulse amplitude spectrum will exhibit multiple independent peaks. The bandwidth of the target peak is determined by the number of Fast Fourier Transform (FFT) points and the signal coherence.

[0093] The key to target detection is accurately estimating the amplitude level of background noise or clutter to provide a basis for threshold decision. Common methods include: global noise estimation, which calculates the mean and standard deviation of all points in the descrambled pulse amplitude spectrum, suitable for scenarios with uniform background noise (such as distant clutter-free areas); and local sliding window noise estimation, which takes a local window (e.g., N points to the left and right) around each detection point in the descrambled pulse amplitude spectrum and calculates the mean and standard deviation of the amplitude within the window, suitable for scenarios with non-uniform clutter (such as near-range ground clutter or sea clutter), and can adaptively track local clutter changes to avoid thresholds that are too high or too low due to global estimation.

[0094] Based on the noise estimation results, threshold decision and target peak detection are performed. Fixed threshold decision is based on the noise estimation results, setting a detection threshold. If a point in the amplitude spectrum is greater than or equal to the threshold, it is determined that a target exists at that point.

[0095] In one implementation, due to the coherent accumulation gain in the descrambling pulse amplitude spectrum, the peak may broaden into multiple adjacent points exceeding a threshold. A clustering algorithm can be used to merge adjacent peaks into a single target, avoiding duplicate counting. For example, if the distance between adjacent points exceeding the threshold is less than the distance resolution... , it is determined as the same target.

[0096] Based on the obtained peak detection results, target parameter calculation and verification are performed. First, distance calculation is carried out based on the peak, the frequency is extracted from the target peak position, and the target absolute distance is calculated; the target peak amplitude is recorded, and the radar cross section (RCS) of the target is inversely deduced in combination with the radar equation, and false targets with abnormal amplitudes (such as noise spikes) are eliminated. The detection results of multiple frames of amplitude spectra are correlated, and only the targets that appear in multiple consecutive frames are retained to further reduce the false alarm probability.

[0097] In one implementation, as Figure 7 shown, target detection is performed according to the deskewed pulse amplitude spectrum to determine the target detection result, including: Step S501, construct a binary hypothesis testing model; Step S502, perform target detection according to the deskewed pulse amplitude spectrum and the binary hypothesis testing model to determine the target detection result.

[0098] Binary hypothesis testing is to put forward two mutually exclusive hypotheses (null hypothesis and alternative hypothesis) for a population parameter or the distribution characteristics of a random variable, judge the hypotheses through sample data, and finally choose to accept one hypothesis and reject the other hypothesis.

[0099] In binary hypothesis testing, there are only two hypotheses, denoted as and respectively, and the two are completely mutually exclusive and exhaust all possibilities.

[0100] Null hypothesis ( , zero hypothesis): Usually it is the hypothesis of no difference, no effect, and no signal, and it is the benchmark for testing. Examples: In radar detection, the target does not exist; in product detection, the product is qualified, etc. In this embodiment, the null hypothesis is set, that is means that there is only the noise term in the deskewed pulse amplitude spectrum . Alternative hypothesis ( , alternative hypothesis): The hypothesis opposite to the null hypothesis, usually it is the hypothesis of difference, effect, and signal existence. Examples: In radar detection, the target exists; in product detection, the product is unqualified, etc. In this embodiment, the alternative hypothesis is set, that is means that the deskewed pulse amplitude spectrum contains the target signal and the noise term .

[0101] In one implementation, the binary hypothesis testing model is expressed as: , where For likelihood ratio, The descrambled pulse amplitude spectrum, To set the detection threshold, the false alarm probability should be set as needed. This indicates that the descrambled pulse amplitude spectrum contains a target. This indicates that the descrambled pulse amplitude spectrum contains only noise. It is a combination of greater than or equal to and less than or equal to.

[0102] The performance of the proposed detector was verified using real radar data. The radar carrier frequency was 11.5 GHz, the pulse repetition frequency was 100 Hz, the bandwidth was 3 GHz, and the corresponding range resolution was 0.05 meters.

[0103] The target detected was an aircraft, approximately 37 meters in length. Each High Resolution Range Image (HRRP) contained 2048 range cells. This dataset had a high signal-to-noise ratio (SNR), estimated at 25.2 dB. For performance evaluation, additive white Gaussian noise (AWGN) with varying variances was added to the de-skewed pulses. The receiver operating characteristic (ROC) curve was obtained using 3500 pulses. Figure 8 and Figure 9 As shown, where, Figure 8 It is a comparison of the amplitude spectra of deskewing pulses under different convolution orders. Figure 8 (a) is the high-resolution range image of the first pulse. Figure 8 (b) represents the convolution of the first three pulses. The deslope pulse amplitude spectrum, Figure 8 (c) represents the convolution of the first six pulses. The deslope pulse amplitude spectrum. Figure 9 This compares the performance of traditional integral detectors (ID), spatial scattering density (SSD) detectors, and our proposed method at different convolution orders. The false alarm probability is set to... When the number of iterations At that time, the proposed detector's detection signal-to-noise ratio threshold was approximately 6 dB lower than that of the spatial scattering density detector and approximately 7 dB lower than that of the conventional integral detector. Increasing the threshold from 2 to 5 further reduces the detection threshold by 2.5 dB, at the cost of increased computational burden and longer pulse accumulation time.

[0104] Based on the above embodiments, the present invention also provides a broadband radar range-extended target detection device, such as... Figure 10 As shown, the device includes: Signal acquisition module 01 is used to acquire the radio frequency signals of each linear frequency modulated pulse transmitted by the radar; The deskewing processing module 02 is used to perform pulse compression on each of the linear frequency modulated pulse radio frequency signals in the stop-and-go mode, and to determine each deskewing processing signal. The coherent accumulation module 03 is used to accumulate coherent energy based on each of the deskewing processing signals and determine the coherent accumulation signal; Frequency domain conversion module 04 is used to convert the coherent accumulated signal to the frequency domain and determine the descrambling pulse amplitude spectrum; The target detection module 05 is used to perform target detection based on the deslant pulse amplitude spectrum and determine the target detection result.

[0105] In one implementation, the signal acquisition module 01 includes: A linear frequency modulated pulse acquisition unit is used to acquire linear frequency modulated pulses transmitted by the radar. The carrier frequency signal modulation unit is used to modulate the carrier frequency signal based on the pulse complex envelope of the linear frequency modulated pulse to determine the linear frequency modulated pulse radio frequency signal.

[0106] In one implementation, the linear frequency modulated pulse acquisition unit includes a pulse complex envelope representation unit, wherein the pulse complex envelope representation unit includes: , in, It has a rectangular pulse shape. It is a rectangular pulse function. For the variables of the rectangular pulse function, The pulse width. For phase terms, For frequency modulation slope, For time variables, It is the imaginary unit.

[0107] In one implementation, the carrier signal modulation unit includes a linear frequency modulated pulse radio frequency signal representation unit, the linear frequency modulated pulse radio frequency signal representation unit comprising: , in, The linear frequency modulated pulse radio frequency signal is... The carrier frequency signal, To save time, This is the index of the transmitted pulses within a coherent processing interval. For all times, For slow time, This is the pulse repetition interval.

[0108] In one implementation, the de-skew processing module 02 includes: A stop-and-go mode signal determination unit is used to determine each of the linear frequency modulated pulse radio frequency signals in the stop-and-go mode; The pulse deskewing processing unit is used to acquire a local reference signal, and to perform pulse compression on each of the linear frequency modulated pulse radio frequency signals in the stop-and-go mode based on the local reference signal to determine each of the deskewing processing signals.

[0109] In one implementation, the stop-and-go mode signal determination unit includes a stop-and-go mode signal representation unit, the stop-and-go mode signal representation unit comprising: , in, For slow time The corresponding linear frequency modulated pulse radio frequency signal, The number of scattering points. For the first The scattering coefficient at each scattering point It is additive white Gaussian noise. This is to delay the round-trip time.

[0110] In one implementation, the pulse descrambling processing unit includes a local reference signal representation unit, which includes: , in, For time variables The corresponding local reference signal, Indicates the length of the receiving window.

[0111] In one implementation, the pulse deskewing processing unit includes a deskewing processing signal representation unit, the deskewing processing signal representation unit comprising:

[0112] in, For slow time The corresponding descrambling signal, The signal item corresponding to the descrambling signal. This refers to the noise term corresponding to the descrambling signal.

[0113] In one implementation, the coherent accumulation module 03 includes: An initial convolutional unit is used to convolve each of the deskewing signals with the adjacent deskewing signals to determine each energy accumulation signal; An iterative convolution unit is used to iteratively perform the step of convolving each energy accumulation signal with the adjacent energy accumulation signals for a preset number of iterations to obtain updated energy accumulation signals. The coherent accumulation signal determination unit is used to take the updated energy accumulation signal corresponding to the preset iteration number as the coherent accumulation signal.

[0114] In one implementation, the iterative convolutional unit includes: The updated energy accumulation signal determination unit is used to determine the first... The energy accumulation signal corresponding to each slow time The adjacent first The energy accumulation signal corresponding to each slow time Perform convolution to obtain the updated energy accumulation signal. , is represented as: , in, This represents the convolution operator. For the signal term corresponding to the updated energy accumulation signal, The noise term corresponding to the updated energy accumulation signal. This represents the current iteration number. This indicates a definition.

[0115] In one implementation, the frequency domain conversion module 04 includes: The Fourier transform unit is used to perform Fourier transform on the coherent accumulated signal to determine the spectrum of the continuous descrambling pulse; The absolute value unit is used to take the absolute value of the spectrum of the continuous descrambling pulse to determine the amplitude spectrum of the descrambling pulse.

[0116] In one implementation, the target detection module 05 includes: Binary hypothesis testing model building unit, used to build binary hypothesis testing models; The target detection unit is used to perform target detection based on the deslanted pulse amplitude spectrum and the binary hypothesis testing model, and to determine the target detection result.

[0117] In one implementation, the binary hypothesis testing model construction unit includes a binary hypothesis testing model representation unit, wherein the binary hypothesis testing model representation unit includes: , in, For likelihood ratio, The descrambled pulse amplitude spectrum, To detect threshold, This indicates that the descrambled pulse amplitude spectrum contains a target. This indicates that the descrambled pulse amplitude spectrum contains only noise. It is a combination of greater than or equal to and less than or equal to.

[0118] Based on the above embodiments, the present invention also provides a terminal, the principle block diagram of which can be as follows: Figure 11 As shown, the terminal includes a processor, memory, network interface, and display screen connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a broadband radar range-extended target detection method. The display screen can be a liquid crystal display (LCD) or an e-ink display.

[0119] Those skilled in the art will understand that Figure 11 The schematic diagram shown is merely a partial structural diagram related to the present invention and does not constitute a limitation on the terminal to which the present invention is applied. A specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0120] In one implementation, the terminal's memory stores one or more programs, and these programs are configured to be executed by one or more processors, and the programs contain instructions for performing a broadband radar range-extended target detection method.

[0121] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0122] In summary, this invention discloses a broadband radar range-extended target detection method, apparatus, terminal, and medium. The method acquires each linear frequency modulated (LFM) pulse radio frequency (RF) signal transmitted by the radar; in a stop-and-go mode, pulse de-chewing processing is used to compress each LFM pulse RF signal to determine each de-chewing processed signal; coherent energy accumulation is performed based on each de-chewing processed signal to determine a coherent accumulated signal; the coherent accumulated signal is converted to the frequency domain to determine the de-chewing pulse amplitude spectrum; and target detection is performed based on the de-chewing pulse amplitude spectrum to determine the target detection result. Because this invention performs pulse de-chewing processing and coherent energy accumulation on each received LFM pulse RF signal to obtain a coherent accumulated signal for subsequent target detection, it can effectively solve the problem of existing methods that struggle to achieve good noise immunity with minimal computation when the signal-to-noise ratio decreases.

[0123] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for wideband radar range expansion target detection, characterized in that, The method comprises: acquiring each linear frequency modulation pulse radio frequency signal transmitted by a radar; in a walk-stop mode, performing pulse compression on each linear frequency modulation pulse radio frequency signal by using pulse dechirp processing to determine each dechirp processed signal; performing coherent energy accumulation according to each dechirp processed signal to determine a coherent accumulation signal; converting the coherent accumulation signal to a frequency domain to determine a dechirp pulse amplitude spectrum; performing target detection according to the dechirp pulse amplitude spectrum to determine a target detection result.

2. The wideband radar range extension target detection method of claim 1, wherein, The method comprises: acquiring each linear frequency modulation pulse radio frequency signal transmitted by a radar; modulating a carrier frequency signal based on a pulse complex envelope of the linear frequency modulation pulse to determine the linear frequency modulation pulse radio frequency signal.

3. The wideband radar range extension target detection method of claim 2, wherein, The pulse complex envelope of the linear frequency modulation pulse is expressed as: ， wherein is a rectangular pulse shape, is a rectangular pulse function, is a variable of the rectangular pulse function, is a pulse width, is a phase term, is a frequency modulation slope, is a time variable, is an imaginary unit.

4. The wideband radar range extension target detection method of claim 3, wherein, The linear frequency modulation pulse radio frequency signal is expressed as: ， wherein, is the linear frequency modulated radio frequency signal, is the carrier frequency signal, is the fast time, is the index of the transmitted pulse within a coherent processing interval, is the total time, is the slow time, is the pulse repetition interval.

5. The wideband radar range extension target detection method of claim 4, wherein, in a walk-stop mode, performing pulse compression on each linear frequency modulation pulse radio frequency signal by using pulse dechirp processing to determine each dechirp processed signal, which comprises: determining each linear frequency modulation pulse radio frequency signal in the walk-stop mode; acquiring a local reference signal and performing pulse compression on each linear frequency modulation pulse radio frequency signal in the walk-stop mode according to the local reference signal by using pulse dechirp processing to determine each dechirp processed signal.

6. The wideband radar range extension target detection method of claim 5, wherein, Each linear frequency modulation pulse radio frequency signal in the walk-stop mode is expressed as: ， wherein, is a slow time corresponding to the linear frequency modulated radio frequency signal, is a number of scattering points, is a scattering coefficient of the scattering point, is a complex additive white Gaussian noise, is a round trip time delay.

7. The wideband radar range extension target detection method of claim 6, wherein, The local reference signal is expressed as: ， wherein, is a time variable corresponding said local reference signal, denotes a receive window length.

8. The wideband radar range extension target detection method of claim 7, wherein, The dechirp processed signal is expressed as: wherein is a slow time corresponding to the deskewed signal, is a signal term corresponding to the deskewed signal, is a noise term corresponding to the deskewed signal.

9. The wideband radar range extension target detection method of claim 1, wherein, performing coherent energy accumulation according to each dechirp processed signal to determine a coherent accumulation signal, which comprises: convolving each dechirp processed signal with an adjacent dechirp processed signal to determine each energy accumulation signal; iteratively performing the step of convolving each energy accumulation signal with an adjacent energy accumulation signal for a preset number of iterations to obtain each updated energy accumulation signal; taking the updated energy accumulation signal corresponding to the first preset number of iterations as the coherent accumulation signal.

10. The wideband radar range extension target detection method of claim 9, wherein, convolving each energy accumulation signal with an adjacent energy accumulation signal to obtain each updated energy accumulation signal, which comprises: convolve the energy accumulation signal corresponding to the first slow time with the energy accumulation signal corresponding to the first slow time adjacent to it, to obtain an updated energy accumulation signal corresponding to the first slow time, denoted as ​ ， wherein denotes a convolution operator, is a signal term corresponding to the updated energy accumulation signal, is a noise term corresponding to the updated energy accumulation signal, is the current iteration number, denotes a definition.

11. The wideband radar range extension target detection method of claim 1, wherein, converting the coherent accumulation signal to a frequency domain to determine a dechirp pulse amplitude spectrum, which comprises: performing Fourier transform on the coherent accumulation signal to determine a continuous dechirp pulse spectrum; taking an absolute value of the continuous dechirp pulse spectrum to determine the dechirp pulse amplitude spectrum.

12. The wideband radar range extension target detection method of claim 1, wherein, performing target detection according to the dechirp pulse amplitude spectrum to determine a target detection result, which comprises: constructing a binary hypothesis testing model; performing target detection according to the dechirp pulse amplitude spectrum and the binary hypothesis testing model to determine the target detection result.

13. The wideband radar range extension target detection method of claim 12, wherein, The binary hypothesis testing model is expressed as: ， wherein, is a likelihood ratio, is the dechirped pulse amplitude spectrum, is a detection threshold, indicates that the dechirped pulse amplitude spectrum contains a target, indicates that the dechirped pulse amplitude spectrum contains only noise, is a combination of greater than or equal to and less than or equal to.

14. A wideband radar range expansion target detection apparatus, characterized by comprising: The apparatus comprises: a signal acquisition module configured to acquire each linear frequency modulation pulse radio frequency signal transmitted by a radar; a dechirp processing module configured to, in a walk-stop mode, perform pulse compression on each linear frequency modulation pulse radio frequency signal by using pulse dechirp processing to determine each dechirp processed signal; a coherent accumulation module configured to perform coherent energy accumulation according to each dechirp processed signal to determine a coherent accumulation signal; a frequency domain conversion module configured to convert the coherent accumulation signal to a frequency domain to determine a dechirp pulse amplitude spectrum; A target detection module is configured to perform target detection according to the dechirped pulse amplitude spectrum to obtain a target detection result.

15. A terminal, characterized by The terminal comprises a memory and one or more processors; the memory stores one or more programs; the programs contain instructions for executing the wideband radar range expansion target detection method according to any one of claims 1-13; and the processors are configured to execute the programs.

16. A computer readable storage medium having stored thereon a plurality of instructions, the plurality of instructions comprising: The instructions are loaded and executed by the processor to implement the steps of the wideband radar range expansion target detection method according to any one of claims 1-13.

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