451 results about "Radar signal processing" patented technology

The application discloses an improved radar two-dimensional ambiguity resolution method for multi-targets, comprising the following steps: arranging point trail data after radar signal processing according to pulse repetition period from small to large; constructing a reference lookup table for resolving range ambiguity based on the arranged data; constructing a reference lookup table for resolving velocity ambiguity based on the arranged data; traversing all the frequency combinations of radar transmission, selecting N groups from M groups of frequency for multi-target pairing; obtaining a range pairing table based on the reference lookup table for resolving range ambiguity, calculating the standard deviation between rows of the range pairing table, and solving the real range of targets; obtaining a velocity pairing table based on the reference lookup table for resolving velocity ambiguity, calculating the standard deviation between rows of the velocity pairing table, and solving the real velocity of targets; and merging and processing output target data. The application can solve the problem that the traditional one-dimensional set method cannot meet the real-time requirement when the number of targets is large and the ambiguity is large.

The invention discloses a radar moving target parameter preprocessing method and system based on classification, and relates to the technical field of radar signal processing. The method comprises the following steps: constructing a signal model for a radar moving target needing to be identified and processed in a region of interest for simulation, and establishing a moving target signal data set; classifying according to the motion condition of the moving target in the moving target signal data set, preprocessing the moving target signal according to a classification result, and obtaining feature information in a corresponding category; taking the feature information as sample data, and training a classification model through the sample data to obtain a trained classification model; and inputting a to-be-processed moving target signal into the trained classification model for classification and identification, and obtaining a corresponding classification test result. The method can effectively reduce the calculation amount, improve the parameter estimation speed and save calculation resources.

The invention relates to the technical field of radar signal processing, in particular to a ground penetrating radar reinforcing steel bar clutter suppression method based on physical constraints, and mainly solves the problem that a data set is difficult to obtain in an existing ground penetrating radar reinforcing steel bar clutter removal method based on deep learning. The method is an improved method based on the CUT network, the CUT network structure and a comparative learning mechanism determine that the requirement of the network for the data size of a data set is low, a waveform smoothness constraint is added on this basis, the clutter removal effect and generalization ability are improved by introducing physical prior, the physical constraint serves as a regularization item, and the regularization efficiency is improved. The problem that a CUT network is prone to model collapse under a small data set is solved. Finally, the improved model is compared with other models through different evaluation indexes, and the result shows that the improved model has more advantages.

The invention discloses a narrowband-broadband intelligent switching method of a radar, and belongs to the field of radar signal processing. Single radar wide-narrow band function integration is achieved through resource multiplexing, self-adaptive triggering and dynamic parameter configuration, detection tracking in a default narrow band mode is achieved, switching is triggered based on manual instructions and double thresholds, hardware such as a common antenna and a T / R assembly is reconstructed through time division multiplexing and software parameters, the signal synchronization time is shortened, and the target tracking response delay time is shortened; double-radar collaborative design is not needed, and the design workload is reduced. According to the invention, double radars are combined into a single radar, the hardware cost is greatly reduced, and the method is suitable for unmanned aerial vehicle-mounted, vehicle-mounted and other space-limited scenes and military reconnaissance, civil security and protection and other tasks.

Disclosed herein are an FFT processor, an FFT computing method, a radar signal processing system-on-chip, an integrated circuit, and an electromagnetic wave sensor. The FFT processor comprises two cascaded FFT kernels, and the FFT processor has at least two operating modes among a large-point-number FFT mode, a pipeline mode and an independent parallel mode, wherein when the FFT processor is in the large-point-number FFT mode, the two FFT kernels are configured to decompose FFT of N points into two instances of FFT; when the FFT processor is in the pipeline mode, the former FFT kernel of the two cascaded FFT kernels is configured to perform distance FFT, and the latter FFT kernel of the two cascaded FFT kernels is configured to perform Doppler FFT; and when the FFT processor is in the independent parallel mode, the two FFT kernels are configured to independently process data of different channels in parallel.

The invention discloses a phased array radar signal processing system with deterministic delay, and relates to the technical field of semiconductors, the system carries out equal-length wiring design on a link in a hardware level, a timestamp marking circuit is embedded in the link, a core processing module carries out multi-channel data alignment based on timestamp marks in a software level, and the data alignment is carried out based on the timestamp marks. The multi-channel data transmission delay deviation is solved through elastic buffer control, the most reasonable buffer depth and release phase parameters are determined through calculation, and therefore the buffer delay is minimized, the system achieves deterministic minimum delay through software and hardware collaborative design, data alignment and quick response are guaranteed, and the system is suitable for large-scale popularization and application. Low-delay and high-consistency transmission and processing of multi-channel signals are achieved, so that high-precision pointing control of radar beams and time consistency of multi-target tracking are achieved, and the high-synchronization and low-jitter requirements of phased array radar for high-speed signal processing are met.

The invention discloses a weather radar meteorological echo and non-meteorological echo identification system, and belongs to the technical field of meteorological radar signal processing. The method comprises the following steps: acquiring radar original data containing reflectivity factors, radial velocity and spectral width, and generating a three-dimensional feature matrix through format standardization, combined noise removal, neighborhood interpolation filling and parameter normalization; constructing a sample set through professional labeling, consistency verification and multi-dimensional data enhancement; a deep convolutional neural network containing a ResNet50 feature extraction module, a CBAM double attention module and a classification output module is constructed, and a binary cross entropy loss function, an Adam optimizer and an early stop regularization strategy are adopted for training optimization; to-be-recognized data is preprocessed and then input into the model, and a classification result and confidence are output. The method does not need manual feature design, significantly improves the recognition stability of echoes difficult to distinguish in a complex scene, adapts to different radars and regional environments, and meets the real-time processing requirements.

The invention relates to the technical field of radar signal processing, in particular to an urban environment low, small and slow target radar clutter suppression method, which comprises the following steps of: 1, acquiring and decomposing a signal; step 2, adaptive clutter cancellation; step 3, space-time combined treatment; step 4, constant false alarm rate detection; step 5, fine classification and identification; step 6, target tracking and early warning; according to the method, a cascade processing framework integrating multi-scale signal decomposition, adaptive filtering, space-time combined processing and intelligent identification is constructed, so that the defect that the performance of a traditional method is sharply reduced in a city strong non-uniform and non-stationary clutter environment is effectively overcome; and in combination with a recursive least square filter with dynamically adjustable parameters, the combined suppression capability of static ground clutter and dynamic traffic interference is remarkably improved, so that the detection of a'low, small and slow 'target under the condition of an extremely low signal-to-clutter ratio becomes possible.

The invention discloses a pulse compression radar accelerator generation method based on model driving, and relates to the technical field of pulse radars, and the method comprises the steps: based on a pulse compression radar signal processing flow, splitting operators according to calculation, interconnection and storage dimensions, and extracting features; defining 9 types of core components to form a parameterized component library; the components and the connection relation are combined, and an architecture description graph in a JSON format is generated; analyzing the ADG through an architecture interpreter to obtain a standardized parameter, and generating an RTL code based on a Chisel hierarchical architecture; performing simulation verification on the RTL code, pre-estimating the resource if the simulation verification is passed, and returning an error if the simulation verification is not passed; injecting expert configuration and combining with Latin hypercube sampling to obtain an initial solution set, iteratively searching a high-quality solution cluster by a TPE algorithm, resetting a parameter boundary and then switching to an ILS algorithm, and combining with a hardware rule to obtain a global optimal solution; and repeatedly executing the steps until the end conditions that the resources reach the standard and iteration reaches the upper limit are met, and outputting the accelerator architecture with the optimal resources under the target application constraint and the complete RTL code.

The invention belongs to the field of laser radar signal processing, and provides a method and system for inverting vertical visibility based on a Mie scattering laser radar, and the method comprises the following steps: S1, obtaining a signal; s2, signal preprocessing, which sequentially comprises background noise correction, overlap factor correction, distance square correction, de-noising processing and normalization; and S3, vertical visibility inversion, including construction, training and use of a DBO-BP optimization neural network model. The system comprises a Mie scattering laser radar, a data preprocessing module and a DBO-BP optimization neural network model module. According to the method, physical characteristics and data characteristics of original echo signals are taken into consideration during inversion of the vertical visibility, the anti-noise performance is remarkably enhanced through multiple times of denoising during signal preprocessing, and efficiency and precision are balanced by adopting a hierarchical iteration strategy during model training.

The invention discloses a phased array radar digital beam forming system, and belongs to the technical field of radar signal processing, and the system comprises a radar central processing and dynamic scheduling subsystem which is used for carrying out the real-time dynamic scheduling control of all subsystems according to external environment parameters; the time sequence synchronous control subsystem is used for receiving a scheduling instruction of the central processing unit and generating a whole-system reference clock and a key time sequence signal; the data transmission and preprocessing subsystem is used for transmitting and preprocessing the data; the long and short pulse cooperative processing and target detection subsystem is used for receiving the preprocessed baseband data stream and executing pulse analysis and target extraction; and the target information extraction and real-time display control interface is used for uploading the processed data in real time and displaying target related information in real time. Through physical complementation of the long and short pulses and extension of the detection distance, full-distance continuous high-precision detection is realized, and through distance-direction dynamic fusion of the long and short pulse data, a distance fault of a traditional scheme is eliminated.

The embodiment of the invention provides a near-field MIMO radar data processing method based on multistage background suppression and target enhancement, and is applied to the technical field of radar signal processing. The method comprises the following steps: acquiring a real-time background template and a real-time image frame of a target scene; calculating to obtain differential image data corresponding to the real-time image frame based on the real-time background template and the real-time image frame; performing Gaussian filtering processing on the difference image data to obtain Gaussian filtering image data; performing morphological processing on the Gaussian filtering image data to obtain morphological image data; performing target enhancement processing on the morphological image data to obtain target enhanced image data corresponding to the real-time image frame; and outputting the target enhanced image data. The technical effect of improving the radar imaging precision is achieved.

The invention relates to the technical field of radar signal processing, and discloses an anti-multipath interference vehicle-mounted millimeter wave radar signal processing method, and the method comprises the steps: obtaining a radar echo signal, and decomposing the radar echo signal into a plurality of overlapped sub-band signals in a frequency domain; constructing a static environment Doppler manifold curved surface by using self-vehicle motion data, and calculating a theoretical phase evolution model according to the static environment Doppler manifold curved surface; extracting an actual measurement phase difference between the sub-bands, and carrying out coherent accumulation on the actual measurement phase difference and the theoretical model to generate a manifold consistency coherence coefficient; direction-of-arrival estimation is carried out on each sub-band signal, and the spatial spectrum drift statistical dispersion of an angle estimation value is calculated; and generating a target multipath confidence score according to the manifold consistency coherence coefficient and the spatial spectrum drift statistical dispersion, and executing a suppression decision on a radar detection target. According to the invention, by introducing a kinematics physical constraint and broadband space stability detection mechanism, false targets generated by a multipath effect are effectively identified and eliminated, and the environmental perception precision and robustness of the vehicle-mounted radar are improved.

The invention relates to a method for preventing and monitoring blood pressure based on terahertz radar electrocardiogram heart rate variation parameters, and belongs to the field of terahertz radar signal processing. The method comprises the steps that a human thoracic cavity micro-motion signal is collected through a terahertz radar, an intermediate frequency signal is obtained through ADC sampling, distance dimension Fourier transform and phase unwrapping processing are carried out, and a target object is obtained; extracting a chest displacement signal containing heartbeat information; band-pass filtering is adopted to preliminarily separate respiration and heartbeat signals, and variation mode decomposition optimized by an ant colony algorithm is introduced to effectively suppress respiration harmonic interference; inputting the heartbeat signal into a multi-modal deep learning framework fusing a convolutional neural network, a long-short-term memory network and a multi-head attention mechanism to realize end-to-end high-precision reconstruction from a radar mechanical vibration signal to a standard electrocardio waveform; r peak detection is conducted on the reconstructed radar ECG signals, and time domain and frequency domain heart rate variability parameters are calculated and used for evaluating the autonomic nerve function state. The method has the effect of improving the monitoring comfort of special crowds.

The invention provides a translation compensation method for an inverse synthetic aperture radar image of a non-cooperative target, and relates to the technical field of radar signal processing and radar imaging, and the method comprises the steps: carrying out the calculation of a target motion and a radar echo signal based on the inverse synthetic aperture radar image of the non-cooperative target, and obtaining a receiving signal; filtering the received signal to obtain a high-resolution range profile sequence; obtaining a motion offset prediction model by using a spatial feature extraction module and a time sequence decoding module; processing the high-resolution range profile sequence by using the trained motion offset prediction model to obtain a translation offset estimation sequence; and constructing a translation compensation item by using the translation offset estimation sequence, performing translation compensation on the compressed echo to obtain a translation compensation result, and completing envelope and phase joint compensation and inverse synthetic aperture radar imaging. According to the method, the problem of translational motion compensation caused by uncertainty and complexity of a non-cooperative target motion mode is solved.

The application is suitable for the technical field of radar signal processing, and provides a deep unfolding ISAR super-resolution imaging method based on sparse-neighborhood joint constraint, comprising: firstly, constructing an ISAR image degradation model, constructing an ISAR super-resolution imaging problem based on the ISAR degradation model and the compressed sensing theory, using ADMM to solve the ISAR super-resolution imaging problem, unfolding the process of solving the ISAR super-resolution imaging problem by ADMM into a multi-level neural network, and finally inputting low-resolution ISAR echoes into the trained neural network to obtain an ISAR super-resolution imaging result. The application combines sparse constraint and neighborhood amplitude constraint, deduces a corresponding signal model and an ADMM solving algorithm, effectively improves the reconstruction ability of the algorithm to complex target details and the representation ability of the algorithm to structural information, and can realize effective super-resolution imaging based on narrowband short-aperture echoes.

The application belongs to the technical field of radar signal processing and imaging, and provides a differential coupling single-frequency time-varying low-quantization imaging method, which comprises receiving a SAR echo signal, constructing a single-frequency time-varying threshold signal, single-bit quantization processing of a reference channel, single-bit quantization processing of a phase shift channel, double-channel data fusion and harmonic cancellation, and imaging processing based on a synthesized signal. The application effectively reduces the quantization noise base and improves the detection capability of a SAR system on weak targets under the premise of not significantly increasing the hardware cost.

The present application relates to the technical field of radar signal processing, aiming at the target positioning and imaging ambiguity caused by the distance-angle coupling of the traditional frequency diversity array beam pattern, and the problem that more array elements are needed for random frequency offset to remove ambiguity, a FDA structure based on joint design of intra-array frequency offset and inter-array frequency offset is proposed, the transmission energy is focused on the expected distance-angle area to realize distance-angle decoupling, and by increasing the number of intra-array frequency increments, the number of array elements is increased to improve the target ambiguity-free limit, the number of frequency increments is increased from N of the traditional FDA to, the order of magnitude of the ambiguity-free limit can be greatly increased, and the tolerance of the target ambiguity-free limit is greater. By optimizing the parameters of the array element and inter-array frequency offset design, the de-ambiguous imaging can be realized without complex imaging algorithm.

The invention belongs to the technical field of radar signal processing and electromagnetic target characteristic analysis, and particularly relates to an extended target scattering modeling method for a broadband multistatic radar system. According to the method, for aircrafts with complex motion characteristics such as unmanned aerial vehicles and missiles, a unified scattering model under various motion types is established, and multi-base geometric modeling, broadband signal expression and coupling modeling of various target motion mechanisms are introduced; accurate simulation and feature extraction of target scattering characteristics under any transmitting-receiving geometric condition are realized, and a basis is provided for subsequent target identification and parameter inversion.

The invention relates to the technical field of radar signal processing, and discloses a vehicle-mounted radar anti-interference method and system based on time-frequency-space three-dimensional adaptive sampling. Aiming at the problems of low detection efficiency and unreasonable sampling resource allocation in a multi-interference-source scene, interference is accurately identified by constructing a time-frequency-space three-dimensional joint interference feature tensor and utilizing a three-dimensional cross coupling effect; local sampling density is dynamically adjusted based on interference intensity and gradient information thereof, sampling is adaptively increased in an interference dense and boundary region, and high-precision reconstruction is performed on non-uniform sampling signals by using a compressed sensing algorithm. According to the method, the interference identification accuracy under the complex electromagnetic environment is effectively improved, the target detection performance is ensured, meanwhile, the system data throughput and the calculation overhead are remarkably reduced, and the method is suitable for a high-performance vehicle-mounted radar system.

The invention provides an intermediate frequency signal processing unit for generating a radio frequency characteristic simulation decoy signal, which belongs to the field of radar signal processing, and comprises a signal receiving and parameter measuring module for completing orthogonal frequency mixing, detection, DDC and extraction on a target radar signal, pulse time domain parameter measurement, frequency measurement and intra-pulse parameter measurement are carried out on the signals to obtain detection signals, PDW information and frequency information; the matching tracking module is used for filtering irrelevant pulses in a signal environment according to the detection signals, the PDW information and tracking parameters, and performing frequency matching and PRI tracking on the received detection signals; the time sequence control module is used for generating time sequence control parameters and time sequence control signals according to the working parameters, the detection signals and the tracking gate; the signal storing and playing module is used for storing and playing the target radar signal according to the time sequence control signal; and the decoy interference generation module is used for generating a decoy interference signal according to the target radar signal, the frequency information and the time sequence control parameter.

The invention relates to radar signal processing, in particular to a clutter suppression method and system based on a track clutter map, and the method comprises the steps: collecting initial track data at the initial starting stage of a radar, and carrying out the preprocessing, thereby obtaining an effective track set; according to motion features and morphological features of clutter tracks, clutter tracks are screened out from the effective track set, and a clutter track set is obtained; the space distribution characteristics of the clutter track set are quantified into a probabilistic track clutter map, and precise representation of clutter space distribution and confidence is achieved; updating the track clutter map in real time by adopting a sliding window to ensure that the track clutter map can accurately represent a dynamic clutter environment all the time; performing grading processing on the new track based on grading judgment of a high-confidence clutter area coverage proportion; the matching degree of the new track and the clutter track is quantified from two dimensions of a space path and a motion feature, and accurate clutter judgment is realized; the method can effectively overcome the defect that a radar detection system is difficult to effectively suppress clutters in a complex urban environment.

The invention discloses an intelligent heterogeneous radar hardware accelerator applied to rail transit, and belongs to the technical field of radar signal processing and integrated circuits. The accelerator is based on an SoC FPGA platform, a microprocessor soft core based on an RISC-V instruction set is constructed at an FPGA end, and an FFT calculation module and a CFAR calculation module are integrated to serve as hardware acceleration units. And the microprocessor soft core dynamically schedules each hardware acceleration unit by executing a program stored in the instruction memory, constructs a reconfigurable data path, and completes a radar signal processing flow. The method overcomes the defects of power consumption, communication bandwidth and flexibility of traditional DSP and FPGA schemes, and is particularly suitable for efficient and real-time detection and identification of roadbed structure damage in rail transit.

The invention provides a radar intra-pulse modulation signal waveform inversion method and device, and relates to the technical field of radar signal processing, and the method comprises the steps: obtaining a signal parameter; generating an intermediate frequency signal for the signal parameter according to the signal generation function, and performing short-time Fourier transform on the intermediate frequency signal to generate a time-frequency diagram; respectively calculating a time range and a frequency range based on waveform parameters of the intermediate frequency signal, and respectively normalizing the time range and the frequency range into a coordinate range of a time-frequency diagram to obtain a detection label; according to the target detection model, training the time-frequency diagram through detection labels, and carrying out positive and negative sample distribution based on a Hungary matching strategy to obtain an improved target detection model; performing unknown parameter target detection on the time-frequency graph based on an improved target detection model to obtain a detection result; and performing inversion processing on the intermediate frequency signal based on the detection result to obtain an inversion result. According to the invention, the problem that the recognition accuracy is greatly reduced is solved.

The application discloses a kind of distributed array high-precision time synchronization method based on compressed sensing (CS) and secondary least square (QLS), belong to wireless communication and radar signal processing technical field.For under the restriction hardware bandwidth and strong multipath environment, traditional cross-correlation method is limited by Rayleigh resolution and sampling grid, there is the problem of serious peak aliasing, insufficient synchronization accuracy, the application proposes CS-QLS joint decoupling strategy.The method constructs frequency domain observation matrix and high-density time delay over-complete dictionary by transmitting sparse multi-tone probe signal, reconstructs sparse channel impulse response using CS, separates multipath aliasing and determines direct wave coarse synchronization boundary;Further combined with main path and adjacent grid point amplitude information, QLS is used to fit continuous domain peak position, and grid mismatch error is corrected.The method breaks through the limitation of physical bandwidth and sampling grid, and realizes nanosecond-level high-precision time synchronization in complex non-line-of-sight environment with very low computational complexity.

The invention discloses a target micro-Doppler extraction method based on vernier ranging, which belongs to the technical field of radar signal processing, and comprises the following steps: obtaining radar vernier ranging data through first-order and second-order difference; the de-noising effect is verified according to the statistical standard deviation; performing modal decomposition by adopting a CEEMDAN algorithm to obtain an intrinsic mode function matrix and a residual matrix; and Fourier transform is performed on each component, and the frequency corresponding to the maximum amplitude value is extracted as a micro-Doppler frequency value. According to the target micro-Doppler extraction method based on vernier ranging, the high-precision characteristic of vernier ranging and the CEEMDAN anti-aliasing capability are combined, random errors are effectively reduced, the micro-Doppler extraction precision is improved, and the method is adaptive to nonlinear and non-stationary radar signals and is suitable for radar target fine recognition scenes.

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.

An operation method of a radar signal processing apparatus in a radar system may include: generating pulse signals of a number of any one sampling rate having different phases; transmitting the pulse signals to a target; receiving reflected pulse signals reflected back from the target; generating a composite signal by sampling the reflected pulse signals and combining the sampled reflected pulse signals to match the phases; and extracting target information from the composite signal.

The present application relates to radar signal processing technical field, specifically provide a kind of staggered pulse repetition interval time-frequency domain dual-polarized radar detection variable estimation method, comprising: in frequency domain, the estimation of echo signal-to-noise ratio, reflectivity factor, differential reflectivity of horizontal / vertical polarization based on power spectral density;And the estimation of average Doppler velocity and velocity spectrum width;In time domain, after ground clutter filtering based on odd-even pulse, respectively, odd-even pulse correlation parameter estimation is carried out, so that two detection variables of dual-polarized radar correlation coefficient and differential propagation phase shift of odd-even pulse are obtained respectively, then odd-even combination can obtain the estimation result of accurate correlation coefficient and differential propagation phase shift.The present application realizes the accurate estimation of dual-polarized radar multi-class detection variable, ensures that estimation result is not disturbed by ground clutter interference, simultaneously adapts single pulse repetition interval and staggered pulse repetition interval two working modes, improves the reliability and applicability of radar detection.

The application discloses a radar sensing confrontation verification system for a complex electromagnetic environment, which comprises a host computer, a radar signal processor and an environment simulator.The host computer is used for sending initialization binding parameters to the radar signal processor in real time and sending interference types to the environment simulator.The radar signal processor is used for generating radar transmitting signals according to preset waveform parameters.The environment simulator is used for generating target signals according to the received radar transmitting signals, generating interference signals according to the interference types and sending echo signals to the radar signal processor.The radar signal processor is further used for processing the echo signals and adjusting an anti-interference strategy based on a processing result to generate an optimal transmitting waveform.Meanwhile, the radar signal processor returns target detection results and anti-interference effects to the host computer in real time, so that real-time detection of the target is realized.The system can sense various types of interference signals and adaptively adjust the transmitting waveform, so that the radar can adaptively detect the target in a complex and changeable electromagnetic environment and achieve the optimal performance.