1398 results about "Doppler frequency" patented technology

The invention discloses a multi-satellite network converged communication link optimization and anti-interference method, which belongs to the technical field of wireless communication networks, and comprises the following steps: acquiring Doppler frequency shift parameters of satellite nodes, adjacent satellite radiation quantity parameters and preset geographical shielding coefficients, and generating a link dynamic quality coefficient; constructing a dynamic topological graph according to the link dynamic quality coefficient; performing radio frequency fingerprint extraction and frequency domain waveform phase reversal processing on the detected interference signal to generate an anti-interference compensation signal; and when the link dynamic quality coefficient is greater than or equal to a preset quality threshold value, selecting a target transmission path according to the dynamic topological graph, and injecting the anti-interference compensation signal into the target transmission path. According to the invention, a mechanism of cooperation of dynamic link quality evaluation, interference fingerprint feature matching and multi-path fragmentation transmission is adopted, and real-time optimization selection of communication paths, accurate suppression of interference signals and efficient distribution of network resources can be realized in a complex air and space environment.

The invention relates to a low-orbit communication satellite Doppler positioning method and device based on factor graph optimization. The method comprises the following steps: after required observation data is received and an initial state value of a ground receiver is solved, a factor graph framework is introduced to set a priori factor, a Doppler frequency shift factor, a state constraint factor and a state variable consisting of a three-dimensional position and frequency drift of the receiver according to a Doppler positioning observation model; and constructing a Doppler positioning factor graph model by taking the factors and variables as nodes, introducing a sliding window mechanism to update a factor graph in a factor graph optimization solution process, and solving state variables by adopting a Gaussian-Newton algorithm to finally obtain a Doppler positioning result. According to the method, factor graph modeling is carried out on the Doppler positioning observation model, the advantages of nonlinear modeling, global optimization and capability of fully utilizing historical observation of a factor graph optimization method are exerted, and a relatively small positioning error and a higher convergence speed can be obtained.

The invention discloses a space-variant self-focusing imaging method for a missile-borne synthetic aperture radar sea surface moving target. The method comprises the following steps: acquiring a radar fundamental frequency echo signal; performing range pulse pressure and range migration correction on the radar fundamental frequency echo signal to obtain a correction signal, and further obtaining a coarse focusing radar image; extracting a single defocusing target image in the coarse focusing radar image, and inverting the single defocusing target image to an echo data domain to obtain data of single target energy; performing correction to obtain data after correction of the residual range walk; selecting a part of distance units from the data after the residual range walk is corrected, performing Doppler frequency modulation rate estimation on the selected part of distance units by adopting fractional Fourier transform, fitting the estimated Doppler frequency modulation rate by adopting a space-variant phase error model, and constructing a space-variant phase error compensation function of the target; and compensating the data after the correction of the residual range walk, and imaging. According to the invention, the refocusing effect of the moving ship target can be improved.

The invention relates to the technical field of unmanned aerial vehicle autonomous decision, provides an unmanned aerial vehicle autonomous decision reinforcement learning method, system and device based on multi-objective optimization, and a storage medium, and solves the problems of limited dynamic task distribution capability and poor decision capability of an unmanned aerial vehicle. The method comprises the steps that based on infrared data and radar data, a moving track prediction sequence of a suspicious target in a target area is generated, a moving probability thermodynamic diagram is constructed, and the target area comprises a patrolled area; performing Doppler frequency shift analysis on the radar data to generate a target velocity vector field; and in combination with the position data of the unmanned aerial vehicle, outputting an unmanned aerial vehicle autonomous decision reinforcement learning result of a dynamic segmentation scheme containing an unpatrolled region through a region re-division reinforcement learning model based on a reward function for multi-objective optimization. The reward function is used for reflecting area coverage rate maximization, target tracking success probability maximization and path energy consumption minimization. According to the invention, autonomous intelligent decision-making of the unmanned aerial vehicle on the unpatrolled area is realized.

The invention discloses an intelligent sealing test method and system for a wafer in a semiconductor chip, and relates to the technical field of semiconductor manufacturing, and the method comprises the steps: initializing a magneto-electric field cooperation parameter, optimizing the magneto-electric field cooperation parameter through a multi-target genetic algorithm, and driving core-shell nanoparticles to carry out the metallization filling of a high-precision through hole wafer, generating a wafer with a metalized through hole structure; based on the metalized through hole structure wafer, bonding parameters are generated through a laser Doppler frequency vibration spectrum analysis method, flip interconnection is achieved through a thermal ultrasonic virtual process, and a low-defect bonding wafer is generated; a finite element inversion algorithm is adopted, a stress distribution map of a bonding interface is established, an anti-thermal-stress packaging layer is constructed through an intelligent stress matching algorithm, and the low-defect bonding wafer is packaged; and through a multi-target genetic algorithm, magnetoelectric field cooperation parameters are optimized, core-shell nano-particles are driven to directionally deposit, and accurate control over the metallization filling process is achieved.

A wind and wave response modeling and ocean current inversion method based on machine learning relates to the technical field of artificial intelligence and ocean information services, and comprises the following steps: (1) data acquisition; (2) data processing; (3) constructing a data set; (4) establishing a sea surface flow velocity inversion model by using a particle swarm optimization machine learning algorithm; and (5) obtaining an optimal sea surface flow velocity inversion model through testing and case analysis. Aiming at ocean and Doppler frequency shift characteristics of the sea surface, the invention provides a particle swarm optimization XGBoost model wind wave Doppler contribution prediction method for the first time, and the wind wave Doppler contribution estimation precision and speed can be effectively improved.

The invention discloses a laser radar test method based on a long-distance target distance measurement result, and the method comprises the following steps: obtaining a laser radar echo signal, and extracting the frequency spectrum information of the echo signal; doppler frequency shift characteristic parameters are extracted according to the frequency spectrum information, and the relative speed of the target is calculated based on a preset frequency shift calculation model; acquiring multi-source sensor data associated with the laser radar test platform, and fusing to construct a dynamic ranging reference coordinate system; performing dynamic motion compensation on a laser ranging result according to the relative speed of the target to obtain a target initial measurement distance after Doppler correction; mapping the target initial measurement distance after Doppler correction to the dynamic distance measurement reference coordinate system to obtain a remote target final distance measurement result aligned with a test platform coordinate system; and outputting the accurate position and moving state information of the target in the three-dimensional space according to the final distance measurement result. According to the invention, the ranging precision and stability can be improved.

The invention provides an underwater ultrasonic Doppler real-time analysis method and device based on a digital transducer, and relates to the technical field of data analys.The method comprises the steps that 1, multiple beams of directional ultrasonic waves are emitted into drilling fluid through a digital transducer array on the outer wall of a marine riser, echo signals reflected by gas-liquid two-phase flow are received, and the digital transducer array is used for receiving the echo signals; performing real-time digital conversion on the echo signal to generate an original digital signal containing phase and amplitude information; 2, Doppler frequency shift feature extraction is conducted on the original digital signals, and the real-time movement speed and direction of bubbles in the drilling fluid are determined by calculating the frequency deviation of reflected ultrasonic waves and transmitted ultrasonic waves. Through the digital transducer array and the ultrasonic Doppler technology, accurate measurement of motion parameters of bubbles in drilling fluid, real-time calculation of local gas content and early warning and grading response of gas cut are achieved, and the safety and the intelligent level of drilling operation are improved.

The invention discloses a GNSS real-time deception jamming detection method and system based on deep learning, and belongs to the field of satellite navigation signal processing, and the method comprises the steps: collecting Doppler frequency shift signals of a GNSS receiver in real time, and obtaining an initial training data set; an LSTM prediction model with an incremental learning mechanism is constructed, the LSTM prediction model comprises a double-layer LSTM network and a full connection layer, a gating mechanism is introduced into the double-layer LSTM network, and the initial training data set is adopted to add Gaussian white noise to the prediction model for model training; performing sliding window processing on the initial training data set, and extracting a multi-dimensional feature vector; inputting the trained prediction model for prediction to obtain a model prediction value; calculating a residual error between a model predicted value and a real value, calculating a standard deviation of the residual error after eliminating a preheating period, and dynamically setting a threshold value based on the standard deviation of the residual error; and when the absolute value of the residual exceeds a threshold value and the sampling point processed by the sliding window is located in a preset interference time window, judging that a signal interference event occurs.

The invention belongs to the technical field of radar signal processing, and discloses a radar scattering rapid test method based on polarization decomposition. Comprising the following steps: scanning a target 3D model, simulating scattered field distribution in different incident angles and polarization modes, calculating polarization contrast, and identifying a polarization sensitive area; establishing a dynamic coordinate system conversion model, fusing RTK data, IMU data and laser tracking data, and correcting the position of the trolley and the model in combination with a Doppler frequency shift model and a least square method; calculating an optimal test path of the trolley according to the sensitive area by adopting a natural heuristic optimization algorithm; establishing a geometric environment model, obtaining a back scattering signal through beam forming, analyzing a polarization coherence matrix, obtaining a high-entropy region, and decomposing scattering components; according to the method, closed-loop optimization is formed from a data acquisition source to a scattering component analysis tail end, and the test efficiency and the real-time performance are remarkably improved.

The invention discloses a joint estimation method for timing advance and frequency offset based on a conjugate symmetric ZC sequence, which relates to the technical field of wireless communication and comprises the following steps of: inputting a leader sequence extracted from a demodulated received signal; two ZC sequences in the leader sequence are respectively in cross-correlation with a local ZC sequence, and a peak value of a cross-correlation result amplitude is obtained; iteratively performing fractional frequency offset compensation estimation to obtain a fractional frequency offset estimation value and a compensated leader sequence; performing timing advance estimation and integer frequency offset estimation to obtain a timing advance estimator and an integer frequency offset estimator; obtaining a frequency offset estimation value by combining the decimal multiple and integer multiple frequency offset estimation values; and ending the timing advance and frequency offset estimation, and outputting estimated values of the timing advance and the frequency offset. According to the method, the negative influence of the decimal frequency offset on the ZC sequence is eliminated in a mode of iteratively compensating and estimating the decimal frequency offset, and high-performance timing advance and frequency offset joint estimation with robustness to frequency shift and noise is realized based on the structure of the conjugate symmetric ZC sequence; the method is suitable for a non-ground network communication scene with large Doppler frequency shift and low receiving signal-to-noise ratio.

A radar apparatus includes: a plurality of transmission antennas including a first transmission antenna forming a first beam and a second transmission antenna forming a second beam different from the first beam; and transmission circuitry, which, in operation, performs multiplexing transmission of a transmission signal from the plurality of transmission antennas, the transmission signal being a signal to which a phase rotation corresponding to a Doppler shift amount assigned to each of the plurality of transmission antennas has been applied. In the radar apparatus, a Doppler shift interval by the plurality of transmission antennas is uneven on a Doppler frequency axis, and a first pattern of the Doppler shift amount assigned to the first transmission antenna is different from a second pattern of the Doppler shift amount assigned to the second transmission antenna.

The invention relates to the technical field of laser radars, in particular to an obstacle detection method and system based on a frequency-modulated continuous wave laser radar, and the method comprises the steps: transmitting a chaotic frequency-modulated continuous wave signal to a detection region, and obtaining a reflection echo signal of a target object; performing decoupling calculation on the difference frequency electric signal to obtain a target time frequency distribution matrix; according to the target time-frequency distribution matrix, predicting the Doppler frequency shift amount of the target object at the next moment; based on the chaos frequency modulation adjustment signal, obtaining a distance measurement deviation compensation amount; the chaos frequency modulation adjustment signal is obtained by dynamically adjusting the chaos frequency modulation slope of the chaos frequency modulation continuous wave signal through the Doppler frequency shift amount; and compensating the difference frequency electric signal frequency value of the target object according to the distance measurement deviation compensation amount and the environmental noise data so as to solve obstacle distance speed detection information. According to the invention, the Doppler frequency shift amount is predicted in real time and the chaotic frequency modulation continuous wave signal parameters are dynamically adjusted, so that the accurate compensation of the distance measurement deviation is realized, and the accuracy of obstacle distance speed detection is improved.

The invention relates to the technical field of radar, and discloses a three-dimensional positioning life detection radar system, and the radar system comprises a phased array antenna unit which is used for transmitting radar waves and dynamically adjusting the wave beam direction according to the target position; the signal receiving unit is used for receiving a radar signal reflected by a target; the Doppler frequency shift analysis module is used for analyzing the frequency change of the received radar signal and extracting a micro-motion signal of the target; the target motion analysis module is used for tracking the motion of the target through a Kalman filtering technology; the three-dimensional reconstruction module is used for reconstructing the three-dimensional position of the target through an electromagnetic field integral equation and multi-source sensor information fusion according to the received signals; and the deep learning module is used for identifying the micro-motion signal and optimizing target classification. By adopting the phased-array antenna unit and the beam forming technology, the technical effects of carrying out accurate three-dimensional scanning and rapid dynamic beam adjustment on the target are achieved.

The invention discloses an SER6 Pro antenna with adaptive beam forming capability, comprising: a generation module for generating an initial beam directional diagram based on spatial-temporal correlation analysis of multipath signals; the calculation module is used for updating beam direction parameters in real time by using a Doppler frequency shift estimation algorithm so as to adapt to Doppler frequency shift change of a high-speed mobile user; the suppression module is used for carrying out noise suppression on the beam signal in a frequency domain by adopting an adaptive filter; and the optimization module is used for dynamically adjusting the beam forming matrix and optimizing the beam direction and intensity through an iterative optimization algorithm. The method has the beneficial effects that the problem of inaccurate beam direction identification caused by excessive reflected and scattered signals in a complex multi-path propagation environment is solved; the problem of unstable beam tracking caused by significant change of Doppler frequency shift in a high-speed mobile user scene is solved; and the problem that the signal-to-noise ratio is reduced due to the strong external noise source in a high-interference environment is solved.

The invention discloses an inter-Doppler interference suppression method based on a Gaussian learning factor particle swarm algorithm. The inter-Doppler interference suppression method comprises the following steps that pilot frequency and data symbols are coded to a resource grid of a two-dimensional time delay Doppler domain through orthogonal time-frequency space modulation; on a transmitter, mapping data on a time delay Doppler domain grid to a time-frequency domain through inverse symplectic finite Fourier transform to obtain a time-frequency domain signal; performing Hisenberg transformation on the time-frequency domain signal to obtain a time domain sending signal; obtaining a time domain receiving signal after the time domain sending signal passes through a wireless channel; performing Doppler compensation processing on the time domain receiving signal by using Doppler frequency shift to obtain a signal after Doppler compensation; then performing matched filtering on the signal after Doppler compensation and a received pulse, and sampling to obtain a matched filter output signal; and the matched filter output signal is subjected to the Sextile Fourier transform to obtain a time delay Doppler receiving signal. The method can realize suppression of inter-Doppler interference to a certain extent.

The invention discloses a sparse Bayesian parameter estimation method based on a Markov chain Monte Carlo (MCMC). The sparse Bayesian parameter estimation method is suitable for super-resolution target number detection and high-precision target parameter estimation in a communication perception integration (ISAC) scene. The method comprises the following steps: a base station transmits an orthogonal frequency division multiplexing (OFDM) signal and receives a target reflection echo; performing frequency domain transformation on the echo signal and constructing a high-dimensional observation vector; target parameters are modeled as random variables including path complex gain, time delay, Doppler frequency shift and angle, and a learnable parameterized sensing matrix is constructed; the sparse Bayesian framework is combined with MCMC sampling, the parameters are iteratively updated through random small-batch gradient optimization and the Metropolis-Hastings criterion, and finally the estimation result of the target parameters is output. According to the method, the precision limitation of a traditional gridding method is broken through, super-resolution parameter estimation is achieved, meanwhile, the calculation complexity and the storage overhead are remarkably reduced, and the method is suitable for the high-precision sensing requirement in a 6G communication system.

The invention provides an emergency communication method and system based on a multi-mode early warning broadcast terminal. Wherein the early warning function of the multi-modal terminal is activated and a dynamic feature library is constructed by defining disaster triggering conditions of combination of soil humidity and rainfall intensity; periodically scanning surface micro-deformation by using a radar array, calculating a mountain displacement rate in combination with Doppler frequency shift measurement, and generating a terrain risk thermodynamic diagram; a low-power-consumption long-distance wireless netlike self-organizing communication link is constructed, multi-hop redundancy transmission is started when a public network is interrupted, and an early warning data packet is segmented and forwarded; according to the early warning level cooperatively judged by the dynamic feature library and the radar array, the forwarding priority of the data packet is dynamically allocated, synchronous matching of an acousto-optic early warning signal and a disaster risk gradient is realized, and a hierarchical response link for linkage of terrain deformation monitoring and emergency communication is formed. According to the technical scheme provided by the invention, the emergency response efficiency and the coverage range are improved.

The invention belongs to the technical field of unmanned aerial vehicle communication perception integration, discloses a double-base ISAC clock synchronization algorithm design and system based on an LoS reference diameter, and aims to solve the problem of measurement errors caused by clock asynchronization of a transmitting end and a receiving end. And a receiving end receives a communication signal based on an LoS path and a sensing signal based on a non-line-of-sight (NLoS) path through a communication and sensing integrated design. The invention provides a clock synchronization algorithm based on LoS reference path assistance, and the time delay and Doppler frequency of the signal are measured by using the propagation characteristics of the LoS signal, so that the clock skew and Doppler frequency skew are accurately estimated. According to the algorithm, communication and sensing signals are combined, the clock skew of the receiving end is dynamically adjusted and compensated, asynchronous error accumulation is reduced, and sensing precision and system performance are remarkably improved. Simulation results show that the method effectively enhances communication and sensing functions of the system in application scenarios such as low-altitude economy.

The invention discloses an SAR sea surface flow velocity inversion method based on physical guidance and data driving fusion, and relates to the field of flow velocity inversion, and the method comprises the steps: carrying out the non-geophysical Doppler frequency shift correction of the Doppler frequency shift observed by a spaceborne synthetic aperture radar, and obtaining the geophysical Doppler frequency shift; predicting based on a wave-induced Doppler frequency shift model according to a radar incident angle, reanalyzed wind direction data, a sea surface 10-meter height wind speed inverted by an SAR (Synthetic Aperture Radar), a simulated wind wave parameter, a simulated surge parameter and a simulated maximum wave parameter to obtain a wave-induced Doppler frequency shift; the wave-induced Doppler frequency shift model is obtained based on physical guidance and data-driven modeling; doppler frequency shift generated by sea surface flow is determined according to the geophysical Doppler frequency shift and the wave-induced Doppler frequency shift; according to the method, the Doppler frequency shift generated based on the sea surface flow is converted to obtain the sea surface radial flow velocity, the wave-induced Doppler frequency shift is accurately removed, and reliable inversion of the sea surface flow velocity is realized.

The invention relates to the technical field of satellite communication signal processing, and discloses a broadband satellite signal blind demodulation reconstruction method and system based on sparse representation. The method comprises the following steps: carrying out frequency domain transformation on broadband satellite mixed signals to extract pilot frequency features to construct a beam state feature matrix, inputting the matrix into an adversarial network to generate a beam adaptive sparse dictionary, constructing a topological relation graph according to a Doppler frequency shift set, and carrying out collaborative sparse decomposition to obtain a sparse coefficient matrix; and extracting a code rate candidate set to execute parallel sparse reconstruction, determining an actual code rate through self-consistency verification to obtain a complete signal, analyzing a switching instruction, extracting time sequence statistical characteristics, predicting target domain characteristics, generating a switched sparse dictionary, and executing demodulation. The sparse decomposition precision, the code rate blind estimation accuracy, the cooperative processing efficiency and the switching continuity of the broadband satellite mixed signals are improved.

The invention discloses a frequency discrimination curve calibration system, method and device. A frequency locking technology is adopted, the output laser frequency of the seed laser is stably locked on an absorption peak of the atom / molecule absorption cell, and the problem of frequency drift of the seed laser is effectively solved. Meanwhile, two acousto-optic modulators are used for implementing accurate out-of-cavity passive frequency modulation on the seed laser, and the laser frequency is moved to a preset zero-speed frequency point of an optical frequency discriminator and a linear working area edge frequency point from an atom / molecule absorption peak position. In the calibration process, the telescope vertically points to the zenith, and atmospheric echoes with zero Doppler frequency shift are provided as reference. At the moment, the optical frequency discriminator measures and records the transmittance of a preset zero-speed frequency point in the center of the linear working area and the transmittance of an edge frequency point, and a new frequency discrimination curve can be derived based on the linear hypothesis of the frequency discrimination curve.

The invention relates to the technical field of flow chart automatic testing, and provides a flow chart automatic testing method, system and device of a control system and a storage medium so as to solve the problems of low testing efficiency and poor accuracy. The method comprises the following steps: acquiring a film thickness and transverse tension fluctuation curve by using an intelligent textile sensor array, generating a tension compensation factor based on a phase difference to correct the film thickness, and establishing a thickness distribution topology model; performing non-contact scanning by using a terahertz wave emission array, and activating a defect mark cluster when Doppler frequency shift is detected; transmitting the thickness distribution model and the defect characteristics to a test platform, reconstructing a control logic and generating a test script, and realizing a virtual-real synchronous test through a communication protocol; and generating a process parameter correction factor according to a test result, and feeding back the process parameter correction factor to the distributed control system to optimize the tension closed-loop control module, and generating a matched terahertz verification map. According to the technical scheme provided by the invention, the efficiency and accuracy of automatic testing of the flow chart can be improved.

The invention discloses a signal acquisition and processing method and system based on a multifunctional radar, and relates to the technical field of signal acquisition and processing, and the method comprises the steps: employing a quantum genetic algorithm to optimize radar transmission waveform parameters, including center frequency, bandwidth and frequency modulation slope, and generating a nonlinear frequency modulation waveform through FPGA hardware; a non-uniform sparse array is adopted to receive a target echo signal, time domain random interval sampling and frequency domain pseudo-random frequency point selection are synchronously implemented, and time-space-frequency three-dimensional compressed sensing observation data are formed; performing trilinear tensor joint sparse reconstruction on time-space-frequency three-dimensional compressed sensing observation data, decomposing a polarization scattering matrix eigenvalue from a reconstructed signal, and calculating a coupling characteristic quantity of eigenvalue entropy and micro-Doppler frequency; inputting the coupling characteristic quantity into a deep reinforcement learning model, and dynamically outputting a constant false alarm detection threshold, a moving target display filter order and a resource allocation weight; and detecting a threshold based on a constant false alarm rate.

The invention belongs to the technical field of communication, and particularly relates to an unmanned aerial vehicle group cooperative communication and navigation method based on a 5G Red Cap module, and the method comprises the steps: 1, carrying out the high-resolution sampling of a multipath space-time channel between unmanned aerial vehicles in an unmanned aerial vehicle group through a 5G Red Cap module, and constructing a link channel matrix; 2, on the basis of each link channel matrix, aiming at each unmanned aerial vehicle, constructing a joint channel matrix in combination with a neighbor set of the unmanned aerial vehicle, and extracting an optimal beam forming vector; 3, according to the optimal beam forming vector and the link channel matrix, time delay, phase and Doppler frequency shift are extracted, and position information of each unmanned aerial vehicle is estimated; and 4, according to the obtained position information of each unmanned aerial vehicle and the optimal beam forming vector, ensuring collaborative optimization of navigation and communication. According to the invention, interference can be effectively suppressed, energy consumption is reduced, and communication link stability and navigation reliability are ensured.

The invention provides a channel estimation method of a multi-user uplink low earth orbit satellite wireless communication system, which is used for transmitting signals by adopting an OTFS (Over The Over The Fine Switching) modulation technology aiming at a low earth orbit satellite rapid moving scene, and provides a low-complexity uplink channel estimation method combining path number, time delay, Doppler and channel fading. The method comprises the following steps: firstly, designing different pilot symbol grid positions of multiple users in a time delay-Doppler domain; then, performing energy threshold detection on all time delay domains of low-orbit satellite receiving signals to estimate the total number of paths and the time delay value of each path; then, giving a closed expression of channel fading by using a maximum likelihood estimation method, and estimating Doppler frequency shift by using a one-dimensional search method; through simulation verification, the provided uplink joint channel estimation method can effectively realize channel detection, can be further applied to ergodic capacity derivation work, and has relatively good practicability and performance.

The invention belongs to the technical field of radar electronic countermeasures, and discloses an FPGA-based Doppler flicker interference generation method, which comprises the following steps that: an upper computer issues system parameters and Doppler flicker interference strategy parameters to an FPGA; the signal transmitting and collecting module of the FPGA receives and processes the radar radio frequency signal to obtain a radar baseband signal and stores the radar baseband signal; the control unit extracts a radar baseband signal according to the system parameters, and generates alternately changing Doppler frequency control words according to strategy parameter control; the extracted radar baseband signal or synchronization information thereof and a frequency control word are sent to a multi-path parallel DDS unit to generate a Doppler flicker interference baseband signal; the interference baseband signal is processed by the signal emission and acquisition module and then is emitted to form an interference radio frequency signal. The method is realized by utilizing the FPGA, Doppler flicker interference can be flexibly and efficiently generated, effective cheating is caused to radar speed tracking, and the method has the advantages of high response speed, high flexibility and good interference effect.

This disclosure relates generally to action recognition and more particularly to system and method for real-time radar-based action recognition. The classical machine learning techniques used for learning and inferring human actions from radar images are compute intensive, and require volumes of training data, making them unsuitable for deployment on network edge. The disclosed system utilizes neuromorphic computing and Spiking Neural Networks (SNN) to learn human actions from radar data captured by radar sensor(s). In an embodiment, the disclosed system includes a SNN model having a data pre-processing layer, Convolutional SNN layers and a Classifier layer. The preprocessing layer receives radar data including doppler frequencies reflected from the target and determines a binarized matrix. The CSNN layers extracts features (spatial and temporal) associated with the target's actions based on the binarized matrix. The classifier layer identifies a type of the action performed by the target based on the features.

The invention belongs to the field of wireless communication, and particularly relates to wireless communication of aerospace crafts, in particular to a differential coding modulation communication method suitable for large Doppler frequency shift. The method comprises the following steps: 1, setting frame structure parameters; 2, framing is carried out according to power control, a synchronization header, a header and a data segment, and a frame structure is generated; step 3, quantizing and de-spreading the received signal to generate a to-be-synchronized data stream; 4, determining a frame synchronization position and a bit synchronization position, calculating frequency offset by using FFT (Fast Fourier Transform), and calculating channel frequency offset to carry out frequency offset compensation; 5, calculating a correlation value after compensating the data stream, and determining a coarse synchronization position of a receiving end frame; and 6, carrying out five-path parallel correlation peak calculation to obtain a data block bit synchronization position, a position ahead of two sampling points, a position lagging of two sampling points, a position lagging of one sampling point and a position ahead of one sampling point.

The invention relates to the technical field of communication, and discloses a network communication chip signal interference suppression processing method. The method comprises the following steps: acquiring a local oscillator phase jitter sequence in real time through an on-chip phase noise monitoring unit; estimating Doppler frequency shift and channel coherence time based on the sequence; dynamically adjusting the closed-loop bandwidth of the phase-locked loop; and generating a phase compensation signal, and performing time-varying channel minimum mean square error equalization in combination with a received baseband signal to eliminate inter-symbol interference. The system integrates a phase noise monitoring function module, a channel parameter estimation function module, a phase-locked loop bandwidth regulation function module, a phase compensation generation function module and an interference joint elimination function module. By means of dynamic bandwidth reconstruction and high-precision phase compensation, the bit error rate under high-speed movement is remarkably reduced, the 5G millimeter wave communication standard requirement is met, and the method has the advantages of being achieved on a whole chip, low in delay and high in robustness.