1173 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 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.

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 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 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 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 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 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.

Method of measuring ionosphere scintillation phase index Sigma-Phi, the method including, for each of N satellites being tracked, calculating a phase prediction at an i-th sample; for each of the N satellites, calculating an individual loop discriminator signal based on the phase prediction; rejecting the i-th samples of some of the N satellites, where K non-rejected satellites remain; calculating common loop discriminator signal based on the individual loop discriminator signals of non-rejected K satellites; calculating a phase estimate and a Doppler frequency estimate at the i-th sample for each of the N satellites based on individual loop discriminator signal; calculating test statistic based on the phase estimate at the i-th sample and an observed phase for each of the N satellites; calculating index Sigma-Phi as standard deviation estimation of the test statistic for each of the N satellites; and outputting the index Sigma-Phi for each of the N satellites.

The invention discloses a communication-detection integrated sonar signal design method and device based on multi-pulse composite modulation, and the method comprises the steps: dividing a total frame period into a detection sub-frame and a communication sub-frame, enabling the detection sub-frame to achieve the high-resolution distance measurement through employing a bidirectional linear frequency modulation (BILFM) signal, a communication sub-frame adopts a multi-frequency multi-phase composite modulation (MTPM) signal to realize high-bit-rate data transmission; after band filtering, orthogonal demodulation, low-pass filtering and down-sampling preprocessing are carried out on detection sub-frame echoes, distance and speed information is extracted by adopting fast-time low-sampling two-dimensional fast Fourier transform (2D-FFT), unambiguous Doppler frequency is recovered by utilizing the Chinese remainder theorem (CRT), and accurate speed measurement of long-distance and high-speed targets is realized; a communication subframe receiving signal is subjected to IQ demodulation after down-conversion, Costas loop carrier synchronization and matched filtering, and multi-frequency multi-phase coded data are extracted. According to the method, the time-frequency collaborative design of detection and communication is realized, the distance resolution and the speed measurement range are considered, and the signal bandwidth utilization rate and the underwater information transmission reliability are remarkably improved while the system complexity is kept low. The device comprises a processor and a memory, and an executable program for implementing the method is stored in the memory. The technology can be widely applied to the fields of unmanned underwater vehicles, ocean monitoring, underwater sensing networks and the like.

The invention provides a GEO communication satellite uplink signal Doppler frequency compensation method and device. The method comprises the following steps: acquiring a satellite orbit determination result corresponding to a GEO communication satellite; determining a Doppler compensation frequency curve according to the satellite orbit measurement result and the local frequency of the frequency conversion of a satellite transponder configured in the GEO communication satellite; and compensating a first uplink signal to be transmitted from the ground station to the GEO communication satellite by using the Doppler compensation frequency curve through the compensation frequency mixer, and transmitting the compensated first uplink signal to the GEO communication satellite. According to the invention, under the condition that the user receiver is non-inductive, the carrier frequency and the spreading code rate of the user receiver are changed in equal proportion, so that the user receiver can adopt a receiving algorithm of the carrier-assisted spreading code rate to improve the sensitivity.

The invention belongs to the technical field of wireless communication networks, and discloses a wireless signal testing method and system for an unmanned vehicle. The method comprises the steps of synchronously collecting electromagnetic signals inside and outside a vehicle, and generating an electromagnetic observation data set; constructing a calibration observation matrix based on a vehicle attitude, position information, a road side reference signal and a communication link state, extracting a candidate interference cluster set and constructing a power curve, and calculating a Pearson's correlation coefficient and Doppler frequency shift to identify an interference type label; determining an interference source position of each interference cluster by adopting a corresponding interference source positioning algorithm according to the interference type label; comprehensively evaluating the communication reliability of the wireless link of the whole vehicle by combining all interference source positions, corresponding labels and power curves and fusing communication link performance indexes and vehicle state information; according to the invention, accurate identification and traceability of wireless link interference of the unmanned vehicle are realized, and the accuracy and real-time performance of communication reliability evaluation are improved.

The invention belongs to the technical field of communication, and particularly relates to a high-robustness multi-channel frequency shift Chirp modulation signal generation method and system for a time-frequency doubly selective channel. The method comprises the following steps of: 1, calculating robust code digits based on statistical characteristics of time delay and Doppler frequency shift of an ionized layer channel; 2, based on the number of robust code bits in the step 1, setting an address code, and realizing RO-MFSCM signal mapping of binary information bits; 3, modulating and transmitting the RO-MFSCM signal based on the information mapping in the step 2, thereby realizing the transmitting process of the RO-MFSCM signal; step 4, based on the emission signal in the step 3 and the robust code digit in the step 1, the receiver carries out robust domain energy aggregation on the RO-MFSCM signal; and step 5, based on the multi-channel robust domain energy aggregation signal in the step 4, adopting a multi-channel parallel demodulation algorithm and de-mapping to realize the receiving process of the RO-MFSCM signal under the time-frequency doubly selective channel. The method aims at the transmission fading problem of the FSCM signal in the ionosphere time-frequency doubly selective channel.

The invention relates to the technical field of satellite conduction integration, and discloses a high and low orbit satellite conduction integration method and system, and the method comprises the steps: carrying out the spatial characteristic analysis of a high orbit navigation satellite signal and a low orbit communication satellite signal, and obtaining visible relation data and Doppler frequency shift characteristic data; executing high-orbit and low-orbit satellite conduction switching analysis, and generating a self-adaptive threshold parameter of conduction service switching between the high-orbit and low-orbit satellites; a high-orbit and low-orbit integrated inter-satellite communication network is established between the high-orbit navigation satellite cluster and the low-orbit communication satellite cluster; conducting resource collaborative allocation is executed, and a resource scheduling instruction is generated; according to the method, deep integration of communication and navigation functions is realized, the limitation of function separation of a traditional satellite system is broken through, and the problem of unstable control caused by dynamic change of network topology of the high-orbit and low-orbit satellites is solved.

The invention discloses an acousto-optic radar wind measurement data correction system based on adaptive noise suppression, and relates to the technical field of data correction. Environmental parameters and acousto-optic radar system parameters are combined through a dynamic adjustment module to dynamically adjust a signal-to-noise ratio threshold; the echo signal quality analysis module inputs the frequency spectrum characteristic data and the dynamically adjusted signal-to-noise ratio threshold value into an echo quality model and judges whether the current echo signal is valid or not, if yes, interpolation is carried out by adopting a spatial smooth interpolation method, if yes, the dominant frequency of the echo signal is extracted, Doppler frequency shift is calculated, and according to the detection angle and the laying direction, the Doppler frequency shift is calculated; and calculating a radial wind speed, inverting a three-dimensional wind speed vector and carrying out physical consistency correction. According to the correction system, the dynamic adjustment module is introduced, real-time environment parameters and system operation parameters are combined, and a signal-to-noise ratio threshold value required by judgment is dynamically adjusted, so that a judgment basis can be intelligently self-adapted along with a measurement environment, and the accuracy and robustness of echo signal quality judgment are remarkably improved.

The invention discloses a feed frequency offset compensation method and a communication system. The method comprises the following steps: a satellite communication management module obtains ephemeris information of a satellite and position information of a gateway station, and determines a first Doppler frequency offset of a feed link between the satellite and the gateway station according to the ephemeris information and the position information; obtaining a test frequency offset obtained by performing frequency estimation on a measurement signal transmitted on the feed link, and determining a feed frequency offset of the feed link according to the test frequency offset and the first Doppler frequency offset; and transmitting the feed frequency offset to the compensation module. The compensation module receives a message sent by the satellite communication management module; detecting whether the information contains the feed frequency offset of the feed link; and under the condition that the message contains the feed frequency offset, performing frequency offset compensation on the signal transmitted on the user link according to the feed frequency offset. According to the invention, the technical problem of feed frequency offset caused by unstable clock due to improvement of the working frequency of the feed link is solved.

The invention discloses an integrated waveform generation method and device based on transmission symbol compensation. The method comprises the following steps: generating an imitated radio frequency division multiplexing pilot signal; the simulated radio frequency division multiplexing pilot signal is sent to a receiving end, the receiving end is used for carrying out channel estimation on the simulated radio frequency division multiplexing pilot signal to obtain channel state information, and the channel state information comprises normalized time delay, normalized Doppler frequency shift or gain; according to the channel state information, pre-compensation processing is carried out on an imitated radio frequency division multiplexing information symbol on a target domain to obtain a compensation signal, and the target domain comprises a discrete affine Fourier transform domain or a time domain; and performing precoding processing on the compensation signal to obtain an integrated waveform. According to the invention, integrated waveform generation is realized, the efficiency is improved, and the signal processing complexity and resource overhead are reduced. The method can be widely applied to the technical field of wireless communication.

The invention discloses a synthetic aperture radar sea surface wind field inversion method considering Doppler centroid anomaly, and the method comprises the following steps: obtaining vertical polarization SAR image data, and extracting a radar backscattering coefficient NRCS and an original Doppler centroid anomaly DCA related image; based on Doppler frequency data of the VV polarized SAR image, through quintic polynomial fitting and land area correction processing, DCA information caused by geophysical factors is extracted; acquiring actually measured wind speed data of the buoy, matching the actually measured wind speed data with an external background wind field, and performing nonlinear fitting correction by adopting an exponential function to obtain a corrected background wind field speed; constructing a variational analysis model containing an NRCS and DCA observation field, taking the corrected external wind field as a background field, and obtaining a wind speed field and a wind direction field through minimum cost function inversion; performing verification analysis on an inversion result by adopting buoy observation data subjected to space-time matching; the precision and reliability of the vector parameters of the sea surface wind field can be improved.

The invention provides a ground positioning method and device fusing Doppler and pseudo-range of a low-orbit satellite, and the method comprises the steps: collecting pseudo-range observation values and Doppler frequency shift observation values of a plurality of epoch signals through a ground receiver in a transit time period of the low-orbit satellite by employing an enhanced link between the low-orbit satellite and the ground, and obtaining a Doppler frequency shift observation value of the multiple epoch signals; the orbital position, the running speed and the clock error of the low-orbit satellite corresponding to the epoch signal are collected; calculating the position, speed and clock error of the low-orbit satellite at the emission moment of each epoch signal; when the number of the accumulated observation equations reaches a preset threshold value, a fixed weight least square algorithm is adopted to fuse pseudo-range observation values and Doppler information to solve the position of a ground user receiving end; performing post-test residual error test on the calculation result; and if the after-test residual error test is passed, outputting a positioning result.

The invention discloses a micro-action three-dimensional sensing method and system based on WiFi channel state information, and relates to the technical field of wireless signal sensing. The method comprises the following steps: collecting CSI data, preprocessing, and outputting a CSI amplitude matrix and a phase matrix; the phase difference of adjacent antenna pairs is used for counteracting common noise, a linear mapping model of displacement increment and phase change is constructed, and displacement calculation is achieved; designing a space-time TransFormer model, fusing CSI amplitude, phase difference, displacement increment and Doppler frequency shift characteristics through a time sequence and space joint attention mechanism, and outputting an initial three-dimensional trajectory; optimizing the initial three-dimensional trajectory by using a self-supervised learning mechanism based on physical consistency constraint; and finally, constructing a dynamic path filter, carrying out real-time filtering correction on the optimized trajectory in combination with extended Kalman filtering and Bayesian multipath fusion, and outputting a final three-dimensional trajectory, thereby realizing high-precision and low-delay trajectory reconstruction without labeling in a complex scene.