128 results about "Orthogonal matching pursuit algorithm" patented technology

The invention belongs to the technical field of carrier frequency offset estimation, and particularly relates to a carrier frequency offset estimation method based on Newton orthogonal matching pursuit. The method comprises the following specific steps of: splitting CFO into two parts of frequencies, namely off-grid deviation and grid point frequency, and further modeling an observation signal as a parameter weighted compressed sensing problem; using a Newton orthogonal matching pursuit algorithm to iteratively optimize the off-grid deviation of the CFO and the estimation of the grid point frequency, and obtaining a CFO candidate frequency set; and obtaining a required CFO estimation result from the candidate set by using the lead code information of the target user. According to the method, the complexity requirement of an actual system is met, meanwhile, the precision of CFO estimation is remarkably improved, and good robustness is achieved.

A broadband oscillation characteristic identification method for a new energy access AC power grid comprises the following steps: compressing an oscillation signal acquired by a PMU by using a Gaussian random matrix, uploading low-dimensional data to a master station, and reconstructing the signal at the master station through an orthogonal matching pursuit (OMP) algorithm; a VMD algorithm with the minimum energy loss as a threshold value is adopted to conduct self-adaptive decomposition on the reconstructed signals, and IMF components containing oscillation information are obtained; the purpose of blind source separation is achieved by maximizing the non-Gaussian property of the output signal through FastICA, independent components are extracted from the mixed signal, and noise is removed; and finally, calculating related information (frequency and amplitude) of oscillation by using FFT (Fast Fourier Transform). According to the method, the technical advantages of CS-OMP, VMD and FastICA are combined, different kinds of oscillation modes and complex working conditions can be dealt with, broadband oscillation in a power system can be better monitored and recognized, safe and stable operation of a power grid is guaranteed, and accurate characteristic parameters (frequency and amplitude) are provided for the oscillation suppression technology.

The invention relates to a multi-dimensional transmission data compression sensing method and system for urban emergency rescue, and the method comprises the steps: obtaining multi-modal data, carrying out the normalization processing and sparse representation, and obtaining the sparse coefficient of each modal; constructing a block diagonal random matrix for each modal sparse coefficient to perform independent compression sampling, generating a low-dimensional observation value before coding, and performing arithmetic coding and low-density parity check code error correction coding to generate an anti-interference code stream; and performing low-density parity check code decoding and arithmetic decoding on the anti-interference code stream to obtain a decoded low-dimensional observation value, performing iteration by using an orthogonal matching pursuit algorithm, recovering sparse coefficients of each mode, performing reconstruction to obtain text, image and audio features, and projecting the text, image and audio features to a shared semantic space to obtain a shared semantic space. And calculating a joint semantic weight through a cross-modal attention mechanism, and generating a multi-modal fusion result with consistent semantics. The method disclosed by the invention provides an efficient, robust and semantic collaborative end-to-end solution for urban emergency rescue.

The invention is suitable for the technical field of radar signal processing, and provides a space target SFM three-dimensional reconstruction method based on a multi-frame ISAR image, and the method comprises the steps: carrying out the preprocessing and imaging of large-angle inverse synthetic aperture radar ISAR echo data of a space target, and obtaining a multi-frame ISAR image sequence; extracting scattering points in each frame of ISAR image sequence according to an orthogonal matching pursuit algorithm, and performing feature matching on adjacent frames of ISAR image sequences to obtain a scattering point set; obtaining instantaneous radar sight line information, and constructing a projection matrix from a space target scattering center three-dimensional coordinate to an ISAR two-dimensional pixel plane according to the instantaneous radar sight line information; and obtaining a three-dimensional reconstruction result according to the scattering point set and the projection matrix in combination with a triangulation principle in an incremental motion recovery structure SFM method. According to the method, the robustness and precision of three-dimensional reconstruction can be improved.

The invention discloses an ultra-harmonic rapid detection method based on compressed sampling and multiple measurement vectors, and solves the problems of high sampling rate, low reconstruction efficiency and insufficient spectrum resolution in the prior art. Sub-Nyquist compressed sampling is realized through a sparse random matrix, and the hardware burden is reduced; a dynamic step size sparse self-adaptive matching pursuit algorithm (DSSAMP) is adopted to reconstruct signals, the step size is adjusted in a self-adaptive mode in combination with residual energy changes, and the convergence speed and precision are balanced; an improved multi-measurement vector model (IMMV) is constructed through framing processing and introduction of interpolation factors and prior frequency point screening, and the calculation efficiency is improved; and finally, extracting super-harmonic frequency, amplitude and phase parameters based on an orthogonal matching pursuit (OMP) algorithm. According to the method, the high resolution is ensured, the sampling rate and the calculation complexity are remarkably reduced, and the real-time requirement is met.

Conventional Orthogonal frequency division multiplexing (OFDM) is unable to retain its orthogonality and suffers loss in performance in high Doppler circumstances. The present disclosure converts a signal received in delay-time domain into delay-Doppler domain and extracts a guard band region from the received converted signal. A 2-dimensional fast Fourier transform is performed on guard band region extracted from received converted signal. A 2-dimensional fast Fourier transform of the received converted signal is divided with the 2-dimensional fast Fourier transform of transmitted signal to extract phase information. A dictionary is created using a pre-defined set of values of delay and Doppler. A sparse recovery problem is formed for received converted signal using an orthogonal matching pursuit algorithm. One or more parameters are estimated by identifying one or more locations pertaining to the one or more columns corresponding to L significant non-zero locations comprised in sparse vector of sparse recovery problem.

The invention discloses a direct current charging pile detection system and method applied to the field, and relates to the technical field of power equipment on-line monitoring, and the method comprises the steps: inputting a three-dimensional data set into a Toeplitz cyclic measurement matrix for compressed sampling, reconstructing the three-dimensional data set into a high-resolution signal through employing an improved orthogonal matching pursuit algorithm, and carrying out the detection of the high-resolution signal; analyzing and calculating a local variable coefficient through a sliding window, marking abnormal positions, and integrating the abnormal positions into an abnormal position set; inputting the abnormal position set into a pre-trained long and short term memory prediction model, evaluating the insulation residual life and the fault risk level, and calculating the maximum allowable output current of the DC charging pile in real time; the load impedance is dynamically adjusted and detected through the memristor array, the output current of the direct current charging pile is collected in real time, and synchronous compression wavelet transform is adopted to analyze a harmonic ridge line and extract a harmonic component; the accuracy of fault early warning is remarkably improved, rapid dynamic adjustment of the output current is achieved, and the technical problem of multi-physics field coupling monitoring of the rapid charging pile is effectively solved.

The invention discloses a distribution network area emergency insurance supply method and system based on vehicle network interaction, and relates to the technical field of distribution network area emergency insurance supply, and the method comprises the following steps: obtaining a distribution network area fault position and electric vehicle distribution data, and constructing a vehicle scheduling instruction set; driving the electric vehicle to move to a target area according to the scheduling instruction set, and transmitting magnetic field disturbance signals of different frequency bands through a vehicle-mounted coil array to obtain a magnetic field disturbance signal set; constructing a dynamic sensing matrix for each magnetic field disturbance signal, and performing compression reconstruction by adopting an orthogonal matching pursuit algorithm to obtain a line impedance feature vector group; constructing a security constraint set based on the line impedance feature vector group, and respectively applying the security constraint set to a multi-objective optimization algorithm to solve the optimal capacity calling proportion of the electric vehicle battery pack; and controlling the electric vehicle to output reverse power to the distribution network area based on the optimal capacity calling proportion, thereby solving the problem that power supply is difficult to optimize due to the fact that difference between multi-vehicle cooperation and a power line is not considered in a traditional method.

The invention discloses a target detection and channel estimation method for a near-field sensing integrated system. The method comprises the following steps: a base station sends a downlink pilot signal to a sensing target and receives a corresponding echo signal; then, a user sends an uplink pilot signal to estimate a user channel; according to the characteristics of a near-field channel, a sensing and communication signal model based on a spherical wavefront hypothesis is established; according to the characteristics of a near-field channel, firstly, a near-field channel model is approximated by adopting Fresnel approximation, then a low-overhead dictionary based on near-field spherical wave approximation is provided, and on the basis, an improved orthogonal matching pursuit algorithm is designed for near-field communication perception to estimate parameters of a perception target and a communication channel. According to the invention, parameters of a near-field sensing target and a channel can be estimated with low overhead, and the estimation precision of the parameters in a near-field scene is improved.

The invention discloses a multipath effect suppression method for indoor visible light positioning, relates to the technical field of indoor visible light communication and positioning, and aims to solve the problems in the prior art, the method comprises the following steps: constructing a fractional order chaotic signal generator and starting to generate a chaotic sequence signal; the chaotic sequence signals are modulated and loaded to an LED array and a driving circuit thereof, and optical signals carrying fractional order chaotic characteristics are generated and transmitted; after being propagated indoors, the optical signal is acquired by a photoelectric detector, is preprocessed and then is transmitted to a field FPGA (Field Programmable Gate Array); in the FPGA, based on a compressed sensing theory, modeling the received signal and constructing an adaptive sensing matrix to obtain a compressed observation signal; iteratively recovering sparse channel response from the compressed observation signal by adopting a path focusing guide orthogonal matching pursuit algorithm; and the FPGA extracts main path information from the reconstructed sparse channel response, and calculates a final positioning coordinate in combination with an arrival time positioning model. And in indoor visible light positioning, the method has a good capability of resisting a multipath effect.

The invention discloses an underwater sound environment sensing method based on multi-array-element sparse channel estimation. An underwater sound receiving end receives signals transmitted through an underwater sound multipath channel through a multi-array-element array; performing Hilbert transform on the receiving signal of each array element to obtain an analysis signal, and calculating a cross-correlation function of the analysis signal and the transmitting signal; based on the cross-correlation function, sparse channel parameters, including path amplitude and time delay, of each array element are estimated by adopting an orthogonal matching pursuit algorithm combined with a constant false alarm detection dynamic threshold value; the method comprises the following steps: constructing an array response vector by using sparse channel parameters of a multi-array element array, and searching and estimating angles of arrival, including a direction angle and a pitch angle, of a multipath signal through a spatial spectrum peak value; and based on the arrival angles, amplitudes and time delays of the direct path and the reflection path, inverting an underwater environment structure through a ray acoustic theory, including a reflection point distance and a reflection surface normal vector, so as to realize three-dimensional perception of the underwater reflector. According to the invention, multipath resolution can be improved, and false alarm and missing detection can be effectively reduced.

The invention provides a comprehensive noise reduction performance evaluation method for a nonlinear ultrasonic detection signal noise reduction algorithm, and the method comprises the steps: firstly constructing a multi-working-condition noise reduction performance pre-screening mechanism based on error band analysis based on early-stage experimental data, and then introducing a radar map as an evaluation tool for the comprehensive noise reduction effect of the signal noise reduction algorithm. The noise reduction effects of a moving average method (MA), a spectral subtraction method (SS), a short-time Fourier transform method (STFT), a wavelet transform method (WT) and an orthogonal matching pursuit algorithm (OMP) are compared, and finally a signal noise reduction algorithm with the optimal comprehensive efficiency is screened out. On the basis of algorithm optimization, quantitative mapping rules between microcrack three-dimensional geometric parameters and relative nonlinear coefficients are analyzed through regression modeling, and the significant level of the correlation degree of the relative nonlinear coefficients and microcrack size parameters is effectively improved; and a high-confidence theoretical support is provided for quantitative nondestructive detection of the microcracks in engineering practice.

The invention relates to the technical field of underwater acoustic communication, in particular to a multi-channel underwater acoustic OFDM (Orthogonal Frequency Division Multiplexing) communication method and system based on joint optimization sparse channel estimation. Selecting sparse signals and designing a measurement matrix; a step of performing dimension reduction on the original signal by using a compressed sensing technology; a step of performing sparse recovery on the observation signal and the measurement matrix by using an orthogonal matching pursuit algorithm, including a step of performing sparsity detection by using global approximate message passing GAMP; based on a high-probability support set output by the GAMP, accurate reconstruction is carried out through a local orthogonal matching pursuit LOMP algorithm, sparse optimization is carried out on signals, and multi-channel underwater acoustic OFDM communication based on joint optimization sparse channel estimation is achieved. According to the method, the traditional channel estimation process is simplified by utilizing the sparse characteristic of the channel, and the performance and efficiency of an underwater acoustic communication system are greatly improved.

The invention relates to the technical field of electrical variable measurement, in particular to a self-adaptive power quality monitoring method for a power cabinet, which comprises the following steps of: starting a low-frequency acquisition unit arranged at a monitoring node of the power cabinet, and acquiring a low-frequency coarse scanning voltage signal of the power cabinet in a current monitoring period at a preset low-frequency sampling rate; according to the method, compressed observation vectors are transmitted, sparse basis inversion calculation is executed by using an orthogonal matching pursuit algorithm, high-precision power quality time domain waveform data are reconstructed, rich high-frequency transient details are restored under the condition of low-data-volume transmission, distortion feature analysis is carried out based on reconstructed waveforms, disturbance types are identified, and a monitoring analysis report is generated and uploaded. The real-time dynamic adjustment of the sampling scale and the matrix structure along with the signal fluctuation state is realized, the optimal balance of the data compression ratio and the signal reconstruction quality is achieved, the contradiction between the storage and transmission bandwidth limitation of massive high-frequency data in a complex power grid environment is solved, and the sensitivity for transient abnormality is improved.

The invention discloses an integrated circuit worst performance processing method, and relates to the field of integrated circuits, and the method comprises the steps: employing a corrected normal distribution cumulative distribution function CDF to describe the nonlinearity between the failure rate and the circuit performance, and introducing a skewness parameter and a kurtosis parameter; and carrying out weight calculation on the sampling points, highlighting important samples near the failure boundary, and constructing a local linear model in a local region by adopting weighted least square regression. On the global scale, logarithmic transformation is carried out on a sampling matrix, feature distribution is converted from nonlinearity to approximate linearity, an orthogonal matching pursuit algorithm is adopted to construct a sparse global linear model, and the generalization ability and interpretation of the model are improved. Finally, according to the method, a circuit performance predicted value at 6 sigma calculated by a corrected Gaussian function is taken as a target, a global or local linear model is flexibly selected as a constraint condition according to the position of a worst performance point, an optimal solution is iteratively solved, and the estimation precision and the calculation efficiency are effectively balanced.

The invention discloses a multi-source remote sensing reflectivity fusion method based on orthogonal matching pursuit and physical constraint, and the method comprises the steps: taking a multi-source remote sensing image as a data basis, and constructing a multiband sparse dictionary through time sequence alignment and overlapping sampling; then, an orthogonal matching pursuit algorithm introducing physical constraints is utilized to gradually select an image atom which is most matched with a target date in a sparse reconstruction process, and physical consistency of a reconstruction result in the aspects of hydrological conditions, phenological characteristics, spectral reflectivity and the like is ensured; and finally, through residual error return correction, day-by-day seamless 30-meter six-waveband reflectivity reconstruction is realized. According to the method, the stability and the physical interpretability of a reconstruction result are remarkably improved while efficient calculation is kept, continuous, multi-band and high-resolution time sequence data generation can be achieved in complex ecological environments such as lake wetlands, and high-precision remote sensing data support is provided for hydrological process simulation, ecological environment evaluation and carbon cycle research.

The present invention relates to a method for obtaining multi-order refraction times of refracted waves at the coal-rock interface. When the source wavelength is greater than the coal thickness, the refracted waves of adjacent orders are mutually aliased, and it is difficult for conventional deconvolution methods to sparsify them. By taking advantage of the characteristics of high similarity and known order among the refracted waves of each order and drawing on the orthogonal matching pursuit algorithm, the present invention can accurately extract the refraction times of each order from severely aliased refracted wave signals. The present invention takes into account the phase differences among the refracted waves of each order. By constructing a dictionary matrix containing the phase rotation angle, the refracted waves of each order can accurately match the corresponding wavelets, obtaining accurate pulse signals and improving the accuracy of the obtained time points.

The invention relates to the technical field of wireless communication perception, in particular to a user perception method based on a multi-layer intelligent omnidirectional metasurface, and proposes to realize accurate perception of reflection and refraction user orientations by utilizing heterogeneous characteristics of propagation paths on two sides of a multi-layer intelligent omnidirectional metasurface structure. Based on the architecture, a user reflection and refraction type judgment algorithm based on uplink pilot frequency information is provided, and the user reflection and refraction types are determined based on the heterogeneous characteristics of user channels on the two sides of the multi-layer intelligent omni-directional metasurface and based on least square optimization problem solving and target function size comparison. The propagation path angle estimation algorithm specifically comprises the following steps: firstly, based on uplink pilot frequency information, designing a channel estimation algorithm comprising alternating optimization, constant-rank manifold optimization, convex relaxation and other methods to estimate and obtain a channel matrix by utilizing channel constant-rank and angular domain sparse characteristics; and finally, based on a user type determination result, obtaining user angle information based on each channel matrix by using an orthogonal matching pursuit algorithm.

The invention discloses a GNSS (Global Navigation Satellite System) signal sparse compression capture method for a low-correlation measurement matrix, which comprises the following steps of: firstly, constructing a code phase matrix and a frequency offset matrix, and carrying out sparse transformation on a downsampled GNSS signal to obtain a correlation matrix; the method comprises the following steps of: firstly, carrying out iterative optimization on a measurement matrix by taking a Gramb matrix as a matrix, then taking a Frobenius norm of a difference between the Gramb matrix and an equiangular tight frame matrix as a target function, alternately using singular value decomposition (SVD) and a shrinkage operator to carry out iterative optimization on the measurement matrix, and carrying out compression measurement on a correlation matrix through the optimized measurement matrix. Secondly, a correlation matrix of compression measurement is quickly and accurately reconstructed by using a least square operator and an orthogonal matching pursuit algorithm; and finally, when the peak value ratio of the primary peak to the secondary peak of the reconstructed correlation matrix is greater than a threshold value, outputting code phase time delay and Doppler frequency offset corresponding to the primary peak. And if the ratio of the primary peak value to the secondary peak value of the reconstructed correlation matrix is smaller than the threshold value, capturing the GNSS signal again. According to the method, the maximum correlation coefficient and the average correlation coefficient of the measurement matrix can be reduced, the GNSS signal capturing sensitivity is improved, and hardware resources in the signal capturing process in a GNSS receiver can be reduced.

The invention discloses an underwater sound double-expansion channel parameter estimation method based on Newton orthogonal matching pursuit. The method comprises the following steps: firstly, realizing frame synchronization by using a cross-correlation peak of an LFM signal and a received signal; a coarse estimation value of a Doppler coefficient is obtained on a discrete time frequency grid through an ambiguity function method by utilizing the self-correlation characteristic of m-sequence pilot frequency, multipath time delay of a channel is detected by utilizing a matched filtering peak value of a signal after frequency offset compensation, and a coarse estimation result of the channel is obtained; executing Newton iteration optimization in a continuous parameter space by adopting a Newton orthogonal matching pursuit algorithm to realize super-resolution off-grid estimation of the Doppler coefficient of the first data block; and finally, proposing an iterative block tracking strategy, initializing the compensation of the rear block through the estimated value of the front block, and updating the time-varying Doppler coefficient by using the balanced signal feedback to realize the dynamic tracking of the time-varying Doppler coefficient. According to the invention, the Doppler estimation root-mean-square error is obviously reduced, and the calculation efficiency is high.

The invention discloses a power distribution network fault signal reconstruction method, system and device based on K-SVD and orthogonal matching pursuit, and a medium, and belongs to the technical field of power systems, and the method comprises the steps: obtaining a fault signal from a monitoring device of a power distribution network, and carrying out the preprocessing of the signal; a K-SVD algorithm is used for dictionary learning, a sparse dictionary suitable for power distribution network fault signals is generated, and the dictionary is optimized through training of a signal data set; performing sparse representation on the signal by adopting an orthogonal matching pursuit algorithm, and realizing sparse decomposition of the signal by searching an optimal sparse representation coefficient; based on the sparse representation coefficient, reconstructing the signal from the sparse dictionary, calculating a reconstruction error, comparing the reconstruction error with an actual fault signal, evaluating a reconstruction effect and an error, and performing parameter optimization adjustment; and accurately judging the type of the fault according to the reconstructed signal. According to the method, the key information of the fault signal is effectively extracted in a complex noise environment, and the signal reconstruction precision is remarkably improved.

The invention discloses a double-time-scale transmission method and system for an RIS-assisted MIMO system. The method comprises the following steps: step 1, constructing a single-cellular uplink RIS-assisted millimeter wave large-scale MIMO system model; 2, converting an RIS element phase shift vector problem into a multi-arm bandit problem, and finding out a correlation matrix closely related to each time slot phase shift vector; 3, based on an improved orthogonal matching pursuit algorithm, calculating a small time slot matrix of the current time slot by using information of all time slots before the current time slot, and finally obtaining a correlation matrix of the whole time period; step 4, according to the calculated correlation matrix, solving phase shift vectors of all time slots by using a CMAB-based phase shift algorithm; and 5, calculating an effective uplink matrix and a combined matrix according to the solved phase shift vector, and further solving a base station receiving signal. According to the method, the cost can be remarkably reduced, and the effective spectrum efficiency is improved.

The invention discloses a compressed sensing coherent signal DOA estimation method based on Toeplitz reconstruction, and the method comprises the steps: carrying out the forward and reverse smoothing operation of a covariance matrix of a received signal, obtaining a new covariance matrix, carrying out the Toeplitz reconstruction of the covariance matrix, enabling the rank of the covariance matrix of the received signal to be recovered to the number of information sources, not to be affected by the signal correlation, and carrying out the estimation of the DOA of the compressed sensing coherent signal. And the azimuth estimation performance is improved. The method comprises the following steps of: firstly, reconstructing a covariance matrix by using Toeplitz, then performing eigenvalue decomposition by using the covariance matrix after Toeplitz reconstruction, and obtaining a DOA (Direction of Arrival) estimated value of a signal in combination with an orthogonal matching pursuit (OMP) algorithm. Simulation results show that compared with a traditional DOA estimation algorithm, the coherent signal DOA estimation method can accurately estimate the coherent signal DOA, has better estimation precision and resolution capability, and does not cause reduction of spatial resolution.

The invention belongs to the technical field of Raman spectrum detection, and relates to a mixture qualitative and quantitative analysis method and system based on Raman spectrum. The method comprises the following steps: taking spectral information of a mixture and a qualitative dictionary as input, adopting a sparseness-based adaptive step-by-step orthogonal matching pursuit method for analysis, preliminarily determining various pure substance components in the mixture and corresponding spectrums and weights thereof, and adding constraint conditions to the pure substance components to obtain a final qualitative analysis result. And finally, taking the mixture spectrum, the qualitative component list and the quantitative dictionary as input of an orthogonal matching pursuit algorithm, and carrying out iterative loop according to qualitative analysis steps to obtain a quantitative analysis result. The components and the concentration of the mixture can be quickly and accurately judged through an orthogonal matching pursuit algorithm; meanwhile, by adding constraint conditions, the problem that analysis results are affected by factors such as baseline drift and noise interference due to the reasons of spectrums is effectively avoided, and the accuracy and efficiency of the analysis results are effectively improved.

The invention discloses a gas compressor near stall state voiceprint continuous monitoring method and system, a medium and equipment, and the method comprises the steps: randomly selecting a preset installation number of microphone measuring points at an inlet to form a microphone array, and carrying out the synchronous collection of multi-channel sound pressure time domain signals; the method comprises the following steps: adding a rectangular window to a multi-channel sound pressure time domain signal, constructing an acoustic time domain signal segment, carrying out fast Fourier transform on the multi-channel acoustic time domain signal segment in a current time domain window to form a plurality of sound pressure frequency spectrums, judging whether a plurality of asynchronous single-tone characteristic frequencies which are non-integer multiples of current rotation frequency exist in the sound pressure frequency spectrums, and if yes, judging whether the sound pressure frequency spectrums exist in the sound pressure frequency spectrums; the method comprises the following steps: constructing a multi-channel microphone continuous frequency domain observation matrix of an asynchronous single-tone characteristic frequency, constructing an orthogonal Fourier transfer matrix based on a microphone sensor installation azimuth angle and a modal highest order, and establishing a compressor near-stall characteristic modal reconstruction model under a non-uniform few-measurement-point condition; and the amplitude is solved based on a block orthogonal matching pursuit algorithm, and compressor near-stall working condition monitoring based on voiceprint features is achieved.

The invention discloses a gear vibration signal compressed sensing method based on adaptive sparse representation, and particularly relates to the technical field of signal processing and mechanical fault diagnos.The method comprises the steps that firstly, a multi-channel vibration sensor is used for collecting gear vibration signals, and the gear vibration signals are preprocessed to obtain high-quality signals; then, an improved K-SVD algorithm is adopted to construct a self-adaptive sparse dictionary, and the sparse representation capability of the signals is improved; thirdly, designing an optimized measurement matrix meeting RIP (Restricted Isometric Property), including a combination of a weighted random Toeplitz matrix and a cyclic matrix, and realizing efficient compressed sampling; in the signal reconstruction stage, a regularization item is introduced, and an improved orthogonal matching pursuit (OMP) algorithm is adopted, so that the reconstruction precision and the anti-noise performance are improved. The method significantly improves the signal reconstruction precision and processing efficiency, and is suitable for the field of real-time monitoring and fault diagnosis.

The invention relates to an unmanned aerial vehicle physical layer secret key secret communication method based on an orthogonal time-frequency space. Comprising the following steps: establishing an unmanned aerial vehicle air-ground communication system consisting of a multi-antenna unmanned aerial vehicle base station, ground single-antenna legal users and ground passive eavesdropping illegal users; obtaining channel estimation vectors of all dominant paths by adopting a three-dimensional structured orthogonal matching pursuit algorithm; the method comprises the steps of obtaining a channel characteristic value of a communication channel through a path gain self-adaptive weighted moving average coding method, carrying out double-bit uniform quantization, carrying out Winnow key negotiation based on dynamic grouping and carrying out SHA-2 hash function confidentiality enhancement, and thus obtaining a physical layer key. According to the method, the channel dimension is converted through the orthogonal time-frequency space technology, the influence of Doppler frequency shift is effectively resisted, the channel reciprocity is improved, the key inconsistency rate is reduced, and the safety and stability of a communication system can be remarkably improved.

The invention discloses a millimeter wave scattering aperture sparse three-dimensional imaging method and a millimeter wave scattering aperture sparse three-dimensional imaging system, and aims to realize high-resolution three-dimensional reconstruction through a sparse reconstruction algorithm aiming at a non-vision field target imaging problem under a rough scattering surface condition. The method comprises the following steps: firstly, improving the spectral resolution of an echo signal by using a time domain zero padding technology, accurately positioning a scattering aperture position based on spectrum peak estimation and completing distance compensation, converting a non-vision field echo into an equivalent vision field echo, and retaining complete information of a target; secondly, in combination with target space scattering point sparsity and scattering aperture sparse sampling characteristics, a virtual array and a measurement matrix are constructed, an imaging problem is converted into a sparse reconstruction task, and a target scattering coefficient is efficiently solved by adopting a generalized orthogonal matching pursuit algorithm; the dependence on a mirror reflection condition is broken through, and a non-vision target can be accurately reconstructed in a diffuse reflection scene; compared with an existing scattering aperture algorithm, the method has the advantage that the imaging resolution and the anti-noise capability are remarkably improved through double sparsity constraints. The method has important application value.

The invention provides a foundation pit support structure lateral displacement prediction method based on dictionary learning fusion monitoring data. The foundation pit support structure lateral displacement prediction method comprises the steps that S1, a physical parameter database is established; s2, performing conversion to obtain weak prior distribution of a compressibility parameter ES; s3, sampling by using Latin hypercube to obtain N alternative parameter combinations of the soil body; s4, establishing a finite element model of the target foundation pit; s5, inputting a parameter combination to calculate corresponding side displacement data of the enclosure structure, and forming an over-complete dictionary D; s6, reading measured side displacement data of the enclosure structure to form a monitoring data matrix Y; S7, extracting corresponding data in the over-complete dictionary D, and forming a dimension transformation matrix A matched with the dimension of the monitoring data matrix Y; s8, obtaining an important atom set and a sparse solution vector x by using an orthogonal matching pursuit algorithm program; and S9, obtaining a side displacement prediction curve of the building envelope corrected by combining the monitoring data. The method has the advantages of high prediction precision, low calculation cost and high response speed.

The invention discloses a wheel track roughness separation method. The method comprises the following steps: resampling an original time domain ABA signal and interpolating the original time domain ABA signal into an angular domain signal with equal angle intervals; according to a wheel rotation total period and a synchronous average window, an angular domain signal of the ABA signal is segmented into N segments by using a synchronous average thought; carrying out downsampling on the segmented segments by using a measurement matrix based on an independent identically distributed Gaussian matrix; adding data points corresponding to each random down-sampling signal and calculating an average value to obtain a sequence of sparse angular domain synchronous average SADSA; reconstructing a sequence based on an orthogonal matching pursuit (OMP) algorithm in a compressed sensing basic theory (CS) to obtain a periodic component extracted from the ABA signal; the invention also discloses an application of the wheel-rail roughness separation method in quantitative detection of rail corrugation, and the invention proposes that ABA signals are subjected to random downsampling and accurate reconstruction by using a compressed sensing principle under the condition of not changing original data attributes.