40 results about "Multiple signal classification algorithm" patented technology

The invention relates to the technical field of wireless communication, in particular to an angle-distance joint positioning method in a near-field communication system assisted by wave beam squint, which comprises the following steps of: determining a starting point (theta s, rs) and an end point (theta e, re) of a near-field sensing area, and determining a distance-to-angle joint in the near-field sensing area by adjusting parameters of a true time delayer and a phase shifter. Generating a beam squint focusing scanning track for joint angle-distance positioning; the method comprises the following steps: a base station sends a pilot signal, receives an echo signal of a user side on each subcarrier, and reversely deduces an initial angle estimation value and an initial distance estimation value of a target user by calculating receiving power and searching a subcarrier index corresponding to a power peak value; and a local search area is selected near the initial estimation value obtained in the coarse positioning step, angle and distance two-dimensional joint search is carried out based on an improved near-field multiple signal classification algorithm, and a high-precision final angle estimation value and a high-precision final distance estimation value are output.

The invention provides a LoRa positioning method and system based on symbol-level frequency hopping, and the method comprises the steps: a commercial LoRa node generates a LoRa signal, and transmits a signal containing symbol-level frequency hopping through dynamically adjusting the carrier frequency; the receiving gateway receives the symbol-level frequency hopping signal, aligns a demodulation window by using a time-frequency window alignment algorithm and eliminates frequency offset; and the operation server integrates cross-band channel state information of the frequency hopping signals through coherent multi-channel splicing, calculates a power delay spectrum, jointly estimates an angle of arrival and flight time by using a multi-signal classification algorithm, and carries out fusion calculation to obtain a target node position. According to the method, the positioning precision is remarkably improved, and the positioning delay is greatly shortened.

The application relates to the technical field of wireless communication, in particular to a beam squint auxiliary angle-distance joint positioning method in a near field communication system, which comprises the following steps: determining the starting point (theta s ,r s ) and the ending point (theta e ,r e ) of the near field sensing area, generating a beam squint focusing scanning track for joint angle-distance positioning by adjusting the parameters of the true time delay device and the phase shifter; a base station sends a pilot signal, receives echo signals of a user terminal on each subcarrier, calculates the received power, finds the subcarrier index corresponding to the power peak value, and reversely deduces the initial angle estimation value and the initial distance estimation value of the target user; a local search area is selected near the initial estimation value obtained in the coarse positioning step, a two-dimensional joint search of the angle and the distance is carried out based on an improved near field multiple signal classification algorithm, and a high-precision final angle estimation value and a final distance estimation value are output.

The invention discloses a transformer partial discharge multi-target positioning method and system based on an ultrasonic array. The method comprises the following steps: S1, receiving an ultrasonic signal and constructing a data matrix; s2, calculating a covariance matrix and performing characteristic decomposition; s3, estimating the number of partial discharge sources based on a Gerschnoid circle criterion; s4, determining the spatial orientation of the discharge source based on a multi-signal classification algorithm; and S5, calculating space coordinates through multi-platform direction-finding cross positioning: synchronously measuring the azimuth angle theta and the pitch angle of the same discharge source through at least two independently arranged ultrasonic arrays, combining the azimuth angle theta and the pitch angle with the space position coordinates of the arrays, establishing an equation set based on a triangular relationship, and solving the equation set to obtain the three-dimensional coordinates of the discharge source so as to realize multi-target positioning. The method has the advantages of high positioning precision and the like.

The application provides a LoRa positioning method and system based on symbol level frequency hopping, and the method comprises the following steps: a commercial LoRa node generates a LoRa signal, and sends a symbol level frequency hopping signal by dynamically adjusting a carrier frequency; a receiving gateway receives the symbol level frequency hopping signal, aligns a demodulation window by using a time-frequency window alignment algorithm, and eliminates frequency offset; a calculation server integrates cross-band channel state information of the frequency hopping signal by coherent multi-channel splicing, calculates a power delay spectrum, jointly estimates an angle of arrival and a time of flight by using a multiple signal classification algorithm, and obtains a target node position by fusion calculation. The method of the application significantly improves positioning accuracy and greatly shortens positioning delay.

The invention discloses an indoor positioning method and system, and the method comprises the following steps: carrying out the enhancement processing of original IQ in-phase orthogonal signals collected by multiple antennas through a lightweight neural network, and outputting an anti-multipath interference enhanced IQ signal matrix; and constructing a covariance matrix based on the enhanced signal matrix, and calculating an azimuth angle and a pitch angle by using a MUSIC multiple signal classification algorithm. According to the invention, multipath interference can be effectively suppressed, phase jitter is eliminated, multichannel feature fusion is realized, and the accuracy of indoor positioning is improved.

The application discloses a millimeter wave radar gesture control method and related devices, and relates to the technical field of data analysis. The method comprises: performing clutter suppression processing on each frame of gesture signal data; performing effective gesture signal extraction and signal reconstruction on each frame of gesture signal data after clutter suppression processing based on modal component screening, to obtain a plurality of frames of target gesture signal data; performing distance-angle graph analysis and enhanced radar spectrum graph analysis on the plurality of frames of target gesture signal data, and performing feature extraction by using a multiple signal classification algorithm, to obtain target feature data; determining target weights of each frame of target gesture signal data, and performing gesture recognition by using a multi-task learning gesture recognition model in combination with the target feature data; and matching operation instructions based on a gesture recognition result to perform device control. The application can improve the reliability of gesture recognition and realize more accurate gesture control.

The application discloses a MIMO-OFDM omnidirectional target parameter estimation method based on segmented echo parameter adaptive matching, and specifically comprises the following steps: a two-stage forward-backward average multiple signal classification algorithm is used to estimate the angle parameter of a potential target in a super-resolution manner; a discrete Fourier transform is performed on the echo signal along the antenna dimension to extract segmented echoes, and a known angle-signal correlation term is reconstructed through the accurate angle parameter estimation value of the target; DFT and cross-correlation operation are performed along the subcarrier dimension, a global peak value is obtained through non-coherent accumulation in the cross-symbol dimension, and the distance parameter of the target is estimated; a cross-symbol complex sequence is taken out and point DFT is performed to obtain a Doppler spectrum, and then the speed parameter of the target is estimated; and the parameter estimation of all targets is completed through the above steps. The application overcomes the defect that the overall performance is degraded due to error propagation in the existing successive estimation framework, and the parameter estimation performance is significantly improved compared with the existing successive estimation method.

The invention discloses a multi-target positioning method and device based on a wireless signal, a medium and a product, and relates to the field of wireless sensing, and the method comprises the steps: carrying out the static noise filtering of a reflected signal; performing FFT operation on the filtered reflection signal on a fast time axis to obtain distance dimension data, and performing FFT operation on a slow time axis based on information in each distance gate corresponding to the distance dimension data to obtain a distance Doppler map; clutter suppression is carried out on the distance Doppler map through a CFAR algorithm, and a target distance index is recorded; constructing a two-dimensional data block based on the distance dimension data of the plurality of channels and the target distance index; on the basis of the two-dimensional data blocks, angle information of multiple targets is obtained through a self-adaptive second-order difference multi-signal classification algorithm; constructing a distance-azimuth spectrogram based on the angle information and the target distance index; therefore, when the multiple targets move in the range smaller than the radar angle resolution, accurate positioning and counting of the targets can be achieved.

The application discloses an unmanned aerial vehicle integrated comprehensive monitoring system and method, and relates to the technical field of unmanned aerial vehicle management. The system synchronously broadcasts a standard 5G synchronization signal block and receives airspace target echoes to generate a local detection spectrum; symbol-level fusion processing is performed on the local detection spectrum of multiple base stations, an improved spatial smoothing multiple signal classification algorithm is used for joint spectrum bias minimization processing, and the position and speed of a target unmanned aerial vehicle are extracted; the identity legality and flight category of the target unmanned aerial vehicle are identified; the perception capacity is dynamically estimated, and traffic scheduling is performed when overload occurs; flight instructions are generated or security linkage measures are triggered according to the identification result; and task load data returned by the unmanned aerial vehicle is processed and abnormality detection is performed. The application can improve the coverage and precision of low-altitude airspace unmanned aerial vehicle synchronous perception, accurately identify illegal flight behavior and quickly respond, and enhance the airspace safety monitoring capacity in complex environments.

The application discloses a kind of intelligent metasurface assisted multi-target positioning system, belong to wireless communication field.The system includes: intelligent metasurface;Receiver;Multiple wireless access points, can periodically emit probe signal, and the probe signal can reach intelligent metasurface by multiple targets, reach receiver after being reflected by intelligent metasurface;Received signal model construction module is used to obtain the expression of the received signal of intelligent metasurface and receiver under different time block time slot;Virtual multidimensional signal construction module calculates the multidimensional signal according to the received signal of receiver, obtains the virtual steering vector received by receiver;And, spatial information positioning module is used to obtain the spatial spectrum of multiple signal classification algorithm;The steering vector corresponding to multiple peak values in spatial spectrum is obtained by searching the spatial spectrum, and the angle and distance of multiple targets are obtained.

The present invention discloses a method for jointly estimating the AOA and TOA of signals based on a dimensionality reduction multiple signal classification algorithm. The method comprises the following steps: converting the time domain signal of an ultra-wideband multipath signal received by a uniform linear array into a frequency domain form to construct a frequency domain model of the received signal; calculating the covariance matrix of the frequency domain model to obtain a noise subspace, and constructing a two-dimensional MUSIC spectrum peak function based on the orthogonal relationship of the signal steering vectors; performing dimensionality reduction processing on the two-dimensional MUSIC spectrum peak function, estimating the AOA of the ultra-wideband multipath signal through a one-dimensional angle search, and estimating the TOA based on the estimated incident angle to discriminate the main path signal angle of the ultra-wideband multipath signal. The method achieves high-precision TOA and AOA estimation, while significantly reducing the computational complexity compared to a two-dimensional multiple signal classification algorithm. Furthermore, the method can distinguish the main path signal independently of the sampled values ​​of the transmitted signal.

The invention relates to the technical field of wireless sensing, and discloses an RFID (Radio Frequency Identification Device) pose estimation non-line-of-sight shielding influence suppression method based on antenna weight, which comprises the following steps of: S1, constructing a relation model of a label position and a non-line-of-sight shielding error; s2, distributing antenna weights according to the theoretical phase difference and the actual phase difference between each antenna and the reference antenna; s3, constructing an augmented Lagrangian convex optimization algorithm according to the relation model in the S1 and the antenna weight in the S2, and finally obtaining label position information by continuously iteratively inhibiting the influence of non-line-of-sight shielding; and S4, in combination with an antenna weight and a multi-signal classification algorithm, label attitude information is obtained through peak detection. By constructing a relation model of a label position and a non-line-of-sight occlusion error, the error size is quantified instead of being simply regarded as environmental noise; in addition, through an adaptive antenna weight distribution mechanism based on phase residual statistical analysis, the shielding condition of the antenna is automatically identified, and the corresponding weight is reduced.

This invention discloses a switching time-modulated harmonic direction finding device and method, belonging to the field of radio frequency signal direction finding technology. It includes a radio frequency switching unit, a control unit, an ADC acquisition module, and a digital processing module. The radio frequency switching unit achieves signal time modulation through periodic switching of PIN diodes, coupled with a compensation network to optimize impedance matching and isolation performance. The control unit uses a high-speed comparator to output a stable, high-speed control signal. The ADC acquisition module performs analog-to-digital conversion. The digital processing module recovers the equivalent direction finding signal using a signal recovery algorithm based on the time-modulated sequence and estimates the direction of arrival based on a multiple signal classification algorithm (MUSIC). The method includes signal modulation, analog-to-digital conversion, equivalent signal recovery, and direction estimation steps. This invention eliminates the need for high-precision phase shifters and multi-channel parallel complete receiving links, simplifying the system structure and reducing hardware costs while retaining array direction finding capabilities. It is suitable for radar, communication, and other scenarios, balancing hardware simplification and direction finding accuracy.

The invention relates to the technical field of optical fiber sensing, in particular to a rapid space positioning method based on improved space phase shift, which comprises the following steps of: firstly, acquiring a sensing array signal, designing a space phase shift angle by adopting an improved space phase shift algorithm and particularly utilizing a relationship among the space phase shift angle, sampling frequency and acousto-optic modulator frequency shift; and a spatial phase shift matrix is constructed by directly using the intermediate frequency signals to quickly obtain phase signals of each sensing array, and the phase signals are processed through a multiple signal classification algorithm to determine the specific position of a sound source. According to the method, the real-time performance of sound source positioning of the system is effectively improved, in addition, the improved space phase shift algorithm is utilized in the demodulation process, complex frequency mixing filtering operation and additional hardware equipment are reduced, and the system cost is reduced.

The application provides a communication and sensing integrated system sensing assisted beam forming method, and relates to the technical field of communication; the method comprises the following steps: S10, an ISAC base station sends a reference signal, the reference signal comprises a reference signal sent omnidirectionally in an initialization stage and a reference signal sent directionally according to a preset encoding vector f k in a sensing assistance stage; S20, an ISAC receiving end utilizes a return signal to acquire parameters of surrounding targets or users based on orthogonal matching pursuit (OMP) and multiple signal classification (MUSIC) respectively; S30, the distance and angle of the targets or users are obtained by using a sensing time slot, and the encoding vector f k is calculated; S40, steps S20 and S30 are repeated to realize sensing assisted cellular communication beam forming; the application has the beneficial effects that high-precision position information of the ISAC receiving end can be sensed, and more accurate sending beams can be formed.

Provided are a direction of arrival (DOA) estimation method and system for a sparse array based on Vandermonde decomposition reconstruction, relating to the technical field of array signal processing. The method includes: constructing a covariance matrix completion optimization model based on sparse array signals and uniform linear array signals, and performing Vandermonde decomposition by using characteristics of a uniform linear array; introducing a nuclear norm to optimize a rank function in the model, and updating the covariance matrix completion optimization model; and introducing an auxiliary variable to transform the model into a solvable optimization problem, and solving the problem by an alternating direction multiplier method to obtain an optimal estimation value. The DOA is estimated using a root multiple signal classification algorithm.

The invention belongs to the technical field of wireless communication security, and discloses an MIMO system equipment identity authentication method based on mutual coupling and spatial AoA, which is realized through the following steps: a transmitting end communicates with a receiving end, an uplink millimeter wave channel is constructed, a communication model with a bimodal characteristic is established, namely, a signal is received, and the signal is transmitted to the receiving end; the communication model comprises a mutual coupling fingerprint model and an AoA fingerprint statistical model, and the mutual coupling fingerprint model comprises a transmitting array mutual coupling matrix and a receiving array mutual coupling matrix; a multi-signal classification algorithm based on a feature space is adopted to extract MC features and an AoA value of a communication model, a receiving end judges whether a current received signal is from legal equipment or an attacker based on the extracted MC features and the extracted AoA value, and authentication is completed. According to the method, a hardware-level MC effect and space arrival angle characteristics are combined, an efficient and high-robustness bimodal physical layer authentication scheme is provided, and a new solution is provided for a future 6G high-security scene.

The invention belongs to the technical field of sensing positioning, and relates to a non-contact personnel trajectory tracking method, which comprises the following steps of: acquiring original channel state data, and performing phase calibration on the original channel state data to obtain calibrated channel state data; adopting a super-resolution multi-signal classification algorithm to obtain an initial position of a track; establishing a geometrical relationship model between the calibrated channel state data and the reflection path length, and calculating the reflection path length variation of the personnel relative to the tracking equipment based on the geometrical relationship model; and obtaining a personnel trajectory based on the initial position and the reflection path length variation. The invention also provides non-contact personnel trajectory tracking equipment, which comprises an antenna assembly, a shell assembly, a sensing module, a development board module and a power supply assembly, the sensing module, the development board module and the power supply assembly are sequentially stacked and connected from top to bottom along the vertical direction, and the sensing module comprises two network cards working in different channels. According to the invention, people do not need to wear any equipment, and the method has the advantages of wide coverage, high precision, low deployment cost and the like.

The invention discloses a robust adaptive beamforming method based on null broadening and main lobe interference detection and elimination, which uses time decay covariance matrix sampling to improve the real-time performance of an algorithm, reconstructs a covariance matrix to separate a desired signal and interference, uses virtual interference rotation broadening null, and uses the main lobe interference detection and elimination to detect and eliminate the main lobe interference. And main lobe interference detection based on an improved multiple signal classification algorithm is used, and interference in a main lobe is eliminated. According to the beam forming method, the output signal to interference plus noise ratio in a high dynamic environment is effectively improved, and the system performance is improved. Compared with an existing classical beam forming algorithm in a high dynamic environment, the scheme provided by the invention has obvious performance gain.

The application relates to a kind of based on reconstruction subspace's super-resolution two-dimensional signal angle of arrival estimation method, comprising the following steps: S1, covariance matrix is constructed;S2, signal subspace matrix and noise subspace matrix are established;S3, construct two-dimensional multiple signal classification algorithm spatial spectrum expression;S4, based on eigenvalue decomposition obtains multiple eigenvalues and corresponding multiple eigenvectors;S5, based on eigenvalue, eigenvector is sorted, and constitutes to be eliminated matrix;S6, reconstruction subspace matrix is constructed, and S6 is repeated to carry out iterative calculation, and reconstruction subspace matrix is obtained Reconstruction subspace matrix set is formed;S7, simultaneously reconstruction subspace matrix set and spatial spectrum expression, obtain new spatial spectrum function set;S8, to new spatial spectrum function set is jointly estimated, and signal angle of arrival is obtained.Compared with prior art, the application has the advantages of high estimation accuracy.

The invention provides a method for recognizing liquid hydrogen C-type ball valve inner leakage based on acoustic emission frequency characteristics, and belongs to the technical field of liquid hydrogen C-type ball valve inner leakage detection. After self-adaptive multi-scale wavelet packet decomposition, mixed noise reduction and coherent accumulation enhancement are carried out, a material frequency dispersion compensation model is established, parameters are extracted and input into a leakage feature recognition model to obtain a leakage probability value, and when the probability value exceeds a threshold value, rapid independent component analysis and sparse reconstruction are adopted to estimate the number of leakage sources; the space angle of a leakage source is positioned by using a multi-signal classification algorithm, the leakage aperture is calculated through thermodynamics-driven inversion, and fusion judgment is carried out by combining turbulence noise features extracted by a fractal theory. The technical problem that it is difficult to accurately recognize a tiny leakage source and achieve quantitative evaluation of the leakage degree in the strong background noise environment during inner leakage detection of the liquid hydrogen C-type ball valve is solved.

The invention relates to the technical field of fault detection, and discloses a thermal runaway detection method, device and equipment, a storage medium and a program product. According to the method, initial delay summation output corresponding to a plurality of grid points is obtained through a multiple signal classification algorithm to serve as an iteration initial value, a plurality of sound source positions can be effectively positioned, a sound source recognition result is sharpened through multiple iterations, the main lobe width is reduced, side lobe interference is attenuated, the detection resolution is improved, and the detection accuracy is improved. The initial delay summation output corresponding to the multiple grid points is screened through the preset screening condition, the initial delay summation output which does not meet the preset screening condition is replaced with the preset value to directly serve as the output result, the output result does not participate in the subsequent iteration process, the calculation amount can be reduced, the detection efficiency can be improved, and therefore the thermal runaway detection accuracy can be improved when the thermal runaway detection function is achieved. And the resolution ratio and the efficiency are high.

The invention discloses a monitoring direction-finding method for spatial spectrum estimation and beam forming based on channel correction, and relates to the technical field of wireless spectrum monitoring, and the method comprises the steps: carrying out the channel correction of a direction-finding system, so as to eliminate a phase error caused by the inconsistency between a plurality of direction-finding channels, acquiring real phase difference information of the antenna array receiving signals; receiving signals by using the antenna array subjected to channel correction, and performing spatial spectrum estimation through a multiple signal classification algorithm to obtain the direction of arrival of one or more incident signals; and selecting a desired signal direction according to the direction of arrival, carrying out adaptive beam forming by adopting a minimum variance criterion based on linear constraint, and carrying out weighting processing on an antenna array receiving signal so as to enhance a desired signal and suppress an interference signal. According to the invention, the direction finding precision and the signal enhancement capability are improved in a complex electromagnetic environment and a long-term operation condition.

Provided are a direction of arrival (DOA) estimation method and system for a sparse array based on Vandermonde decomposition reconstruction, relating to the technical field of array signal processing. The method includes: constructing a covariance matrix completion optimization model based on sparse array signals and uniform linear array signals, and performing Vandermonde decomposition by using characteristics of a uniform linear array; introducing a nuclear norm to optimize a rank function in the model, and updating the covariance matrix completion optimization model; and introducing an auxiliary variable to transform the model into a solvable optimization problem, and solving the problem by an alternating direction multiplier method to obtain an optimal estimation value. The DOA is estimated using a root multiple signal classification algorithm.

The invention discloses a millimeter wave radar gesture control method and a related device, and relates to the technical field of data analysis, and the method comprises the steps: carrying out the clutter suppression processing of each frame of gesture signal data; performing effective gesture signal extraction and signal reconstruction on each frame of gesture signal data after clutter suppression processing based on modal component screening to obtain a plurality of frames of target gesture signal data; performing distance angle diagram analysis and enhanced radar spectrogram analysis on the plurality of frames of target gesture signal data, and performing feature extraction by using a multiple signal classification algorithm to obtain target feature data; determining a target weight of each frame of target gesture signal data, and performing gesture recognition by using a multi-task learning gesture recognition model in combination with the target feature data; and matching an operation instruction based on the gesture recognition result to perform equipment control. According to the invention, the reliability of gesture recognition can be improved, and gesture control with higher precision can be realized.

The application discloses an indoor multi-person trajectory tracking method based on angle of arrival-time of flight combination and belongs to the technical field of wireless signal processing. In view of the problem that the indoor trajectory tracking precision of the current WiFi signal is poor, channel state information is extracted from a WiFi device, and original channel state information is denoised from amplitude and phase. The signal time of flight of each multipath signal is extracted from the denoised channel state information, the angle of arrival of a dynamic reflection path is estimated in combination with a multi-signal classification algorithm, a plane coordinate system is constructed, and the plane coordinates of a target are tracked through the angle of arrival. The application establishes a multi-person tracking model, uses a novel signal classification algorithm, can solve multiple target path information compared to a traditional method which can only solve path information less than the number of receiving antennas, and greatly improves the practicability of the trajectory tracking technology based on the WiFi signal and the generalization ability of the model.

The invention discloses a super-resolution multipath time delay estimation method for Fourier precoding OCDM signals in a dynamic scene, and the method comprises the steps: carrying out the Fourier precoding of a pilot symbol, generating a precoding orthogonal linear frequency modulation wavelength division multiplexing signal through modulation, and eliminating the coupling effect between the time delay and Doppler frequency shift in a time-frequency double-selection channel; doppler frequency shifts of different paths are directly estimated according to the position offset of the received pilot signals in the Fresnel domain, and the number of the multiple paths is determined; and calculating a covariance matrix of the received signal, carrying out decoherence processing, carrying out subspace decomposition on the covariance matrix by using a multiple signal classification algorithm to obtain a spatial spectrum, and determining a multipath time delay estimation value according to a spectrum peak position of the spatial spectrum. The method is suitable for underwater acoustic mobile communication and environment perception with Doppler frequency shift, the relative root-mean-square error of time delay estimation can be remarkably reduced in a high-speed state, and a reliable solution is provided for super-resolution time delay estimation in a dynamic scene.

The embodiment of the application provides a kind of based on smart reflecting surface detection environment perception and electromagnetic deception method and related equipment, belong to wireless communication technical field.The method first utilizes L type perception array embedded on target to receive radar signal, accurately estimates the channel parameters of radar and environment scatterer cluster, including angle of arrival and signal power gain by multiple signal classification algorithm and least square algorithm;Subsequently, under the premise of strictly limiting radar received target echo power below detection threshold, an optimization model is established to maximize the selected decoy cluster echo power;Finally, the closed-form or semi-closed-form solution of IRS reflection coefficient is derived using the Lagrange multiplier method or phase alignment method, and the IRS is configured accordingly.The application can efficiently generate false targets using the scatterers in the surrounding environment to confuse radar detection, while achieving true target stealth, with low computational complexity and high real-time performance, and can be widely applied in the electronic countermeasure field of mobile platforms such as aircraft and missiles.