31 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 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 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 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 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.

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 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 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.

The invention discloses a communication and sensing integrated multi-target direction of arrival estimation method, which comprises the following steps of: constructing a communication and sensing integrated system for describing a communication and sensing collaborative architecture between a first base station and a second base station, and constructing a reconfigurable intelligent reflecting surface signal receiving model and a second base station signal receiving model under the system; carrying out optimization processing on the second base station signal receiving model, constructing a positive semidefinite programming problem model based on atom norm minimization, and taking a minimization signal reconstruction error as an optimization target; carrying out decomposition solving on the matrix by adopting an alternating direction multiplier method of a dual-path self-adaptive penalty mechanism based on residual driving so as to output a Hermitian Toeplitz matrix; and constructing a reconstructed space covariance matrix based on the optimized Hermitian Toeplitz matrix, and performing spectrum peak search by adopting a multiple signal classification algorithm to finally obtain a multi-target direction of arrival estimation value. According to the method, a synergistic effect is formed in three aspects of interference suppression, robust estimation and low-complexity optimization, an efficient and feasible technical scheme is provided for high-precision and low-delay moving target positioning in a 6G sensing integrated system, and meanwhile, a lightweight sensing solution is provided for the Internet of Things with limited resources.

The invention provides an intelligent metasurface (RIS) high-frequency communication system and a near-field channel estimation method. The system comprises a base station provided with a uniform linear array, an intelligent metasurface provided with a uniform planar array and a plurality of users provided with single antennas. The base station and the user are both located in a near-field area of the RIS, and the RIS is located in a near-field area of the base station. The RIS is provided with a transmitting radio frequency chain, the middle row of elements of the uniform planar array are driven to transmit pilot signals in the first stage of channel estimation, and the middle column of elements are driven to transmit pilot signals in the second stage of channel estimation; a base station and a user respectively receive two-stage pilot signals and generate corresponding data samples, and then a serial one-dimensional multiple signal classification algorithm is adopted to independently estimate near-field channel parameters between the base station and the RIS. According to the method, the pilot signals are directly transmitted through the RIS, the two-hop pilot propagation and the double attenuation effect of a traditional cascade channel estimation method are avoided, the precision and efficiency of channel estimation are remarkably improved, and a new scheme is provided for channel estimation of an RIS auxiliary communication system.

The invention discloses an unmanned aerial vehicle DOA joint estimation method based on dual-polarization RIS assistance, and the method comprises the steps: designing a joint reflection matrix of a dual-polarization RIS, and fully utilizing the polarization diversity characteristic to extend the degree of freedom of an array, thereby achieving the effective discrimination of more signal sources under the same physical aperture; the RIS phase is optimized by means of a random optimization subspace mapping algorithm, a high-dimensional problem is subjected to dimension reduction processing through a random projection technology, and the calculation complexity is remarkably reduced while convergence is guaranteed; and a spatial spectrum function is constructed based on a multi-signal classification algorithm, and high-precision and high-resolution DOA estimation is realized by combining global spectrum peak search and a characteristic subspace orthogonality principle. According to the method, the signal source resolution capability and the estimation precision of unmanned aerial vehicle positioning are effectively improved, and meanwhile, the calculation efficiency and the system reliability are better.

The application provides a method for identifying internal leakage of a liquid hydrogen C-type ball valve based on acoustic emission frequency characteristics, and belongs to the technical field of internal leakage detection of liquid hydrogen C-type ball valves. In the application, an acoustic emission sensor array is arranged on the outer surface of the valve seat of the liquid hydrogen C-type ball valve to collect original signals. After adaptive multi-scale wavelet packet decomposition, mixed noise reduction and coherent accumulation enhancement are performed. A material dispersion compensation model is established to extract parameters and input a leakage characteristic identification model to obtain a leakage probability value. When the probability value exceeds a threshold value, fast independent component analysis and sparse reconstruction are used to estimate the number of leakage sources. The spatial angle of the leakage source is located by using a multiple signal classification algorithm. The leakage aperture is calculated by thermodynamic inversion calculation. The turbulent noise characteristics extracted by the fractal theory are fused and judged, thereby solving the technical problems that it is difficult to accurately identify a small leakage source and realize quantitative evaluation of the leakage degree in a strong background noise environment during internal leakage detection of the liquid hydrogen C-type ball valve.

The application discloses a far-field signal source positioning method based on deep learning under unknown mutual coupling, comprising the following steps: acquiring far-field signal data to be positioned, constructing a feature extraction matrix, and inputting the feature extraction matrix into a signal source number detection network model to obtain a predicted signal source number; loading pre-training weight parameters for a covariance reconstruction network model according to the predicted signal source number; inputting the feature extraction matrix into the covariance reconstruction network model after the pre-training weight parameters are loaded, and reconstructing network output according to a toplyiz structure characteristic, and adopting a multiple signal classification algorithm to realize far-field signal source positioning. The application improves the accuracy of signal source number detection by at least 5 percentage points compared with other baseline algorithms when the signal-to-noise ratio is less than 15 dB, improves the positioning accuracy of far-field signal sources by nearly twice compared with other baseline algorithms when the number of signal sources is small, and significantly improves the positioning performance in various harsh environments.

This invention provides a transmission precoding design method and apparatus integrating communication and sensing, relating to the field of communication technology. The method includes: modeling user channel vectors based on the Ricean channel model; constructing a communication signal model by combining the configuration parameters with the transmission precoding matrix to be optimized; discretizing the user's uncertain angle interval into multiple angle sampling points based on the communication signal model and calculating the received signal to construct a target echo signal model; deriving sensing performance indicators based on the target echo signal model and the mean square error of the multiple signal classification algorithm, and constructing a non-convex constraint optimization model; performing semi-definite relaxation on the non-convex constraint optimization model and transforming it for solution to obtain a semi-definite constraint matrix; performing eigenvalue decomposition on the semi-definite constraint matrix, and obtaining the optimized transmission precoding matrix by verifying the largest eigenvalue. This invention solves the problems of inaccurate known user angles and degraded target angle estimation accuracy.

The application discloses a monopole / crossed loop antenna pattern measurement and direction finding error estimation method and system, first, the real distortion pattern is estimated by using the multiple measured patterns of the monopole / crossed loop antenna, the measurement error of the antenna pattern is calculated, then the direction finding error is estimated according to the multiple signal classification algorithm based on the measured antenna pattern and the measurement error. Compared with the existing monopole / crossed loop direction finding error estimation method, the application distinguishes the measured pattern from the real distortion pattern, gives the calculation method of the real distortion pattern and the pattern measurement error, quantifies the influence degree of the pattern measurement error on the azimuth angle estimation, and makes up for the research vacancy of the influence of the pattern measurement error on the antenna direction finding.

Embodiments of the present application provide a target position information determination method and device, network equipment and a storage medium. The method comprises: performing frequency domain point division processing on a received orthogonal frequency division multiplexing echo signal reflected by a target at a first time to obtain an equivalent channel response matrix; resampling a time axis of the equivalent channel response matrix to obtain a first matrix; performing time reversal transformation on a first time signal sequence to obtain a second sequence; the first time signal sequence is obtained by sampling the time axis of the first matrix; determining a target matrix according to the first time signal sequence and the second sequence; the target matrix is used to represent a distance between the base station and the target; and determining position information of the target at the first time and a motion state parameter by using a multiple signal classification algorithm according to the target matrix. The present scheme can efficiently and accurately detect a high-speed moving target without high power consumption and high cost.