197 results about "Signal subspace" patented technology

The invention belongs to the crossing field of information and ocean science and technology, and discloses a DOA estimation method for a UUV broadside parallel co-prime array. According to the method, firstly, a virtual extension array is generated by utilizing an array auto-covariance and cross-covariance matrix, then, Toeplitz completion is carried out on'holes' in the virtual array through trace norm regularization and nuclear norm regularization constraints, a complete covariance structure is recovered, and finally, an extension matrix is constructed, and rotation invariance of a signal subspace of the extension matrix is utilized, so that the covariance structure of the virtual array is obtained. The pitch angle and the azimuth angle of the target are jointly solved, automatic angle pairing is achieved, and the effectiveness and the reliability of the method are verified through simulation results. According to the method, aiming at the application challenges that the UUV broadside array space is limited and the underwater environment is complex, all virtual array elements of the broadside parallel co-prime array are fully utilized, the array freedom degree and estimation precision are remarkably improved, the target detection capacity of the UUV is effectively enhanced, and the method has high practical engineering application value.

The invention provides a sound wave signal self-supervised learning enhanced robust noise reduction processing method and system, and relates to the technical field of signal processing, and the method comprises the steps: carrying out the feature enhancement of an initial time-frequency representation through a dynamic adaptive mask strategy, constructing a self-supervised reconstruction task based on the mask time-frequency representation, separating noise and signal subspaces in a semantic manifold space, and carrying out the self-supervised learning enhanced robust noise reduction. And establishing a probability propagation network in combination with time domain continuity characteristics to model a local dependency relationship, and finally generating a noise reduction weight and realizing semantic fidelity optimization. The method can effectively improve the noise reduction effect and semantic integrity of sound wave signals in a noise complex environment.

The invention discloses a vector hydrophone array orientation estimation method for performing tensor decomposition by using a propagation operator, relates to the technical field of vector hydrophone array orientation estimation, and discloses a vector hydrophone array orientation estimation method for performing tensor decomposition by using a propagation operator. The method comprises the following steps: firstly, constructing a three-dimensional array manifold tensor composed of an array direction matrix and a vector hydrophone output matrix; respectively expanding received signal tensors according to three modes, solving a propagation operator based on a column block covariance matrix, constructing a normalized signal subspace, establishing a spatial spectrum function with a noise subspace, and obtaining a pitch angle and an azimuth angle of a sound source through spectrum peak search; according to the method, high-order singular value decomposition is avoided, the operand is greatly reduced, meanwhile, high resolution and low sidelobe direction finding performance are kept, and the method is suitable for a real-time underwater acoustic direction finding system of a ship-borne platform, a buoy platform and an unmanned platform.

The invention provides a multilayer medium ultrasonic super-resolution imaging method based on a time reversal operator for the blank of a multilayer medium super-resolution imaging technology, and belongs to the technical field of ultrasonic detection. The method specifically comprises the following steps: step 1, placing an ultrasonic phased array probe on the surface of a detected workpiece, and utilizing ultrasonic phased array transceiver equipment to carry out ultrasonic detection on the surface of the detected workpiece; collecting one-transmitting full-receiving data of the N-array-element ultrasonic phased array to obtain full-matrix collection data E; 2, performing singular value decomposition on the collected full-matrix data E in a frequency domain, and selecting a corresponding signal subspace threshold to obtain a signal subspace singular value and a singular vector; 3, calculating an improved Green function GI between the image sampling point and the position of the transducer; 4, the TR-MUSIC super-resolution imaging factor is combined with the TFM imaging factor to obtain a defect image pixel value of the target imaging point Xi, and multi-layer medium ultrasonic super-resolution imaging is completed.

The invention provides a near-field electromagnetic source positioning method based on array signal processing, and relates to the technical field of electromagnetic signal detection and positioning, and the method comprises the steps: constructing an array receiving signal model based on the wave-front characteristics of an electromagnetic wave spherical surface, and employing a steering vector for the construction; a sensor array is used for collecting near-field radiation source signals, and amplitude calibration processing is carried out on the near-field radiation source signals to form an array data set. According to the near-field electromagnetic source positioning method based on array signal processing, high-precision three-dimensional positioning of a near-field electromagnetic source is realized by combining amplitude calibration, characteristic decomposition and joint optimization processing through an array receiving signal model based on electromagnetic wave spherical wavefront characteristics. According to the near-field electromagnetic source positioning method based on array signal processing, a multi-dimensional optimization strategy is introduced in the signal subspace extraction and parameter estimation process, the estimation precision of the distance, the pitch angle and the azimuth angle is improved, and the positioning stability and robustness in a complex electromagnetic environment are improved.

The invention discloses a low-redundancy high-order direction finding method and system based on co-prime characteristics and a computer storage medium, and the method comprises the steps: receiving signals from a plurality of signal sources through employing a low-redundancy array obtained through improvement based on a co-prime array, and obtaining a received signal; calculating a fourth-order cumulant matrix of the received signal according to the received signal; obtaining a covariance matrix according to the fourth-order cumulant matrix; according to the covariance matrix, calculating to obtain a characteristic value and a characteristic vector of the covariance matrix; dividing the feature vector into a signal subspace and a noise subspace according to the size of the feature value; constructing a spectral function according to the projection of the steering vector on the noise subspace; and searching peak values of the spectral function in all possible directions, and determining the direction of the signal source. According to the low-redundancy array obtained based on improvement of the co-prime array, on the basis that the number of receiving array elements is reduced, the number of estimated signal sources is increased, the fourth-order cumulant is adopted, and the positioning precision in a non-Gaussian noise environment can be improved.

The invention discloses a generalized clutter texture distribution-oriented extended target full-adaptive constant false alarm rate detection method, which belongs to the field of radar signal processing, and comprises the following steps of: constructing test statistics according to texture distribution knowledge, covariance matrix structure information, signal subspace and the like; establishing an interpolation function of a threshold offline by using a Monte Carlo method, and estimating a corresponding threshold quickly and precisely according to parameters of a probability density function of a texture component; in a radar target detection process, unknown parameters in texture distribution are estimated by using a second group of training data, a full-adaptive detector is constructed by combining an interpolation function of test statistics and a threshold, and the detector is ensured to have a constant false alarm rate property for the parameters of the texture distribution and the change of a clutter covariance matrix. Compared with a traditional radar target detection method, the cognitive ability of a radar system to a complex environment is remarkably improved, and the method has good engineering application value and popularization potential.

A voice activity detection method and system and a voice enhancement method and system are provided. A voice presence probability of a target voice signal present in microphone signals may be determined by calculating a linear correlation between a signal subspace where the microphone signals are located and a target subspace where the target voice signal is located. The voice enhancement method and system may be used to calculate filter coefficients based on the voice presence probability, so as to perform voice enhancement on the microphone signals. The calculation accuracy of the voice presence probability is improved, and the voice enhancement effect is also improved.

The invention provides a subspace smooth sparse reconstruction passive direction of arrival estimation method under strong interference. The method comprises the following steps: firstly, constructing a far-field airspace sparse signal model received by an array; and obtaining a signal subspace covariance matrix through subspace projection and enhanced space smoothing. And estimating the distribution of the signal power in the spatial domain by using a covariance fitting criterion. And a far-field grid point evolution criterion is formulated, so that the grid points are gradually split along with iteration according to the rule. And outputting the signal power hyper-parameter as a spatial spectrum estimation result, and performing peak searching on the spatial spectrum to obtain a direction-of-arrival estimation result. The method has the advantages that the subspace projection technology is introduced, and the adverse effect of strong interference signals on weak target detection is greatly weakened; by enhancing the spatial smoothing technology, the robustness of coherent signals is improved, and meanwhile, the spatial spectrum reconstruction precision is improved. A grid evolution method is utilized, so that grid points non-uniformly cover an interested airspace with emphasis, and the calculation efficiency of the method is remarkably improved.

The invention discloses an azimuth multichannel SAR channel phase error estimation method and device based on signal subspace matrix rotation invariance, electronic equipment and a storage medium. The method comprises the following steps: converting echo data of each channel into a two-dimensional frequency domain, and compensating a part of a steering vector changing along with Doppler frequency for the echo data of each channel to obtain compensated echo data; dividing the compensation echo data into first sub-array echo data and second sub-array echo data, and respectively obtaining a first signal subspace matrix and a second signal subspace matrix; according to the projection matrix of the first signal subspace matrix and the rotation invariance of the first signal subspace matrix and the second signal subspace matrix, determining a cost function including a channel phase error; and solving the cost function to obtain a phase error estimation value. According to the method, the algorithm operand is reduced, and more stable channel phase error estimation can be realized.

The invention discloses a novel non-uniform array-based signal source positioning method, which comprises the following steps of: determining an actual array element position through flexible array distribution according to environmental characteristics when a target signal reaches the ground; calculating a virtual domain differential common array, determining the position of a virtual array element, constructing a signal model, and calculating a covariance matrix; vectorizing the covariance matrix, and removing redundancy to obtain an equivalent receiving signal of the virtual domain; performing spatial smoothing processing on the equivalent covariance matrix of the virtual domain to obtain a smoothed data correlation matrix; after characteristic decomposition, constructing a signal subspace; and finally, dividing signal subspaces based on an ESPRIT algorithm idea, and calculating a rotation matrix to obtain an estimated angle. The designed non-uniform array can flexibly adjust the array element layout according to complex environment characteristics, the flexible array layout strategy improves the freedom degree of the array, the spatial sampling and signal analysis efficiency is optimized, meanwhile, the calculation path is simplified, and the algorithm complexity is reduced.

The invention discloses a very high frequency broadband radiation source positioning method based on energy weighted subspace fitting, and relates to the technical field of signal processing and radiation source imaging, and the method comprises the steps: carrying out the DFT processing of a lightning very high frequency broadband signal collected by an array, and obtaining any narrowband component; then characteristic decomposition is carried out on covariance matrixes of X-axis and Y-axis sub-arrays according to array receiving signals, main characteristic vectors are taken as signal sub-spaces, in order to emphasize the signal sub-spaces with higher energy, characteristic values are used for weighting, weighted signal sub-spaces are constructed, then the signal sub-spaces are fitted by using a least square method, and the signal sub-spaces with higher energy are obtained; the method comprises the following steps: further constructing a sub-band energy weighted spatial spectrum adapted to a very high frequency broadband signal, then carrying out spectrum peak search on the weighted spatial spectrum to obtain a spatial angle of a spectrum peak, and finally calculating the direction of arrival of a radiation source according to a spatial angle relation to obtain an azimuth angle and an elevation angle. According to the invention, aiming at a lightning very-high-frequency weak radiation source positioning problem, a lightning channel can be inverted more clearly.

The invention discloses a near-field rotation invariant parameter estimation method based on linear fitting, and the method comprises the steps: calculating the cross-correlation between the receiving data of an array element in a first array and the receiving data of an array element in a second array on a signal source three-dimensional space precise propagation model based on a symmetric cross array, and obtaining a cross-correlation matrix; obtaining a virtual receiving data matrix by vectorizing the cross-correlation matrix; performing eigenvalue decomposition on the covariance matrix of the virtual receiving data matrix to obtain a signal subspace matrix; estimating parameters of a narrowband signal source by using an ESPRIT algorithm, specifically, determining a virtual uniform area array according to a covariance matrix, and partitioning a signal subspace matrix into blocks; the rotation invariance is recovered through the subspace relation of the adjacent block matrixes; obtaining the phase difference between the adjacent sub-arrays through the rotation invariance matrix, building a linear observation model, and obtaining the parameter estimation value of the narrowband signal source; the method has the advantages of low calculation complexity and high universality.

This document describes techniques and systems for radar systems with an angle determination process for sparse uniform arrays. The described radar systems include a processor and an antenna that can receive electromagnetic energy reflected by an object in a surrounding environment. The antenna includes a one-dimensional (ID) or two-dimensional (2D) sparse array. The processor can use the received electromagnetic energy to determine a signal subspace associated with the object that includes an invariance equation. Using an estimated solution of the invariance equation, the processor determines a solution of the invariance equation. The solution of the invariance equation is used to determine an angular phase associated with the object. The processor can then use the angular phase to determine an angle associated with the object. In this way, the described angle determination process enables a radar system with a sparse array to efficiently determine an angle associated with an object without blind spots.

The present invention discloses a multi-channel coherent accumulation method of an FDA-MIMO radar based on range-frequency offset compensation, which belongs to the technical field of radar moving target detection. The present invention comprises: obtaining the echo signal of the target by using a two-dimensional planar array FDA-MIMO radar; performing multi-channel matched filtering on the echo signal, and performing FFT transformation in slow time to realize pulse accumulation; then performing covariance matrix calculation to obtain the noise subspace and signal subspace; then performing azimuth and elevation angle search of the target, and obtaining the range-frequency offset coupling compensation vector based on eigendecomposition; multi-channel beamforming, coherently synthesizing the multi-channel signal energy and using a constant false alarm rate to detect the target. The present invention can significantly improve the output signal-to-noise ratio and reduce the computational complexity of coherent accumulation. Moreover, when there is an error in the target distance estimation or the Doppler effect is generated by the frequency offset, the present invention can obtain a higher coherent accumulation gain than the MUSIC algorithm.

The application discloses a kind of real-time detection method and system of food pollutant based on intelligent sensor, comprising: through the multimodal sensor array of deployment in food processing production line key station, sensor response signal is collected;Baseline response under the condition of no pollution is predicted by establishing dynamic baseline prediction model;Signal separation network based on variational decoupling autoencoder is constructed, residual signal is mapped to low-dimensional latent space by sharing encoder and is divided into baseline error subspace and pollutant signal subspace, respectively by two independent decoders reconstructing baseline prediction error signal and pollutant candidate signal;Multi-scale time-frequency transform is carried out to pollutant candidate signal to identify pollutant type and estimate concentration;Through distributed intelligent agent cooperation, pollution traceability and hierarchical early warning are carried out;Cross-scene adaptive calibration is realized using meta-learning framework.The application realizes the real-time decoupling of pollutant signal and matrix change signal in food processing process.

The invention discloses a synthetic aperture passive positioning method based on a short baseline, and mainly solves the problems of large positioning error caused by residual frequency deviation and large estimation error caused by adopting spectrum estimation frequency in the prior art. According to the implementation scheme, the method comprises the steps that a geometric scene comprising a reconnaissance plane, two short baseline antennas and an unknown radiation source is built; obtaining unknown radiation source signals received by two short baseline antennas on the reconnaissance plane according to the geometric scene; performing correlation method processing on the two received signals to obtain a single-frequency signal; root-MUSIC spectrum estimation is carried out on the single-frequency signal, that is, a frequency estimation value is obtained by using orthogonality of a signal subspace and a noise subspace and a polynomial rooting method; and coordinates of an unknown radiation source are solved according to the frequency estimation value. According to the method, the residual frequency deviation caused by inaccurate carrier frequency estimation of the radiation source emission signal is reduced, the spectrum estimation error is reduced, the positioning accuracy and reliability are greatly improved, and the method can be used for unknown signal sources of short base lines and non-continuous short signal sequences without periodicity.

The invention provides a spatial domain-polarization domain multi-dimensional parameter estimation method for a bistatic polarization FDA-MIMO radar, and the method comprises the steps: constructing a dual-system radar system composed of a polarization MIMO radar and a polarization FDA-MIMO radar, and transmitting a signal and receiving an echo signal through the system; calculating a covariance matrix of the echo signal and then decomposing the covariance matrix to obtain a decomposition formula comprising a signal subspace and a noise subspace; constructing a selection matrix by using the signal subspace and the rotation invariant feature of the array element, and then estimating the space angle of the target signal; and constructing a non-singular matrix by using the signal subspace, estimating a polarization parameter of the target signal, and solving a distance parameter of the target signal by combining the angle parameter and the polarization parameter. According to the invention, a polarized MIMO and polarized FDA-MIMO dual-mode working system is utilized to realize joint sensing of target space position information and polarization information, and decoupling and high-precision estimation of multi-dimensional parameters can be effectively realized.

This invention discloses a method and system for separating AIS aliasing signals using a four-circular array antenna. The steps are as follows: S100: AIS signals are received through multiple antennas to obtain the spatial baseband signal matrix X, and the phase error Δφ is calculated using interval calculation. k S200: Calculate the phase compensation matrix p; S200: Compensate the baseband signal according to the phase compensation matrix to obtain the baseband signal X. comp S300: For baseband signal X comp By expanding the spatial and temporal dimensions, we obtain the spatiotemporal snapshot matrix X. st (t); S400: The covariance matrix R is obtained by estimating the spatiotemporal snapshot matrix. xx S500: For the covariance matrix R xx Eigenvalue decomposition is performed to obtain the signal subspace and noise subspace; S600: DOA estimation is performed using the MUSIC algorithm to construct the spatial spectrum P(θ); S700: The beam w at the optimal solution is obtained using the space-time constrained minimum variance algorithm; S800: The separated signal is output through the sparse separation method of protocol features. This method can significantly improve the availability of AIS self-organizing network and provide more reliable protection for ship navigation safety.

The invention relates to an information source number estimation method, in particular to an information source number estimation method based on orthogonal matching pursuit and signal subspace matching. The invention aims to solve the problems that the signal-to-noise ratio of array snapshot data in an underwater acoustic environment is generally not high, the array snapshot data is easily interfered by colored noise and coherent signal sources, and for a high-speed moving target, the number of effective snapshots is small, so that the accuracy of traditional signal source number estimation is low. According to the method, an orthogonal matching pursuit method is utilized to iteratively solve a support vector and a feature vector corresponding to a residual maximum feature value of the support vector to construct two subspaces, and signal source number estimation is realized through a signal subspace matching criterion. Simulation results show that compared with an existing signal source number estimation method, the method has the advantages that the requirement for the signal-to-noise ratio is lower, the performance is better under the condition of small snapshots, and meanwhile the method is not sensitive to coherent signal sources and colored noise. Lake test data processing results show that the method can effectively estimate the number of fixed and moving underwater acoustic targets.

The present invention provides a high signal-to-noise ratio imaging method for synthetic aperture data. First, the STA data of the input biological material is preprocessed to filter out the direct wave; then the preprocessed STA data is extrapolated to the target layer to obtain the STA data of the target layer; the singular value decomposition (SVD) is used for the STA data of the target layer to extract the signal subspace, and then the cross-spectrum matrix (CMS) corresponding to each frequency is calculated; finally, the cross-spectrum matrix of each frequency is deconvolved by using the unsteady point spread function (PSF) to obtain the imaging result corresponding to each frequency, and then the imaging result of the biological material is obtained by iterative calculation frequency by frequency. The imaging method of the present invention uses SVD to eliminate most of the noise in the STA data, and uses PSF for deconvolution to effectively suppress the speckle artifacts in the imaging process, greatly improving the signal-to-noise ratio, enhancing the imaging quality, with small computational amount and high imaging efficiency.

The invention discloses a weighted ESPRIT-based DOA estimation method under the assistance of a semi-passive intelligent reflection surface, and the method comprises the steps: constructing a DOA estimation model under the assistance of the semi-passive intelligent reflection surface, and obtaining a receiving signal; thirdly, calculating a covariance matrix of a received signal, decomposing the characteristics of the covariance matrix, and extracting a signal subspace and a characteristic value; secondly, constructing a Gram matrix, performing characteristic decomposition on the Gram matrix, and extracting a signal subspace and a characteristic value; then, calculating a weight parameter according to the characteristic value; and finally, weighting and fusing the signal subspace information to obtain DOA estimation. According to the method, the target can be effectively sensed under the condition that the base station is shielded, and DOA estimation is carried out. In addition, the characteristics of the intelligent reflection surface are fully utilized, an adaptive weighting mechanism is introduced, and the DOA can be estimated robustly. Simulation results show that the DOA estimation precision of the algorithm provided by the invention is superior to that of a traditional multiple signal classification method, and is close to and approaches the Cramer-Rao bound with an atomic norm minimization algorithm.

The invention discloses a holographic MIMO near-field channel estimation method based on a spatial correlation matrix, and the method comprises the steps: carrying out the modeling of a 3D H-MIMO channel based on a non-uniform spherical wave model, and building an H-MIMO near-field channel model; calculating a spatial correlation coefficient between antenna units at a base station end, introducing a generalized single-ball scatterer model, and deducing to obtain a near-field spatial correlation matrix; eigenvalue decomposition is carried out, and a low-dimensional signal subspace is constructed; designing a pilot frequency matrix, wherein the pilot frequency time slot number in the pilot frequency matrix is set as the rank of the low-dimensional signal subspace; and estimating the low-dimensional signal subspace coefficient to obtain a channel estimator of the low-dimensional signal subspace. According to the channel estimation method, spatial correlation prior information is effectively utilized, and the pilot frequency overhead and the calculation complexity are remarkably reduced.

The invention provides an angle capturing method based on a two-dimensional MUSIC algorithm and related equipment, and relates to the technical field of wireless communication. The method comprises the following steps: receiving a sampling signal and a radio frequency signal, and obtaining a plurality of snapshot data according to the radio frequency signal; calculating a covariance matrix of the radio frequency signal based on the snapshot data, performing eigenvalue decomposition on the covariance matrix, and determining a signal subspace and a noise subspace according to the obtained eigenvalue; calculating a two-dimensional MUSIC spatial spectrum based on the noise subspace; calculating a dynamic threshold, and obtaining a plurality of candidate angles according to the dynamic threshold; performing image rejection processing on each candidate angle to obtain an effective candidate angle, accumulating the effective candidate angle into a two-dimensional statistical histogram, and processing to obtain a two-dimensional probability distribution diagram; selecting a first estimation angle from the two-dimensional probability distribution map; and determining an angle capture state of the target based on the first estimated angle and a second estimated angle at the previous moment. By adopting the method, the angle capturing accuracy can be improved.

The present invention discloses a reference signal fraud attack detection method, device and electronic device. The method includes obtaining the null space using the channel covariance matrix stored in the base station; the channel covariance matrix is ​​the channel covariance matrix of the SRS signal; calculating multiple consecutive instantaneous channel characteristics of the received signal, and obtaining the projections of the multiple instantaneous channel characteristics in the null space; if the residual noise energy existing in the multiple projections is greater than a predetermined detection threshold, it is determined that an SRS attack signal exists in the received signal; the detection threshold is determined according to a set false alarm probability. By introducing the null space of the channel covariance matrix with a low-rank structure, the separation accuracy of the user and attacker signal subspaces can be effectively improved, and attack detection is performed based on a sequential approach focusing on the energy mutation after the null space projection, so that the detection results are more accurate and robust.

The invention relates to a direction of arrival estimation method and device based on a sensor array, computer equipment, a medium and a product. The method comprises the following steps: establishing a signal model of a source signal and a sensor array, determining a signal subspace according to the signal model, determining a first selection matrix and a second selection matrix, carrying out submatrix division on the signal subspace through the first selection matrix, obtaining a reference direction cosine according to the divided first submatrix, and obtaining a reference direction cosine according to the reference direction cosine; and performing sub-matrix division on the signal sub-space through a second selection matrix, obtaining a fuzzy direction cosine according to a second sub-matrix obtained through division, performing phase compensation on the fuzzy direction cosine through a reference direction cosine to obtain a target direction cosine, and determining a two-dimensional arrival direction of the source signal according to the target direction cosine. By adopting the method, space response and polarization response information output by the array can be fully utilized, and high-precision two-dimensional arrival direction estimation is realized.

The invention discloses a high-impedance fault detection method based on transient signal spectrum differences, and belongs to the technical field of power distribution network fault detection. Transient zero-sequence current signals of all lines of a power distribution network are collected, and high-resolution spectrum characteristic spectrums corresponding to all the lines are generated through the separation step of signal subspaces and noise subspaces; establishing a frequency spectrum matrix difference quantification model, converting the frequency spectrum characteristic spectrum into a two-dimensional data matrix, and quantifying frequency spectrum difference characteristics among different lines by adopting a matrix norm calculation method to obtain a difference coefficient; based on a double-layer discrimination threshold system, setting a fault similarity coefficient as a first-layer discrimination threshold, and screening out a potential fault line combination; and setting a fault judgment coefficient as a second-layer judgment threshold value, performing difference comparison on the potential fault line and the normal line, and identifying a high-impedance fault line. The influence of normal transient disturbance such as load switching and capacitor bank switching is eliminated by using the characteristic of transient signal frequency spectrum difference.

The application discloses a coherent signal direction of arrival estimation method and system, which is used for solving the technical problem that the existing coherent signal direction of arrival estimation method leads to high estimation cost. The method comprises the following steps: acquiring a plurality of far-field coherent spatial narrowband source signals at multiple time points; constructing an output signal matrix according to the plurality of far-field coherent spatial narrowband source signals at the multiple time points; determining a reference auxiliary output signal and a signal subspace estimation value based on the output signal matrix; constructing a minimum mean square error optimization model by using the reference auxiliary output signal and the signal subspace estimation value; solving the minimum mean square error optimization model by using a gradient descent method to determine a target to-be-estimated parameter; and determining a target coherent signal direction of arrival based on the target to-be-estimated parameter.

This invention belongs to the field of signal processing, and particularly relates to direction-of-arrival (DOA) estimation for electromagnetic and sonar signals. Specifically, it is a subspace-based DOA estimation method based on a distributed algorithm, which can be used for passive localization and target detection. The method includes the following steps: S1, establishing a distributed array model at the receiver; S2, calculating the signal subspace of the received signal; S3, calculating the weight w(θ); S4, calculating the spatial spectrum and performing a spatial domain search to find the DOA value. The proposed method achieves distributed solution of the algorithm, thus fundamentally avoiding the shortcomings of centralized algorithms. Simultaneously, it maintains good estimation performance, similar to that of centralized algorithms, and outperforms distributed MUSIC methods at low signal-to-noise ratios.