181 results about "Multiple signal classification" patented technology

The invention provides a millimeter wave radar-based bridge deformation monitoring method and system, and the method comprises the steps: obtaining a transmitting signal and an echo signal of a radar, and carrying out the preprocessing of the signals, and obtaining an intermediate frequency signal; processing the intermediate frequency signal by adopting matched filtering and a zoomFFT algorithm to obtain target distance information; processing the intermediate frequency signal by adopting a MUSIC algorithm to obtain target angle information; and obtaining a target distance angle unit by combining the target distance information and the target angle information, and obtaining target deformation information by adopting phase difference and phase unwrapping. According to the invention, the interference of noise and background can be avoided, the deformation displacement of the target area can be accurately calculated, and the real-time monitoring and analysis of the deformation state of the bridge can be realized.

The invention provides a coherent signal arrival direction estimation method and device based on a deep convolutional network, and belongs to the field of array signal processing. The method comprises the following steps: receiving a to-be-detected signal containing a coherent signal by using a uniform linear array antenna to obtain an array receiving data matrix and extract a covariance matrix; forming an input feature vector by right upper triangular elements divided from a diagonal line in the covariance matrix, inputting the input feature vector into a covariance estimation model formed by a deep convolutional network, obtaining an estimation value of the right upper triangular elements under an ideal incoherent condition, and reconstructing the estimation value to obtain a covariance matrix estimation value; and performing characteristic decomposition on the covariance matrix estimation value, and generating a spatial spectrum by using a MUSIC algorithm to obtain an estimation result of the signal arrival direction. According to the method, the noise-containing mixed signal covariance matrix is mapped into the ideal incoherent noise-free signal covariance matrix through a physical constraint supervised learning framework, so that the estimation precision and robustness of the MUSIC algorithm in a coherent scene are improved.

The invention discloses a sound acquisition and processing system based on cooperation of multiple microphone arrays. The system comprises a sound acquisition module, a multi-channel signal preprocessing module, a sound signal feature extraction module, an abnormal sound recognition module, a sound source positioning module and an alarm module. A multi-channel mixed data signal is collected through a circularly-arranged multi-microphone array formed by a plurality of microphones, after echo cancellation, wave beam domain noise reduction and multi-sound-source separation, a single-sound-source feature vector is extracted, according to the single-sound-source feature vector, abnormal sound including explosion, screaming or glass breakage is recognized through a BiLSTM and an attention mechanism model, and the abnormal sound is recognized through an attention mechanism model. And the GCC-PHAT and MDS-MUSIC algorithms are combined to position abnormal sound production, and alarm information is generated. According to the invention, accurate identification, positioning and alarm of the abnormal sound can be realized, and the real-time performance, the accuracy and the multi-target processing capability of abnormal sound monitoring in a complex environment can be obviously improved.

The invention relates to the technical field of pipeline detection, and provides a non-contact pipeline fluid flow velocity measurement method based on a frequency wavenumber domain spatial spectrogram, and the method comprises the steps: collecting a turbulence signal in a pipeline through a piezoelectric film sensor; carrying out snapshot number segmentation on the turbulence signal to obtain a plurality of segmented turbulence time domain signals; fourier transform and narrowband signal processing are carried out on the segmented turbulence time domain signals, and a spatial spectrum corresponding to each narrowband signal component is obtained; constructing a three-dimensional frequency-wave number domain spectrogram according to the spatial spectrum function; and according to the three-dimensional frequency-wavenumber domain spectrogram, calculating the flow velocity of the pipeline fluid. According to the method, a three-dimensional spectrogram characteristic space is constructed through conjoint analysis of the frequency and the wave number, the angle, distance and frequency characteristics of the turbulence signals are decoupled through spatial spectrum estimation methods such as the MUSIC algorithm, multipath interference and noise are effectively restrained, the flow speed of fluid in a pipeline can be accurately estimated, and limitation in a traditional method is overcome.

The invention belongs to the technical field of array signal processing, and particularly relates to a co-prime array design method based on virtual array hole filling, which comprises the following steps of: S1, forwards moving two sub-arrays of an extended co-prime array by a distance of Nd / 2; s2, turning over one sub-array of the shifted co-prime array to obtain an improved co-prime array; s3, generating a differential virtual array according to the improved co-prime array; s4, introducing and combining the array to carry out hole filling on the differential virtual array; s5, calculating a received signal model and a covariance matrix of the filled virtual array; and S6, DOA estimation is carried out by using an ROOT-MUSIC algorithm. The method has the advantages that better signal source resolution and lower array element mutual coupling are achieved, meanwhile, the continuous freedom degree is improved, more signal sources can be estimated at the same time, and high practical value is achieved.

The invention discloses a FDA-MIMO radar multi-target distance angle joint super-resolution method and system, and mainly solves the problem that the existing phased array only depends on the angle to identify multiple targets, resulting in low resolution ability, and the implementation scheme of the method comprises the steps of obtaining FDA-MIMO radar echo data, and performing separation aliasing on the FDA-MIMO radar echo data to obtain a data matrix; performing conversion stacking on the data matrix to obtain NM * L-dimensional data, and calculating a covariance matrix of the NM * L-dimensional data; performing reverse array decoherence processing on the covariance matrix to obtain a new source signal covariance matrix; constructing a two-dimensional spatial spectrum function of a target distance and a target angle for the new source signal covariance matrix through a MUSIC algorithm; and performing spectrum peak search on the two-dimensional spatial spectrum function, and detecting a local maximum value of the two-dimensional spatial spectrum function to obtain a distance and angle joint estimation value of a plurality of targets. The method can improve the angle resolution capability of the target when the target angle interval is lower than the traditional resolution, reduces the influence of the amplitude-phase error on the resolution capability when the target distance interval is large enough, and can be used for target recognition.

The invention provides an arrival wave angle estimation method based on a zero scanning leaky-wave antenna. A rectangular waveguide is selected as a basic structure to design a periodic leaky-wave antenna only working in a-1 harmonic state; designing necessary antenna simulation parameters; a first leaky-wave antenna is designed; adjusting the gap interval p, and designing a second leaky-wave antenna; obtaining pattern functions of the first leaky-wave antenna and the second leaky-wave antenna; proper amplitude and phase parameters are selected for directional diagram synthesis, and a new directional diagram function is obtained; constructing an array guiding matrix suitable for the MUSIC algorithm; signal sources are arranged at different positions, simulation testing is carried out through MATLAB, and the incoming wave angle estimation capability of the zero-point scanning leaky-wave antenna is verified. According to the invention, a feasible technical path is provided for high-precision positioning and tracking application in future 6G mobile communication. The antenna is especially suitable for application in millimeter wave and terahertz frequency bands, such as vehicle-mounted communication, unmanned aerial vehicle platforms, military electronic countermeasures and the like.

The invention discloses a cable partial discharge source positioning method and system based on an improved MUSIC algorithm, and relates to the technical field of power system insulation detection and fault diagnosis. According to the method, the time-frequency domain feature enhancement processing is introduced before the MUSIC algorithm, so that the method can adapt to the non-stationary characteristic of the partial discharge signal, and the spectral peak resolution under the condition of low signal-to-noise ratio is remarkably improved. Compared with the prior art, the method has the advantages of being high in anti-noise performance, high in positioning precision and simple in implementation mode, is suitable for power cable partial discharge online monitoring and fault diagnosis, and can be popularized and applied to insulation defect positioning of high-voltage equipment such as a transformer and a switch cabinet.

The invention provides a 2D-MUSIC beam line damage positioning method and system, and relates to the technical field of material safety monitoring. By collecting reference guided wave signals at different temperatures, amplitude-phase changes of direct waves of all sensor channels are analyzed, and a temperature-induced amplitude-phase error matrix is constructed; the error matrix is introduced into a two-dimensional multiple signal classification (2D-MUSIC) algorithm, an ideal steering vector is corrected, and a spatial spectrum under an actual propagation model is reconstructed; a cost function is established in combination with noise subspace characteristics, and high-precision and high-robustness positioning of tiny damage is realized through iterative optimization and synchronous inversion of damage positions and channel error parameters. According to the method, the applicability and the positioning accuracy of the 2D-MUSIC algorithm in a variable-temperature environment are remarkably improved.

The invention provides a high-voltage electricity approaching safety early warning method, system and device for an automobile crane, and belongs to the technical field of engineering machinery safety protection. Comprising the steps of collecting an electric field signal radiated by a high-voltage line, reversely deducing a distance based on an electric field intensity attenuation model, and calculating an azimuth angle of a charged body through a MUSIC algorithm; controlling a laser radar to perform high-density scanning within a set angle according to the azimuth angle to obtain three-dimensional point cloud data of the high-voltage line; time synchronization and coordinate registration are carried out on the electromagnetic sensing array and laser radar data, a three-dimensional space model of the high-voltage line is established after fusion, and the shortest distance between the three-dimensional space model and a suspension arm is calculated; identifying a voltage level, calculating a basic safety distance, correcting by combining an environment factor, and multiplying by a safety coefficient to obtain a dynamic safety threshold value; and according to the real-time distance between the suspension arm and the electrified body, triggering graded early warning and control actions. According to the invention, the problem of measurement deviation of a single sensor under complex electromagnetic environment, changeable illumination and meteorological working conditions is solved.

The invention relates to a direction-of-arrival estimation method based on a linear-nonlinear branch fusion neural network, and the method comprises the steps: obtaining an original signal of an antenna array, calculating a reference empirical covariance matrix based on the original signal, and obtaining an input tensor based on the reference empirical covariance matrix; based on the input tensor, processing by using a dual-path neural network to obtain a residual matrix; the dual-path neural network comprises a linear branch and a nonlinear branch; obtaining an enhanced covariance matrix based on the residual matrix and the reference empirical covariance matrix; and based on the enhanced covariance matrix, obtaining a DOA estimation value by using a Root-MUSIC algorithm. Compared with the prior art, the direction-of-arrival estimation method provided by the invention has the advantages of a traditional subspace algorithm and a neural network participation type method.

The invention relates to a three-dimensional MUSIC sound source localization method based on an improved particle swarm optimization algorithm, and belongs to the technical field of sound source localization, and the method comprises the following steps: S1, building a covariance matrix for sound signal data collected by an array of M array elements, and separating a noise subspace; s2, performing array manifold construction of a three-dimensional space by adopting a large-step azimuth angle, a large-step pitch angle and a large-step distance; s3, performing preliminary positioning on the sound source according to a MUSIC algorithm principle; and S4, initializing parameters of the particle swarm optimization algorithm for alternate search, and searching a three-dimensional space.

This invention discloses a DOA estimation method based on the anti-diagonal line of the second-order statistical matrix of a non-circular near-field quasi-stationary signal, belonging to the field of array signal processing. Addressing the difficulty in discerning DOA estimation for non-circular near-field quasi-stationary signals when the source angle difference is small, this invention reconstructs a virtual equivalent signal by using the anti-diagonal line of the pseudo-covariance matrix and the parallel lines of the anti-diagonal line of the covariance matrix, thus achieving DOA estimation for non-circular near-field signals. The method implementation steps include: calculating the covariance matrix and pseudo-covariance matrix of the signal at each time frame of the quasi-stationary signal; extracting the parallel lines of the anti-diagonal line of the covariance matrix and the elements of the anti-diagonal line of the pseudo-covariance matrix, reconstructing them into an equivalent signal; and using the classical MUSIC algorithm to estimate the parameters of the equivalent signal. This scheme avoids the spectral peak overlap problem that occurs when the source angle difference is small, improving the accuracy of DOA estimation.

The application discloses a two-dimensional Root-MUSIC angle automatic pairing method and system based on signal receiving timing, and specific steps of the method are as follows: step 1, a Root-MUSIC algorithm mathematical model suitable for angle estimation of two orthogonal arrays of an L-shaped array is constructed, the Root-MUSIC algorithm is applied to the two orthogonal arrays respectively, and a set of azimuth angles and a set of elevation angles are estimated; step 2, timing detection and dynamic grouping are carried out based on signal arrival timing, and simultaneous multi-signal receiving processing is converted into a single-signal processing flow organized according to timing; the Root-MUSIC algorithm is executed on each group of signals, and pairing of the azimuth angles and the elevation angles is automatically completed; and step 3, the pairing result of step 2 is stored, and whether the pairing process is ended is judged, if yes, the angle pair is output in sequence. The application constructs a joint processing mechanism of timing detection-dynamic grouping-serial processing, converts traditional multi-dimensional matching calculation into a simple timing alignment operation, and makes angle pairing become a natural derivative result of the signal processing flow.

This invention provides an adaptive method and system for fast spatial spectrum estimation of multipath channels. The method includes: S1, using a linear uniform array as the receiving array, with the first element in the array as the reference element, deriving the broadband signal model and steering vector matrix received by the array; S2, constructing a fitness function, and using the dung beetle algorithm to search for the optimal fractional Fourier transform order of the received signal from the reference element; S3, performing the optimal fractional Fourier transform on the received signal of the array; S4, finding the coordinates (u) corresponding to the maximum value. p ,v p S5. Energy detection: Set a threshold for comparison. If the threshold is met, it indicates that the location of this point is a component of the multipath; otherwise, the algorithm ends. S6. Use the CLEAN algorithm to separate the multipath components. The center frequency of its narrowband filter is u. p S7. Use the MUSIC algorithm to estimate the incident angle of the multipath components; S8. Mask the strongest component among the current multipath components and return to repeat steps S4 to S7 until all components are estimated.

The application provides a kind of intelligent metasurface assisted near-field time division integrated sensing method and system, it is related to wireless communication field.The application designs integrated sensing system by introducing RIS and single antenna receiver, avoids complex full-duplex base station and multi-antenna receiver, significantly reduces hardware complexity and implementation cost under the premise of ensuring high-quality communication and sensing performance;The adjustable frame structure designed separates the communication subframe and the sensing subframe completely, decouples the communication beam optimization and the sensing signal design, respectively realizes the communication and sensing functions in a purer signal environment;In the communication subframe, the communication and rate maximization are realized, and in the sensing subframe, the sensing capability is enhanced through the transmission beam pattern matching, which significantly improves the overall communication rate and sensing accuracy of the system;Finally, a virtual multi-dimensional receiving signal of multiple passive targets in the near field of RIS is constructed through repetition coding design, and then the 2D-MUSIC algorithm is used to estimate the target angle and distance parameters.

The application discloses a non-uniform noise background-based sparse array gridless parameter estimation method, and the implementation steps are as follows: a sparse array structure is arranged at a receiving end; a sparse array receiving signal in a non-uniform noise background is modeled; a covariance matrix of the array receiving signal is calculated; receiving data of a virtual differential common array is calculated through vectorization and de-redundancy; a distribution to which a fitting error is subjected is derived, and a parameter estimation optimization model based on atomic norm minimization and avoiding a complex regularization parameter determination process is constructed; a semi-positive definite programming form of a primal problem and a dual problem is derived; and a wave direction estimation result is obtained through a MUSIC algorithm or polynomial root seeking. In addition, on the basis of fully utilizing a virtual differential common array of the sparse array to provide extended degrees of freedom and all information, the application restrains the influence of non-uniform noise by constraining the sparsity of data atoms to be recovered and selecting a regularization parameter from a chi-square distribution table according to a distribution to which a fitting error between the data to be recovered and actual receiving data not affected by noise is subjected, overcomes the grid mismatch problem caused by parameter domain discretization, avoids a complex process of determining the regularization parameter, and can obtain a higher-precision source direction estimation result.

The invention discloses a hydrophone array multi-sound-source positioning method based on a frost ice optimization algorithm, and belongs to the field of sound source positioning. According to the method, a linear hydrophone array is constructed, an underwater sound source positioning scene is set, and a sound source signal is collected and processed to obtain a receiving signal; a MUSIC algorithm is used to process the received signal, a spatial spectrum is generated to preliminarily estimate information such as an azimuth angle and a pitch angle of a sound source, normalization processing is carried out on the spatial spectrum, a gravitational force area and a repulsive force area are divided, and a gravitational force-repulsive force type artificial potential energy field is constructed; an independent sub-population is initialized for each sound source by adopting a frost ice RIME optimization algorithm, individual positions are updated in combination with an artificial potential energy field and a frost puncture mechanism in an iterative updating process, and particles with the highest fitness are selected as final estimation positions through iterative search. The method overcomes the limitation of a traditional optimization algorithm, remarkably improves the precision and reliability of sound source positioning, and is particularly suitable for a multi-sound-source positioning scene in a complex underwater sound environment.

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 provides a FDA-MIMO radar gridless target parameter estimation method based on a single base plane array, relates to the technical field of array signal processing, constructs a single base plane array FDA-MIMO radar system, and the transmitting end and the receiving end of the radar system are composed of a uniform plane array; a receiving signal model is established based on the radar system, the model is vectorized, a selection matrix is introduced to construct an angle-distance decoupling receiving signal model; the covariance matrix of the receiving signal model is calculated; a low-rank matrix reconstruction optimization problem suitable for the model is established according to the covariance matching criterion; the optimization problem is solved by the idea of alternating projection by using the properties of the covariance matrix; the information of the angle theta and the distance r is estimated by the multiple signal classification method according to the covariance matrix; the problems that the FDA-MIMO radar angle-distance decoupling model in the prior art is only suitable for a linear array, and the target parameter estimation method has low estimation accuracy and high calculation complexity can be solved.

The application discloses a DOA estimation method and system based on a generative adversarial network. The method first acquires time-domain coherent signals received by a uniform linear array, performs preprocessing, and generates a coherent signal covariance matrix and a corresponding incoherent covariance matrix. Secondly, a covariance matrix reconstruction model is constructed, based on the coherent signal covariance matrix and the corresponding incoherent covariance matrix, a generator of the generative adversarial network is used to extract deep features from the preprocessed coherent signal covariance matrix, and the coherent signal covariance matrix is reconstructed. Then, the MUSIC algorithm is used to estimate and verify the DOA based on the reconstructed covariance matrix. The application improves the precision of coherent DOA estimation while not losing the utilization rate of the array aperture. The application has less parameter quantity, lower calculation complexity, faster covariance matrix reconstruction speed and stronger covariance matrix reconstruction capacity.

The invention relates to a phase shift keying signal positioning method based on co-prime sum-difference common-array compensation. Direction of arrival estimation wide in estimation range and high in estimation precision is achieved. After a non-circular signal is received through an array antenna of an augmented co-prime array structure, the non-circular signal is subjected to digital processing to obtain a digital signal, and an augmented co-prime array comprises a first sub-array and a second sub-array; carrying out covariance matrix calculation on the digital signal and vectorizing a covariance matrix to obtain a difference comatrix and a sum comatrix; determining redundant array elements according to the structure that the array elements in the augmented co-prime array are removed without influencing the difference coordination array, and repositioning the redundant array elements to obtain a third sub-array and a fourth sub-array; translating all the sub-arrays by an optimal shift distance to obtain a converted augmented co-prime array structure; and estimating the direction of arrival by adopting the MUSIC algorithm again according to the conversion augmented co-prime array to obtain the direction of arrival.

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 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.

A system and method for determining the distance between two wireless network devices is disclosed. The present system utilizes an algorithm that leverages additional information contained in the pseudo-spectrum generated the MUSIC algorithm. Specifically, since the MUSIC algorithm operates using the square of the channel frequency response, additional peaks are created in the pseudo-spectrum, which can be used to verify the correctness of the distance measurement. The algorithm verifies that the first peak is correct by identifying a second peak and looking for an additional peak located within a search region that is determined based on the first two peaks.

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 long-distance wireless sensing method for the unstructured environment of coal mines. The method comprises the following steps: an intelligent detection robot is equipped with a directional transmitting antenna and a pair of receiving antennas arranged side by side on the left and right sides; directional transmitting antennas facing the same direction are installed at set intervals along the length direction of an underground coal mine tunnel; and a reflector is installed at the optimal reflection installation position on the tunnel wall of the underground coal mine tunnel. The method uses the transmitting antenna and receiving antenna working periodically for detection. After a disaster occurs, the method can determine the specific location of the trapped person based on the amplitude change direction of the gesture signal of the trapped person and the position of the signal source. The method combines the smoothed MUSIC algorithm and the ISAR algorithm to accurately separate and analyze the reflected signal, thereby determining the number of people in the environment and their relative positions. The method can ensure effective signal transmission and detection in a complex underground coal mine tunnel environment. The method is particularly suitable for rescue detection of trapped people in a post-disaster underground coal mine environment.

The application relates to a MUSIC direction-finding method based on an underwater information system cross array, and belongs to the technical field of underwater acoustic direction finding. In view of the problems of low signal-to-noise ratio and low direction-finding precision of underwater signal direction finding, the application provides a MUSIC direction-finding method based on an underwater information system cross array. The method is based on a MUSIC algorithm, frequency extraction and spatial spectrum accumulation, a cross array is used to perform direction-finding processing on a signal, the relative position relationship between the signal and the cross array is obtained, a suitable linear array in the cross array is selected to perform direction-finding processing on the signal, and the direction finding of an underwater target acoustic signal under low signal-to-noise ratio can be effectively realized.

The present invention provides a distributed array direction-of-arrival (DOA) estimation method for arbitrary subarray configurations, comprising the steps of constructing a distributed array with arbitrary subarray configurations, digitally channelizing incoming signal data received by the distributed array, separating the incoming signal data, estimating the phase difference of each received signal due to the inter-subarray baseline length and the covariance matrix of the received signal data, calculating all ambiguous phase differences for each signal based on the inter-subarray baseline lengths and obtaining corresponding DOA estimates, and substituting all ambiguous DOA estimates for each signal into a multiple signal classification spatial spectrum deambiguation method to obtain high-precision, unambiguous DOA estimates for all incoming signals. This method allows for arbitrary arrangement of array elements within the subarray, addressing the limitations of baseline arrangement imposed by deambiguation methods such as long-short baselines and staggered baselines. The method offers flexible array configuration and ease of engineering implementation, making it suitable for small platforms such as micro- and nano-satellites and drones, and possessing broad market application prospects.

The present invention belongs to the technical field related to remote sensing technology and discloses a method and system for analyzing antenna array position errors based on attitude adjustment. The method comprises: obtaining signals received by the antenna array in a first attitude and a second attitude from the same unknown signal source; performing the following data processing on the received signals in each attitude: constructing a multiple signal classification function after position correction of the array elements, using the terms in the function containing the error correction parameter and the incident angle as the decision quantity, solving the maximum point of the multiple signal classification function to obtain the value of the decision quantity; and constructing a system of equations based on the values ​​of the decision quantity in the two attitudes, using the error correction parameter and the incident angle as unknown quantities, and solving the equations to implement error analysis. The present invention can accurately estimate the array position error without introducing an auxiliary radiation source.