49results about "Diversity direction finding" patented technology

The invention belongs to the acoustic vector communication field, and particularly relates to a vector circular matrix steady broadband MVDR estimation method. The method comprises steps of performing sub-band decomposition on acoustic pressure data and vibration velocity data received by the two-dimension circular array and generating a broadband frequency domain signal matrixes of the acoustic pressure and vibration velocity to obtain a broadband frequency domain snapshot data matrix of the vector matrix, generating vector cross-spectral matrix on all sub-bands, setting pace lengths, performing azimuth scanning, constructing a vector array guide vector on the sub-band, selecting a focusing reference frequency point and constructing the vector array focusing guide vectors on the same azimuth, adopting a coherence signal subspace CSS focusing transformation method to obtain a vector array focusing transformation matrix, obtaining a broadband focusing covariance matrix, obtaining an optimum vector and array average output power after optimization, and determining sound wave source according to the spectrum peak position of the spatial spectrum. The Acoustic vector circular matrix steady broadband MVDR orientation estimation method applies stable constrained optimization and improves the spatial spectrum resolution.

The invention discloses an unmanned aerial vehicle direction estimation method based on voiceprint multiharmonic identification. For a traditional incoherent subspace direction-of-arrival estimation algorithm of a high resolution spectrum, a wide-band signal is divided into several narrow-band signals, angle estimation is performed on a narrow band through a multiple signal classification (MUSIC) algorithm, and an arithmetic mean is obtained. The traditional method ignores uneven energy of sub-bands and different signal-to-noise ratios, and then the algorithm performance is poor. According to the method, characteristic frequency is obtained by performing time-frequency analysis on an acoustical signal of a target information source. For the wide-band signal, only the sub-band where the characteristic frequency is located is extracted, narrow-band MUSIC operation is performed, the energy ratios and the signal-to-noise ratios of all characteristic sub-bands are combined, different weighting coefficients are given to all characteristic sub-band direction angles, the angle estimation result is obtained through weighted mean, and then more accurate angle estimation performance is achieved.

The present invention provides an acoustic vector circular array mode-domain robust direction estimation method. The method includes the following steps that: the received signals P(t), Vx (t) and Vy (t) of an acoustic vector circular array acoustic pressure channel, an acoustic vector circular array vibration velocity x channel and an acoustic vector circular array vibration velocity y channel are obtained; the received signals Pe (t), Vex (t) and Vey(t) of a phase mode-domain acoustic pressure channel, a phase mode-domain vibration velocity x channel and a phase mode-domain vibration velocity y channel are obtained; Vex (t) and Vey(t) are rotated electronically, so that a combined vibration velocity Vec (t) can be obtained, a covariance matrix Repv is obtained based on Pe (t) and Vec (t), an unitary matrix Q is introduced to transform the matrix Repv, so that a real-value covariance matrix Rpv of mode-domain acoustic pressure and vibration velocity combined processing can be obtained; a steering vector a<~>r(Phi<~>) which has been subjected to mode-domain transformation and real-value processing is constrained, second-order cone programming is adopted to carry out solving, so that an optimal weight vector Omegarob can be obtained; and an output space spectrogram can be obtained based on the steering vector Omegarob which has been subjected to mode-domain transformation and unitary matrix real-value transformation, and a target direction can be obtained based on a spectrum peak position. With the method of the invention adopted, the problems of performance degradation and high signal-to-noise ratio processing threshold of a minimum variance distortionless response algorithm under a condition that related sound sources are difficult to distinguish and mismatching occurs can be solved. The method has the advantages of high resolution, high robustness, small amount of calculation, strong background noise suppression ability and the like.

The invention discloses a two-stage MUSIC microphone array direction finding method. The method includes the steps that a microphone array which is composed of N array elements receives spatial far field sound source signals, and sampled data of the microphone array are acquired; the sampled data are segmented to acquire segmented microphone array data; frequency domain segmented array data are acquired; available frequency units are selected, so that an available frequency set is obtained; the reference frequency is determined when the angle of arrival is estimated; the two-stage MUSIC algorithm is used for calculating the angle of incidence of the sound source signals. According to the method, the advantages of the frequency units at different frequency bands in the angle estimating process are combined, the frequency unit which is closest to the reference frequency is selected to be subjected to two-stage MUSIC spectrum estimation at most, the frequency units at the high frequency stage are used for guaranteeing the angle estimating precision, the frequency units at the low frequency stage are used for solving the angle estimating blur, the angle estimating result at the low frequency stage is used for solving the angle blur at the high frequency stage, and therefore a high-precision angle estimating result can be acquired.

An acoustic array near-field source ESPRIT and MUSIC parameter estimation method is provided. An array receives K uncorrelated narrowband random steady near-field sound source signals with different frequencies. Two groups of received signals ahead and after a delay tap and received by the array form full array received signals. A signal data autocorrelation matrix is subjected to characteristic decomposition to obtain the estimated values of an array steering vector matrix and the frequency. A rotation-invariant relation between four sub array steering vectors is obtained from the estimated value of the array steering vector. The rough estimated values of a signal azimuth angle, a pitch angle, and a distance are obtained according to a rotation-invariant relation matrix. A MUSIC spectrum peak search method is used to obtain the accurate estimated values of the azimuth angle, the pitch angle and the distance in a small area near the rough estimated values. The method breaks through the limitation of a conventional linear array parameter estimation method and the super large calculated amount of the full-domain 3D search of a single MUSIC method, combines the advantages of the ESPRIT method and the MUSIC method, requires no parameter matching operation, greatly reduces the calculated amount and improves parameter estimation accuracy.

The invention discloses a voice directing method and system based on intelligent equipment. The method comprises that after that the intelligent equipment is started, a voice signal is obtained in real time; when the voice signal is detected by the intelligent equipment, a present foreground image of the intelligent equipment is obtained, and a candidate direction of a sound source is obtained according to the present foreground image; and according to the candidate direction of a sound source, the intelligent equipment carries out calculation via a positioning algorithm, and then determines a sound source direction of the voice signal according to a calculation result. According to the invention, the candidate direction of the voice signal obtained in advance is calculated by combining image collection, the candidate direction is checked via the algorithm, the optimal sound source direction is obtained, the computing complexity is reduced, and the positioning efficiency of the voice signal is improved.

The invention provides an acoustic vector sensor two-dimensional array MUSIC decoherence parameter estimation method. An array receives K far-field narrowband coherent signals, and N times of snapshot data outputted by all the array elements are acquired by using the receiving array; four subarray data of acoustic pressure and x-axis, y-axis and z-axis acoustic velocity are extracted, and a data covariance matrix after decoherence is constructed by a data covariance matrix before transformation, a covariance matrix after data transformation and a cross-covariance matrix before and after transformation; singular value decomposition is performed on the data covariance matrix after decoherence so as to obtain a noise subspace, the noise subspace is divided into x-axis and y-axis noise subspaces according to the characteristics of an L-shaped array and the corresponding MUSIC space spectrum is constructed, and direction cosine estimation matrixes are obtained by two one-dimensional searches; and matching operation is performed on the direction cosine estimation values of the x-axis and y-axis directions by using the noise subspaces corresponding to the full array so as to achieve the estimation value of the angle of arrival. According to the method, one two-dimensional search is divided into two one-dimensional searches so that the computational burden can be greatly reduced and the parameter estimation accuracy can be enhanced.

The invention provides an acoustic vector sensor array space rotation solution coherence arrival angle estimation method. An array receives K coherence narrowbands and a stationary far-field signal. The single-shot snapshot output data of all elements are acquired through a receiving array. N-times snapshot data of the array are measured. The orthogonal vector characteristic of an acoustic vector sensor is fully used. The acoustic vector sensor array is divided into four sub-arrays of an acoustic pressure sub-array, an x-axis vibration velocity sub-array, a y-axis vibration velocity sub-array and a z-axis vibration velocity sub-array. The signal covariance matrix rank is acquired through sub-array processing, so as to acquire a data covariance matrix after solution coherence. A noise space is acquired through the data covariance matrix after solution coherence. A noise subspace is used to construct a MUSIC spatial spectrum. The estimated value of an arrival angle is acquired by searching the one-dimensional MUSIC peak of an angular domain. Compared with a spatial smooth de-coherence method, the method provided by the invention is applicable to a uniform linear array and a non-uniform linear array, is free of aperture loss, and has the advantages of higher spatial resolution, orientation accuracy and wide application range.

The invention provides a stochastic resonance enhanced acoustic vector signal orientation method. The method can realize amplitude linear gain and is suitable for vector acoustic signal noise reduction processing in orientation, can solve the problem of large vector acoustic orientation error under the condition of low signal-to-noise ratio, and has good orientation effect. The stochastic resonance enhanced acoustic vector signal orientation method is mainly applied to the orientation of an underwater weak target in a low signal-to-noise ratio environment, has good resistance to phase inconsistency of actual vector acoustic signals, and is a stable single-vector hydrophone orientation method.

A method for providing sound detection information producing a result of sound detection based on sound data generated by detecting sound generated around a host vehicle, may include determining an opposite lane vehicle detection index based on the result of sound detection, the opposite lane vehicle detection index forming a basis of determination of presence or absence of an opposite lane vehicle, and controlling a notification of a neighboring vehicle travelling around the host vehicle or controlling the host vehicle according to the opposite lane vehicle detection index, wherein the result of sound detection is information about the probability of presence of the neighboring vehicle for respective angles in frames consecutive over time.

A speech interaction device includes an ascertaining section and a control section. The ascertaining section ascertains a direction of a speech utterer by audio emitted by the speech utterer. The control section controls directionality of audio output through a speaker when outputting audio toward the speech utterer, such that directionality of audio in the direction ascertained by the ascertaining section is higher than directionality of audio in other directions.

A sound source localization apparatus is provided which can more surely detect a sound source located in a detection target region. The sound source localization apparatus includes a plurality of microphone and a buffle. The buffle has a first surface and a second surface. The second surface is a surface opposite to the first surface. The plurality of microphones are two-dimensionally arrayed and fixed in the first surface. The buffle allows the plurality of microphones to pick up direct sound arriving at the first surface and prevents the plurality of microphones from picking up direct sound arriving at the second surface.

Iterative methods for direction of arrival estimation of a signal at a receiver with a plurality of spatially separated sensor elements are described. A quantized estimate of the angle of arrival is obtained from a compressive sensing solution of a set of equations. The estimate is refined in a subsequent iteration by a computed error based a quantized estimate of the direction of arrival in relation to quantization points offset from the quantization points for the first quantized estimate of the angle of arrival. The iterations converge on an estimated direction of arrival.

The invention discloses an electrical equipment partial discharge source direction finding apparatus. The apparatus comprises a square sensor array and an optical measurement system. Each array element of the sensor array comprises a spherical housing, a square weight placed at the center of the spherical housing and six elastic cylinders wound with fibers, wherein the six elastic cylinders are averaged into three groups, the two elastic cylinders of each group are coaxial, axes of the three groups of the elastic cylinders are mutually vertical and pass through center of the spherical housing, the axes of two groups of the elastic cylinders are respectively parallel to two vertical edges of the sensor array, one end of each elastic cylinder is bonded to one surface of the square weight, the other end of each elastic cylinder abuts against the inner wall of the spherical housing, one end of the fiber on each elastic cylinder is provided with a Faraday rotating mirror, and the other end is connected with the optical measurement system. According to the invention, direction finding is performed on partial discharge by use of fiber co-vibrating type vector array sensors, and the apparatus has the advantages of good frequency response, high anti-electromagnetic interference capability, high measurement precision, small volume, high adaptability, small influences on equipment and the like.

The invention relates to a hydrophone direction finding method, a hydrophone direction finding device, a computer readable storage medium and computer equipment. The hydrophone direction finding method comprises the steps of: firstly, acquiring various paths of hydroacoustic signals output by a directional hydrophone array; subjecting the various paths of hydroacoustic signals to discrete Fourieroperation separately, so as to obtain each path of hydroacoustic energy spectrum corresponding to each path of hydroacoustic signal; and acquiring an azimuth value of direction finding at present according to various paths of the hydroacoustic energy spectra, wherein directivity of the directional hydrophone array covers a 360-degree hydroacoustic singal measurement range. The hydrophone directionfinding method and the hydrophone direction finding device can acquire various paths of hydroacoustic signals covering the 360-degree measurement range by means of the hydrophone array, so that the acquired hydroacoustic singal measurement range is complete without omission, the azimuth value of direction finding at present is obtained by adopting a method of acquiring the energy spectra, the anti-reverberation capability is high, and the hydrophone direction finding method and the hydrophone direction finding device are suitable for the complex underwater environments with reverberation andmultipath.

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 belongs to the technical field of crossing of information and ocean science and technology, and discloses a UUV broadside parallel array covariance weighted fusion DOA estimation method. The method comprises the following steps: firstly, calculating auto-covariance and cross-covariance matrixes of two sub-arrays, carrying out weighted fusion on covariance matrixes of different sources through differential common-array expansion of a virtual aperture, then reconstructing a complete covariance matrix by respectively adopting a convex optimization method of trace regularization and nuclear norm regularization according to the characteristics of the fused matrix, and finally, carrying out weighted fusion on the covariance matrixes of different sources. The pitch angle and the azimuth angle of the target are jointly estimated by performing subspace decomposition on the constructed extension matrix, and the effectiveness of the method is verified by a simulation result. According to the method, the precision of parameter estimation is improved through data fusion, the degree of freedom is remarkably improved under a small number of physical array elements, high-precision azimuth estimation of the UUV on multiple targets in the underwater environment is achieved, the target detection capacity of the UUV is enhanced, and the method has high engineering application value.

The invention relates to the technical field of array signal processing, and discloses a method for estimating the direction of arrival of an acoustic vector sensor array under non-uniform noise, and the method comprises the following steps: 1, receiving an output vector X output by the acoustic vector sensor array; step 2, based on a sparse signal model, calculating a signal covariance matrix P and a noise covariance matrix Q according to the output vector X, and constructing a sparse covariance matrix R by using the obtained signal covariance matrix P and noise covariance matrix Q; 3, constructing a cost function based on the sparse covariance matrix R, estimating sparse signal power by using the cost function, and obtaining a signal power vector; and 4, carrying out spectrum peak search on the signal power vector, wherein the sound source position corresponding to the obtained spectrum peak is the estimated target azimuth angle. According to the method, the orientation estimation performance of the acoustic vector sensor array under the non-uniform noise can be improved.

A system includes at least one processor and at least one memory storing program instructions that, when executed by the at least one processor, cause the system to send an acoustic ranging transmitter signal between a plurality of calibration reference positions and at least one anchor point, receive an acoustic ranging receiver signal associated with the acoustic ranging transmitter signal and with distances between the plurality of calibration reference positions and the at least one anchor point, and estimate a speed of sound based on the acoustic ranging receiver signal.

A speech interaction device includes an ascertaining section and a control section. The ascertaining section ascertains a direction of a speech utterer by audio emitted by the speech utterer. The control section controls directionality of audio output through a speaker when outputting audio toward the speech utterer, such that directionality of audio in the direction ascertained by the ascertaining section is higher than directionality of audio in other directions.

A method for providing sound tracking information includes detecting a sound occurred adjacent to a subject vehicle to generate a sound tracking result based at least on a sound data regarding detected sound; determining an angle of point having the maximum probability among at least one of peak points in the sound tracking result as a first vehicle angle; determining whether an angle of candidate point is a second vehicle angle, wherein the candidate point has the maximum probability among peak points included in a detection range except for the first vehicle angle; and generating at least one detection signal corresponding to the first and the second vehicle angles, when the angle of candidate point is the second vehicle angle, wherein the sound tracking result includes a probability of whether there is at least one another vehicle at each of angles in each of frames continued according to time.

The invention discloses a band channel calibration particle swarm optimization broadband beam forming method and device. The method comprises the following steps: calculating a compensation coefficient of an adaptive calibration compensation filter corresponding to each microphone array element channel; determining a frequency band range in which a user is interested and a main lobe and a side lobe of an array beam in the frequency band range; calculating an input spectrum power autocorrelation matrix in the frequency band range in which the user is interested, and constructing a problem of solving an optimal FIR filter weight coefficient under a linear constraint minimum variance criterion; converting the problem into an unconstrained optimization problem, and solving by using a particle swarm optimization algorithm to obtain the optimal FIR filter weight coefficient; summing the digital signal after filtering compensation by using the optimal FIR filter weight coefficient, and outputting a time domain signal after beam forming; and if a target sound source incoming wave direction or side lobe constraint, interference and noise suppression requirements to which the wave beam points are changed, recalculating the FIR filter weight coefficient.

The invention discloses an unmanned aerial vehicle direction estimation method based on voiceprint multiharmonic identification. For a traditional incoherent subspace direction-of-arrival estimation algorithm of a high resolution spectrum, a wide-band signal is divided into several narrow-band signals, angle estimation is performed on a narrow band through a multiple signal classification (MUSIC) algorithm, and an arithmetic mean is obtained. The traditional method ignores uneven energy of sub-bands and different signal-to-noise ratios, and then the algorithm performance is poor. According to the method, characteristic frequency is obtained by performing time-frequency analysis on an acoustical signal of a target information source. For the wide-band signal, only the sub-band where the characteristic frequency is located is extracted, narrow-band MUSIC operation is performed, the energy ratios and the signal-to-noise ratios of all characteristic sub-bands are combined, different weighting coefficients are given to all characteristic sub-band direction angles, the angle estimation result is obtained through weighted mean, and then more accurate angle estimation performance is achieved.

The application discloses a typhoon direction estimation method and system based on a single vector hydrophone and a terminal, and relates to the field of typhoon direction estimation.The method comprises the following steps: strictly checking sound pressure and three-directional vibration velocity data collected by the single vector hydrophone to ensure data quality; then, pre-processing the data, including filtering to remove noise interference; then, normalizing the filtered data; then, calculating sound intensity in each direction within a certain azimuth and pitch search range, constructing a sound intensity matrix, and finding the azimuth and pitch corresponding to the maximum sound intensity as the real reference value; dividing the processed data into a training set and a test set according to a certain proportion; constructing a multilayer perception machine model; and through experiments of different learning rates and small batch sizes, optimizing the model, selecting the parameters with the minimum loss to train the best model; finally, using the trained model to predict the test set to obtain the estimated value of the typhoon azimuth and pitch angle.The application effectively improves the accuracy of typhoon direction estimation.

The application discloses a method for quickly estimating the array shape and direction of a towed line array, and aims at solving the problem of the decline of direction finding performance caused by the maneuvering of the towed line array and reducing the calculation amount of sparse Bayesian learning. The method comprises the following steps: dividing the spatial angle into N grid points averagely, and constructing a sparse signal model in space; modeling the towed line array to obtain an array manifold matrix containing an arch height variable; using the Gaussian generalized approximation message passing and the sparse Bayesian learning algorithm to reconstruct the sparse signal in space and estimate the arch height; and outputting a spatial spectrum diagram to estimate the direction of arrival. The method can estimate the direction of arrival while estimating the arch height under the distortion condition of the maneuvering towed line array, adjust the array manifold matrix, and solve the problems of the decline of direction finding precision caused by the array shape distortion and the loss of weak targets caused by the sidelobe lifting.

The invention discloses a sparse Bayesian out-of-grid orientation estimation method under non-Gaussian noise, which comprises the following steps of: constructing a hierarchical noise prior model based on Student-t distribution, a double-layer sparse signal prior model based on a binary indication variable and the like, and inferring approximate posteriori distribution of iteratively updating parameters by using Bayesian variation; the noise precision weight is adaptively adjusted according to the reconstructed residual energy so as to suppress impulse noise, and random pseudo peaks are effectively removed through a binary indication variable judgment mechanism. And finally, adaptively correcting the grid offset by using the residual gradient information subjected to anti-noise weighting so as to eliminate the off-grid effect. Compared with the traditional method, the method provided by the invention not only can carry out DOA estimation under non-Gaussian noise, but also has higher DOA estimation precision. The method disclosed by the invention still has relatively high performance under the conditions of few snapshots and low signal-to-noise ratio, so that the method has relatively high application value in actual engineering.

This invention belongs to the field of information and marine technology, and discloses a method for estimating the DOA (Direction of Aperture) of a UUV (Ultra-UV) hull-side array using conjugate enhancement and virtual extension. This method performs conjugate enhancement processing on the received signal from a parallel coprime array, calculates the augmented statistical matrix including autocorrelation, conjugate autocorrelation, cross-correlation, and conjugate cross-correlation, and constructs an extended correlation matrix through weighted combination. A virtual uniform linear array is constructed using the differential co-array characteristics of the coprime array. A redundant integration matrix is ​​designed to remove redundancy from the covariance matrix, obtaining the equivalent signal of the virtual array. Then, the covariance matrix of the virtual array with a Toeplitz structure is reconstructed. Finally, a dual rotation-invariant subspace algorithm is used to achieve high-precision, automatic pairing estimation of the underwater target's azimuth and pitch angles. This invention extends the array aperture, improves the estimation robustness in low signal-to-noise ratio environments, and eliminates the need for spectral peak search, providing technical support for UUV underwater target positioning.

A sound source localization apparatus is provided which can more surely detect a sound source located in a detection target region. The sound source localization apparatus includes a plurality of microphones and a baffle. The baffle has a first surface and a second surface. The second surface is a surface opposite to the first surface. The plurality of microphones are two-dimensionally arrayed and fixed in the first surface. The baffle allows the plurality of microphones to pick up direct sound arriving at the first surface and prevents the plurality of microphones from picking up direct sound arriving at the second surface.