45 results about "Coprime array" patented technology

The invention discloses a co-prime array DOA (direction of arrival) estimation method based on interpolation virtual array covariance matrix Toeplitz reconstruction, and mainly solves a problem of information loss caused by the heterogeneity in a virtual array in the prior art. The method comprises the implementation steps: constructing a co-prime array at a receiving end; receiving an incident signal through the co-prime array, and carrying out the modeling; calculating an equivalent virtual signal corresponding to the signal received by the co-prime array; constructing an interpolation virtual array and carrying out the modeling; constructing a multi-sampling snapshot signals of the interpolation virtual array and a sampling covariance matrix; constructing a projection matrix, and defining projection calculation related with the projection matrix; constructing a reference covariance matrix according to all information in an original virtual array, designing an optimization problem based on the interpolation virtual array covariance matrix Toeplitz reconstruction, and solving the optimization problem; and carrying out the DOA estimation according to the reconstructed interpolation virtual array covariance matrix. The method improves the freedom degree and resolution of signal DOA estimation, and can be used for the passive positioning and target detection.

The invention discloses a direction of arrival estimation method based on covariance matrix reconstruction of an interpolated coprime array, which mainly solves the problem of information loss existing in the prior art based on virtual domain statistical signal processing. The implementation steps are: constructing a coprime array at the receiving end; using the coprime array to receive the incident signal and modeling; transforming the coprime array into a uniform linear array according to the idea of ​​interpolation, and constructing the corresponding received signal model; calculating the interpolation Sampling covariance matrix of coprime array; construct projection matrix corresponding to sampling covariance matrix of interpolation coprime array; design convex optimization problem based on kernel norm minimization to realize Toeplitz reconstruction of covariance matrix of interpolation coprime array ; Perform DOA estimation based on the reconstructed interpolated coprime array covariance matrix. The invention improves the degree of freedom and the accuracy of the estimation of the direction of arrival of the signal, and can be used for passive positioning and target detection.

The invention discloses a coprime array adaptive wave beam shaping method based on covariance matrix virtual domain discrete reconstruction, wherein the method mainly settles problems of limited freedom performance and output performance reduction in prior art. The method comprises the following steps of (1), constructing a coprime array at a base station end; (2), receiving a signal by means of the coprime array and modeling; (3), obtaining a virtual array equivalent receiving signal; (4), calculating a coprime array virtual domain spatial spectrum; (5), reconstructing an anticipated signal guiding vector; (6), performing discrete reconstruction of an interference and noise covariance matrix; and (7), calculating a coprime array wave beam shaping weight vector. The coprime array adaptive wave beam shaping method sufficiently utilizes an advantage that the coprime array can improve freedom, and calculates the virtual domain spatial spectrum through an equivalent virtual signal statistics amount, thereby realizing parameter estimation. Furthermore a reconstruction concept is utilized for realizing designing of a coprime array physical antenna array weight vector, thereby effectively improving freedom and output performance of an adaptive wave beam shaper. Furthermore the coprime array adaptive wave beam shaping method can be used for directional transmission and receiving of signals.

The invention belongs to the array signal processing technical field and relates to a co-prime area array-based two-dimensional direction of arrival quick estimation method. The co-prime area array-based two-dimensional direction of arrival quick estimation method includes the following steps that: of: array manifold matrixes are constructed on the basis of an x-axis and a y-axis respectively according to a co-prime area array model, two uniform sparse area arrays are combined so as to form the co-prime area array model; the covariance matrixes of the received signals of the sub-arrays are solved, the propagation operator matrixes of the arrays are constructed on the basis of the x-axis and the y-axis; a PM (Propagator Method) is adopted to solve the twiddle factor matrixes of the sub-arrays along the x-axis and y-axis on the basis of block processing performed on the array manifolds; and angle ambiguity is eliminated through using the co-prime theory of planar arrays, and the azimuthsand pitch angles of the arrays are solved. With the method of the invention adopted, low-complexity, high-precision and fuzzy-free joint estimation of the pitch angles and azimuth angles under the co-prime area array model can be realized.

The invention discloses a co-prime array direction-of-arrival estimation method based on singular value decomposition of multiple sampling virtual signals, which mainly solves a problem of difficult solving caused by information loss existing in the process of virtual domain statistical signal processing and the non-uniformity of an equivalent virtual array in the prior art. Implementation of theco-prime array direction-of-arrival estimation method comprises the steps of structuring a receiving terminal antenna according to a co-prime array structure; receiving an incident signal by using theco-prime array and modeling; constructing multiple sampling virtual signals; performing dimension reduction processing on the multiple sampling virtual signals through singular value decomposition; designing a convex optimization problem based on a joint constraint of an L1-norm and an L2-norm of the multiple sampling virtual signals, and solving the convex optimization problem; and obtaining a direction-of-arrival estimation result through spectrum peak searching. The co-prime array direction-of-arrival estimation method sufficiently utilizes all information of the received signal of the co-prime array, overcomes the problem of difficult solving caused by the non-uniformity of the equivalent virtual array, improves the degree of freedom of direction-of-arrival estimation and can be applied to passive positioning and target detection.

The invention discloses a direction of arrival estimation method based on relatively prime array second-order equivalent virtual signal disperse Fourier inversion. The objective of the invention is tosolve problems of high calculation complexity and a failure of simultaneously estimating signals and power in the current method. The method comprises following achieving steps that a receiving end builds a relatively prime array; by use of the relatively prime array, emission signals are received and modeling is performed; according to the received signals of the relatively prime array, deviating second-order equivalent virtual signals corresponding to augmentation virtual uniform linear arrays; defining angle-space frequency and using the angle-space frequency to describe second-order equivalent virtual signals of the virtual uniform arrays; carrying out disperse Fourier inversion on the second-order virtual signals described by use of the angle-space frequency, and constructing a space-power spectrum; and according to the constructed space-power spectrum, carrying out spectrum peak searching so as to acquire direction of arrival estimation and power estimation information the signals. According to the invention, the degree of freedom of estimation of the direction of arrival is improved; calculation complexity of the direction of arrival is reduced; and power estimation information of the signals can be acquired.

The invention relates to a channel estimation method and system based on a coprime array system, belongs to the field of communication technology, and solves the problems of complicated channel estimation calculation, low efficiency and low estimation precision in the prior art. The method comprises the following steps: obtaining a first signal and a second signal respectively received by the first sub-array and the second sub-array in the coprime array; obtaining the emission angle and the An angle of arrival; calculating an estimated path gain according to the emission angle and the arrival angle; calculating and obtaining a channel estimation value according to the emission angle, the arrival angle, and the estimated path gain. The method narrows down the range of spectrum search by estimating emission angle and arrival angle and path gain, greatly reduces the range of space spectrum search, reduces computational complexity, and improves the efficiency and accuracy of channel estimation.

The invention discloses a co-prime array DOA (direction of arrival) estimation method of an arrival freedom degree increase type based on compressed sensing, and mainly solves problems in the prior art that the freedom degree is limited and the calculation complexity is high. The method comprises the implementation steps: configuring a receiving end antenna according to a co-prime array structure; receiving an incident signal through a co-prime array; constructing a compressed sensing kernel; achieving the compression of the received signal through the compressed sensing, and obtaining a contour signal of the received signal of the co-prime array; calculating the covariance matrix of the contour signal after compressing; calculating an equivalent virtual signal corresponding to the contour signal; constructing a virtual domain sparse signal reconstruction optimization problem according to the equivalent virtual signal deduced from the contour signal, and solving the virtual domain sparse signal reconstruction optimization problem; and obtaining a DOA estimation result through spectrum peak searching. The method makes the most of the advantage that the co-prime array can improve the freedom degree, and the compressed sensing technology. The method achieves the increase of the freedom degree of a DOA estimation method while reducing the calculation complexity, and can be used for passive positioning and target detection.

The present invention provides a coprime array underdetermined direction finding method based on zeroization and denoising technology, which specifically includes the following steps: coprime array arrangement and receiving array data; data preprocessing; constructing a uniform virtual array data vector and model noise Covariance matrix; iterative solution to nulling coefficients; equation root finding and direction finding. The advantage of this method compared with the existing technology is: firstly, the estimation of the variance of array noise is introduced in the process of underdetermined solution, and the hole in the virtual array of coprime array is interpolated by using the technology of zeroization and denoising , making full use of all array element information and array degrees of freedom; secondly, the present invention models the model noise caused by the limited number of snapshots, which can improve the accuracy of direction finding; finally, the method proposed by the present invention belongs to the gridless Algorithm, there is no grid effect, and there is no need for spatial grid scanning.

The invention discloses a coprime array underdetermined direction finding method based on the atomic norm. In the invention, the antenna of the receiving end is structured according to the coprime array; modeling is performed according to the received signal of the array; the output signal of the virtual array is calculated; and the interpolation is initialized Output signal; design an optimization method based on atomic norm to restore the interpolated output signal; reconstruct the covariance matrix of the interpolated virtual uniform linear array signal; estimate the direction of arrival based on the reconstructed covariance matrix. The present invention interpolates the discontinuous virtual linear array of the coprime array to the virtual homogeneous array through interpolation, which makes full use of the degrees of freedom and array element information of the coprime array; when vectorizing the covariance matrix to obtain the output signal of the virtual array, The signals at the same position are averaged, so that the information of the signal can be fully utilized than directly selecting the first signal at the same position; the base mismatch problem of the traditional sparse representation method can be avoided, and denoising is introduced when optimizing the problem operation, improving the accuracy of direction finding.

A dual-hole coprime array antenna structure is composed of four sparse subarrays, the total number of array elements is T, and the number of antennas are N and M respectively, wherein N and M are coprime integers, and M<N. The position of the array elements in the CATHDC antenna structure is where d≤λ / 2 is the unit array element spacing, and λ is the carrier wavelength. The antenna structure of the present invention expands the antenna aperture and weakens the mutual coupling effect. The antenna array layout is simple and can Gain more degrees of freedom than existing coprime arrays. The virtual array generated by CATHDC is a uniform array with unit element spacing, and the classical signal angle of arrival estimation algorithm combined with the spatial smoothing method can be directly applied without angle ambiguity.

The invention discloses a wideband signal DOA estimation method based on a coprime array, comprising: S1, designing a coprime array structure by using an antenna; S2, sampling and discrete Fourier transforming the wideband signal received by the antenna in the coprime array Transform to obtain the frequency domain signal output model; S3, calculate the autocorrelation matrix of the frequency domain signal output model and vectorize it to obtain a new signal model; S4, process the new signal model to obtain the spatial smoothing coherence of the wideband signal Variance matrix; S5, dividing the airspace network, constructing a dictionary, and using the dictionary at multiple frequency points of the broadband signal to perform sparse representation of the spatial smooth covariance matrix, forming a multi-measurement vector sparse representation model of multiple dictionaries of the broadband signal ; S6, realize the DOA estimation of broadband signals in the form of solving the sparse inverse problem through the joint sparse constraints on the multi-dictionary sparse representation coefficients. The invention can improve the estimation accuracy of the direction angle of the broadband signal under the low signal-to-noise ratio, and reduce the direction-finding error.

The invention discloses a dual-layer-hybrid-array-based estimation method for a direction angle of arrival. With the method, problems of high operation load, a few of identification signal sources, and large estimation error in the prior art can be solved. The method comprises the following steps: (1), a one-layer coprime array and a two-layer nesting array are constructed respectively; (2), an output signal of the one-layer coprime array and an output signal of the two-layer nesting array are obtained; (3), on the basis of the output signal of the one-layer coprime array and the output signal of the two-layer nesting array, all four-order cumulants are calculated to form a four-order cumulant vector; (4), according to the four-order cumulant vector, an over-complete base is constructed and an airspace sparse vector is defined; (5), detection airspace direction-angle-of-arrival estimation is converted into sparse constraint equation solving; (6), with a convex optimization method, a sparest solution of an airspace sparse vector is obtained; and (7), an amplitude spectrogram is drawn based on the sparest solution and a direction angle of arrival is obtained. According to the method provided in the invention, the signal source number with identifiable arrays increases substantially under the circumstance that the array element number is limited. The method is suitable for target scouting and passive location.

The invention discloses a method for estimating the direction of arrival of an L-type coprime array based on coupled tensor decomposition, which mainly solves the problems of damaged multi-dimensional signal structure and loss of associated information of virtual domain signals in the existing methods. The implementation steps are as follows: L-shaped coprime array with separate sub-arrays and modeling of the received signal; deduce the fourth-order covariance tensor of the received signal of the L-shaped coprime array; derive the fourth-order virtual domain signal corresponding to the augmented virtual uniform cross array; translational segmentation The virtual uniform cross array; the coupled virtual domain tensor is constructed by superimposing and shifting the virtual domain signals; the DOA estimation result is obtained by decomposing the coupled virtual domain tensor. The present invention makes full use of the spatial association properties of the constructed sub-array split L-shaped coprime array virtual domain tensor statistics, realizes high-precision two-dimensional DOA estimation through coupled virtual domain tensor processing, and can be used for target positioning .

The present invention discloses and proposes a three-dimensional SAR sparse imaging method based on the decomposition and fusion of coprime arrays. In the method, the coprime array and the subarrays of the coprime array are firstly reconstructed by compressive sensing iterative minimization of sparse Bayesian reconstruction. The (SBRIM) imaging algorithm performs imaging separately to obtain three synthetic aperture radar images, and then fuses the obtained imaging results to obtain the final 3D SAR sparse imaging result based on array decomposition and fusion. The present invention combines the advantages of the coprime sampling method and the compressed sensing sparse reconstruction method. The coprime sampling method can not only reduce the sampling data, but also is easier to realize systematically than the traditional random sampling method; compared with the traditional sparse imaging method, the method of the present invention can Effectively suppress grating lobes and false targets and improve imaging quality.