5 results about "Parallel array" patented technology

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 application discloses a two-dimensional coherent signal DOA estimation method based on double parallel relatively prime array movement, which comprises the following steps: a double parallel array comprises a first subarray and a second subarray, phase compensation is performed on the output of the first subarray and the output of the second subarray to obtain first subarray compensation output and second subarray compensation output; a first vector is obtained based on the first subarray compensation output and the second subarray compensation output, and a second vector is obtained based on the first subarray compensation output; a sparse off-grid optimization function is constructed; accurate angle estimation of an incident signal and an X axis is obtained based on the sparse off-grid optimization function; angle estimation of the incident signal and a Y axis is obtained based on the first vector and the second vector; and angle estimation value of the two-dimensional coherent signal is obtained based on the accurate angle estimation of the incident signal and the X axis and the angle estimation of the incident signal and the Y axis. The application uses the double parallel relatively prime array to perform angle estimation of the two-dimensional coherent signal, and makes up for the deficiency of the relatively prime array in angle estimation of a coherent source.

The invention relates to a modular multiplication method and device based on a parallel array architecture, computing equipment and a medium. The method comprises the following steps: performing initialization processing on variables of all processing units to obtain initial variable data; according to a preset calculation parameter and the input data set, performing data updating on the initial variable data to obtain a data updating result; and determining a modular multiplication calculation result based on the data updating result, the input data set and a preset modular multiplication parameter. By the adoption of the method, it is ensured that all the processing units are in the same state at the beginning of calculation, and calculation confusion caused by initial value difference is avoided; data processing is carried out according to the preset calculation parameters and the input data set, and each processing unit can efficiently complete own tasks in the process, so that unnecessary calculation and waiting time is reduced; and then the input data set, the updated data updating result and the preset modular multiplication parameter are combined for calculation, so that the accuracy and reliability of modular multiplication calculation are effectively improved.

The application belongs to the technical field of information and ocean science, and discloses a UUV side parallel array covariance weighted fusion DOA estimation method. First, the self-covariance and mutual covariance matrices of two sub-arrays are calculated, then the virtual aperture is extended by difference co-array, the covariance matrices of different sources are weighted and fused, then, according to the characteristics of the fused matrix, the trace regularization and kernel norm regularization convex optimization methods are used respectively to reconstruct the complete covariance matrix, finally, the pitch angle and azimuth angle of the target are jointly estimated by subspace decomposition of the constructed extended matrix, and the simulation results verify the effectiveness of the method. The application improves the parameter estimation accuracy through data fusion, significantly improves the degree of freedom under a small number of physical array elements, realizes high-precision azimuth estimation of multiple targets in the underwater environment of the UUV, enhances the target detection capability of the UUV, and has high engineering application value.

The application relates to the technical field of antennas and discloses a high-precision two-dimensional DOA estimation method based on optimal redundant linear arrays, 1) input: array receiving data y i (t), optimal redundant parallel array two-subarray element position coordinates P S1 and P S2 ; 2) parameter calculation ① calculating array autocovariance matrices of two optimal redundant linear arrays according to a formula; ② calculating array cross-covariance matrices between the optimal redundant linear arrays according to a formula. The high-precision two-dimensional DOA estimation method based on optimal redundant linear arrays proposes an extended covariance matrix reconstruction algorithm, the algorithm constructs an extended covariance matrix containing autocovariance matrices and cross-covariance matrices, further constructs an extended covariance matrix reconstruction model, simultaneously realizes high-precision estimation of initial autocovariance matrices and initial cross-covariance matrices, and based on the initial autocovariance matrices and the initial cross-covariance matrices, utilizes a covariance vector sparse representation and a total least squares method in sequence to realize high-precision two-dimensional DOA estimation.