An Estimation Method of Source Elevation Angle and Azimuth Angle Based on L-shaped Array
An azimuth and array technology, which is used in the estimation of source elevation and azimuth angles, can solve problems such as limitations, and achieve the effects of suppressing noise interference to signals, suppressing noise, and reducing the difficulty of high-dimensional grid division.
Active Publication Date: 2018-08-07
JILIN UNIV
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[0005] The present invention provides a method for estimating source elevation angle and azimuth angle based on an L-shaped array to solve the problem that current sparse reconstruction methods are only limited to one-dimensional DOA (elevation angle or azimuth angle) estimation
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[0024] Step 1: There are K far-field narrowband incident signals s k (t), incident to an L-shaped array composed of 2M isotropic sensors, the array is located on the plane of the y-axis and the z-axis, in order to reduce the computational complexity of the sparse reconstruction algorithm for the estimation of elevation angle and azimuth angle, we Select an array composed of different array elements to process the received data. The elevation angle of the kth signal in the received data is α k , the azimuth angle is β k , (1≤k≤K), d is the distance between the sensors and is of equal length, let the array element at coordinates (0,md,nd) be the (m,n)th array element, (m,n) ∈{(M-1,0),Λ(1,0),(0,0),(0,1),Λ,(0,M)}, m is the mth sensor located on the y-axis, n is the nth sensor located on the z-axis, then at a sampling time t, the received signal of the (m,n)th array element is j is the imaginary unit, in the formula, s k (t) represents the kth incident signal, n m,n (t) is th...
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The invention provides an L type array-based information source elevation angle and azimuth estimation method and belongs to the array signal processing field. According to the method, the particularities of an L type array are utilized, and array elements at different positions are selected to form a sub array One and a sub array Two, wherein the sub array One only includes elevation angle information and is unrelated to azimuths. At first the sub array One is subjected to sparse representation, and a non-convex penalty function is utilized to reconstruct an elevation angle value; the elevation angle value is substituted into the direction matrix of the sub array Two, sparse representation is performed on an obtained data model, so that an acceptance model only containing an azimuth can be obtained; singular value decomposition is performed on the model, so that the azimuth can be solved through a convex optimization toolkit, and automatic pairing of parameters is completed. With the L type array-based information source elevation angle and azimuth estimation method adopted, the problem of difficult division of high-dimensional grids in sparse reconstruction-based multi-parameter joint estimation can be solved. Successive solving processes of the two sub arrays are utilized to complete the automatic pairing of the parameters, and therefore, interference of noises on signals can be better suppressed, and the accuracy of estimation can be improved.
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technical field [0001] The invention relates to the field of array signal processing, in particular to a method for estimating the elevation angle and azimuth angle of a signal source. Background technique [0002] Source parameter estimation is the main research content in the field of array signal processing, and has important application value in wireless communication, radar, sonar and many other fields. Source parameter estimation is mainly to estimate the elevation angle, azimuth angle and distance of the source. [0003] The existing higher resolution algorithms are all based on the subspace method, and the subspace method has some shortcomings under the inherent framework. They all require a higher signal-to-noise ratio, a larger number of snapshots, or accurate source prior information. Therefore, these disadvantages greatly restrict the practicability of the algorithm. [0004] In recent years, the idea of sparse reconstruction has been rapidly involved in arr...
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IPC IPC(8): G01S3/14
CPCG01S3/14
Inventor 孙晓颖顾飞飞秦宇镝陈建燕学智
Owner JILIN UNIV