Broadband signal source positioning method based on subspace weight sparse recovery

Abstract

The invention discloses a broadband signal source positioning method based on subspace weight sparse recovery. The method comprises steps that multiple broadband signals having unknown correlation in the space are irradiated to a linear sensor array formed by multiple isotropy sensors, and a complex observation matrix is acquired according to the linear sensor array; a target signal arrival angle is estimated under a compression sensing framework according to the complex observation matrix to carry out reconstruction to acquire a first signal model; truncated singular value decomposition of the complex observation matrix is carried out to construct a weight matrix; a weight vector is calculated according to the weight matrix; dimensional reduction is carried out according to the first signal model to acquire a second signal model; the second signal model is optimized to acquire a third presentation form of the target signal under the compression sensing framework; a spectral function is calculated according to the third presentation form of the target signal under the compression sensing framework to acquire an estimate of the target signal arrival angle. The method is advantaged in that decorrelation capability of a compression sensing algorithm and estimation precision of an MUSIC algorithm are realized.

Description

technical field [0001] The invention belongs to the field of array signal processing and specifically designs a broadband signal source positioning method based on subspace weighted sparse recovery. Background technique [0002] The research on the target angle estimation problem has a history of several decades, and it is of great significance in many fields, including wireless communication, radar, sonar and many other fields. [0003] When the form of the target signal is unknown, the traditional wideband target signal angle estimation first needs to convert the wideband signal into a narrowband signal, and then use some narrowband target signal angle estimation algorithms to estimate the target angle. There are two ways to convert broadband signals into narrowband signals. One is the non-coherent processing method. Through short-time Fourier transform, the target signal is transferred to the frequency domain, and then the target angle is estimated independently at each f...

AI Technical Summary

Problems solved by technology

[0004] In comparison, the conventional beamforming algorithm is the simplest, but this method has high sidelobes and the resolution is limited by the Rayleigh resolution limit. The only way to increase the resolution is to increase the array aperture

The resolution of the minimum variance undistorted algorithm and the MUSIC algorithm are not limited by Rayleigh resolution, and super-resolution can be achieved, but the decoherence ability of the two algorithms is poor, and the performance in the coherent source scene will be greatly reduced

Images