Subarray division-based near-far field mixed source passive positioning method

Abstract

The invention discloses a subarray division-based near-far field mixed source passive positioning method and belongs to the field of array signal processing. A symmetric and uniform linear array sensor array is used for receiving a target signal. Sensors are properly selected to form sub-arrays and the covariance treatment is carried out on each sub-array. After that, proper sensor data are selected for constructing a matrix only containing the angle information. The matrix is subjected to characteristic value decomposition, and then a corresponding noise subspace is obtained. Through the searching of a one-dimensional MUSIC spectral peak, a sub-angle corresponding to a real angle is obtained. After that, according to the spatial geometrical relationship, the real angle information is worked out. Furthermore, based on the MUSIC spectral peak searching process, the distance information is obtained. According to the invention, the use of a four-order cumulant is avoided, and the calculation complexity of the algorithm is effectively reduced. The operation time of the algorithm is shortened. The additional parameter matching process is avoided.

Description

technical field [0001] The invention belongs to the field of array signal processing, in particular to a passive positioning method for multi-target near-far field mixed sources. Background technique [0002] Passive source localization is an important research content in the field of array signal processing. According to the distance between the positioning target and the sensor array, it can be divided into near-field source localization and far-field source localization. Traditional passive positioning is mainly far-field source positioning, and the wavefront of the source is a plane wave, but when some sources are located in the Fresnel (Fresnel) region of the array aperture (for example: near-field source), the inherent curvature of the wavefront It cannot be ignored, that is, the assumption of the far-field plane wave is no longer valid, and it needs to be described by spherical waves. In practical application scenarios, for example, when a microphone array is used to...

AI Technical Summary

Problems solved by technology

Analyzing the implementation process of the algorithm, it can be seen that there are two shortcomings as follows: (1) The construction of the high-dimensional fourth-order cumulant matrix leads to high computational complexity; (2) When the far-field source and the near-field source have similar or even the same For the azimuth angle, the first direction matrix no longer satisfies the full-rank condition, which makes it difficult to correctly distinguish the signal subspace and the noise subspace, resulting in an estimation error problem

However, similar to the two-step MUSIC algorithm, this algorithm still has two problems of high computational complexity and estimation errors.

Images