Double-base MIMO radar angle estimation method in colored noise background

Abstract

The invention discloses a double-base MIMO radar angle estimation method in colored noise background. Reception array data is matched and filtered, a cross covariance matrix of the reception data is estimated, and a four-order tensor model of the cross covariance matrix is established; a reception direction matrix, an emission direction matrix and a target covariance matrix are initialized, an ESPRIT algorithm is used to initialize the reception direction matrix and the emission direction matrix, and the target cross covariance matrix is initialized into a unit matrix; an alternative least square method is used to carry out iterative computation on the reception direction matrix, emission direction matrix and target covariance matrix till a convergence condition is met; and the least square method is used to estimate target DOD and DOA. Colored noise in the spatial domain is inhibited by using non-relevant characteristic of different fast-beat output noise, all freedom-degree information of array elements is used, the estimation precision is high, and there is no aperture loss.

Description

technical field [0001] The invention relates to a radar signal processing technology, in particular to a bistatic MIMO radar angle estimation method under the background of colored noise. Background technique [0002] The Multiple-input Multiple-output (MIMO) system has great advantages in anti-interference and anti-attenuation. It is the core technology of 5G in the future and the mainstream direction of radar detection in the future. Different from the existing phased array radar system, MIMO radar adopts the signal processing mode of multiple transmission and multiple reception, and uses diversity gain to greatly improve the target detection performance. Compared with traditional phased array radar systems, MIMO radar has potential advantages in terms of resolution, anti-fading, identifiability, and noise suppression. According to the different configurations of MIMO radar transceiver elements, MIMO radars can be divided into two categories: statistical MIMO radars and c...

AI Technical Summary

Problems solved by technology

Wen et al. extended the tensor to further improve the accuracy of the algorithm (Wen F, Zhang Z, Zhang G, et al. A tensor-based covariance differencing method for direction estimation in bistatic MIMO radar with unknown spatial colored noise[J].IEEE Access ,2017,5:18451-18458.), however, this method requires noise to satisfy a symmetric toeplitz structure, which is not universal

Moreover, the HOSVD method uses ESPRIT to estimate the angle after obtaining the subspace, which cannot use the information of all degrees of freedom of the array element, so the estimation accuracy of the algorithm needs to be further improved

Images