An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

Xinping Mi,Zan Liu,Xihong Chen,Qiang Liu,Gen Q Xu

doi:10.1155/2021/6650278

Abstract

Direction of arrival (DOA) estimation plays an important role in the passive surveillance system based on troposcatter. Rank deficiency and subspace leakage resulting from multipath propagation can deteriorate the performance of the DOA estimator. In this paper, characteristics of signals propagated by troposcatter are analyzed, and an efficient DOA estimation method is proposed. According to our new method, the invariance property of noise subspace (IPNS) is introduced as the main method. To provide precise noise subspace for INPS, forward and backward spatial smoothing (FBSS) is carried out to overcome rank deficiency. Subspace leakage is eliminated by a two-step scheme, and this process can also largely reduce the computational load of INPS. Numerical simulation results validate that our method has not only good resolution in condition of closely spaced signals but also superior performance in case of power difference.

Highlights

Troposcatter as a promising beyond-line-of-sight (b-LOS) communication link has been well studied [1, 2]
E Direction of arrival (DOA) estimation method employed by a passive surveillance system must confront coherent signals owning different power and close DOAs. e maximum likelihood method [7] can overcome the multipath effect
To improve the performance of the passive surveillance system, a novel DOA estimation method is developed in this paper. e invariance property of noise subspace (IPNS), which has strong robustness for close DOAs and different power, is employed as the main method

Summary

Introduction

Troposcatter as a promising beyond-line-of-sight (b-LOS) communication link has been well studied [1, 2]. Erefore, the multipath effect of troposcatter can bring rank deficiency and subspace leakage to pivotal covariance matrix, and prevalent DOA estimation methods, including multiple signal classification (MUSIC) and estimation signal parameters via rotational invariance technique (ESPRIT), will suffer from serious performance deterioration. E DOA estimation method employed by a passive surveillance system must confront coherent signals owning different power and close DOAs. e maximum likelihood method [7] can overcome the multipath effect. To improve the performance of the passive surveillance system, a novel DOA estimation method is developed in this paper. To improve the performance of INPS, rank deficiency is overcome by FBSS, and subspace leakage is eliminated on the basis of a two-step scheme. Some conclusions are drawn in Section 5. e notations of tr(·), ()H, ()T, and (·)∗ denote the trace, conjugationtranspose, transpose, and conjugation of the matrix, respectively

Signal Model

RFB 2L

DOA Estimation Model

Simulations and Results