Joint range and angle estimation of low-elevation target with bistatic meter-wave FDA-MIMO radar

Frequency diverse array multiple-input-multiple-output (FDA-MIMO) radar, which has gained much attention in recent years, can be used for the estimation of multidimensional parameters due to the range-dependent property of the beampattern. The localization of low-elevation targets is a key problem to be solved in meter-wave radar. Combining the advantages of the bistatic system, this paper investigates the joint direction of departure (DOD), direction of arrival (DOA), and range multiparameter estimation problem of the bistatic meter-wave FDA-MIMO radar. Firstly, the signal model of the bistatic meter-wave FDA-MIMO radar is derived. Then the signal model is deformed and then applied to the generalized multiple signal classification (MUSIC) algorithm which does not need to consider the signal coherence. A better performance steering vector matching (SVM) reduced dimension MUSIC algorithm is proposed by exploring the signal model characteristics. Then the computational complexity of the two algorithms and the derivation of Cramer Rao bound (CRB) for estimating low-elevation target parameters is given. The innovation of this paper is to provide a joint localization model for bistatic meter-wave FDA-MIMO, which extends the study of bistatic FDA-MIMO radar to the field of coherent signals. The simulation results verify the effectiveness of two localization algorithms without decoherence processing. (c) 2022 Elsevier Inc. All rights reserved.

Automated summary

This paper investigates the joint estimation problem of direction of departure, direction of arrival, and range for bistatic meter-wave FDA-MIMO radar. It proposes a reduced dimension MUSIC algorithm and provides the computational complexity analysis and Cramer Rao bound derivation. The simulation results demonstrate the effectiveness of the proposed algorithms.