IMPROVED SPECTRUM SEARCHING GENERALIZED–ESPRIT ALGORITHM FOR JOINT DOD AND DOA ESTIMATION IN MIMO RADAR WITH NON-UNIFORM LINEAR ARRAYS

• Published in: Journal of circuits, systems, and computers Vol. 23; no. 8; p. 1450106
• Main Authors: CHEN, WEIYANG, ZHANG, XIAOFEI
• Format: Journal Article
• Language: English
• Published: Singapore World Scientific Publishing Company 01.09.2014; World Scientific Publishing Co. Pte., Ltd
• Subjects: Algorithms; Angles (geometry); Computer simulation; Direction of arrival; Linear arrays; Parameter estimation; Radar arrays; Rotational spectra; Search algorithms; non-uniform linear array; Multiple-input multiple-output (MIMO) radar; angle estimation
• ISSN: 0218-1266; 1793-6454
• DOI: 10.1142/S0218126614501060

This paper investigates the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar with non-uniform linear arrays, and proposes an improved spectrum searching generalized estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation algorithm in bistatic MIMO radar. The proposed algorithm obtains initial estimation of angles obtained from the signal subspace, and uses the 1D local searchings to achieve the joint estimation of DOD and DOA. Compared to the spectrum searching generalized-ESPRIT algorithm which requires the global searchings and additional pairing, the proposed algorithm just needs the local searchings and obtains automatically paired 2D angle estimation. The angle estimation performance of the proposed algorithm is almost the same as that of the generalized-ESPRIT algorithm, and better than ESPRIT-like algorithm. Furthermore, the proposed algorithm is suitable for irregular array geometry, has much lower complexity than the spectrum searching generalized-ESPRIT algorithm, and imposes less constraint on the transmit/receive sensor spacing, which need not be limited to a half-wavelength strictly. The simulation results verify the effectiveness of the algorithm.