Novel angle estimation for bistatic MIMO radar using an improved MUSIC

Abstract

In this article, we study the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar and propose an improved multiple signal classification (MUSIC) algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation. The proposed algorithm obtains initial estimations of angles obtained from the signal subspace and uses the local one-dimensional peak searches to achieve the joint estimations of DOD and DOA. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm, and is almost the same as that of two-dimensional MUSIC. Furthermore, the proposed algorithm can be suitable for irregular array geometry, obtain automatically paired DOD and DOA estimations, and avoid two-dimensional peak searching. The simulation results verify the effectiveness and improvement of the algorithm.

Joint direction finding and array calibration method for MIMO radar with unknown gain phase errors

“…After the estimations of the gain phase errors, the arrays can be calibrated (compensate the gain phase errors in the received data), and the algorithms in [5][6][7][8][9][10][11][12][13][14] can be used when detecting other targets. Till now, the proposal of the algorithm for the joint direction finding and array calibration in MIMO radar has been achieved.…”

“…Multiple-input multiple-output (MIMO) radars, which utilise multiple antennas to transmit orthogonal waveforms simultaneously and similarly receive the reflected signals via multiple antennas, have many potential advantages over other radars [1][2][3][4]. Direction finding in MIMO radar is a key issue, which has been studied by lots of researchers [5][6][7][8][9][10][11][12][13][14]. Many algorithms such as multiple signal classification (MUSIC) [5], estimation of signal parameters via rotational invariance (ESPRIT) [6,7], ESPRIT-MUSIC [8,9], unitary root-MUSIC method [10], direction of arrival (DOA) matrix method [11], propagator method [12] and parallel factor [13,14] have been established for the direction finding.…”