Joint estimation of direction of departure and direction of arrival for multiple‐input multiple‐output radar based on improved joint ESPRIT method

Abstract

This study presents an improved joint estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm for low-complexity simultaneous estimation of direction of departure (DOD) and direction of arrival (DOA) in a multiple-input-multiple-output radar system. The proposed algorithm is based on a data matrix and estimates DOD and DOA without a pairing operation. The computational complexity of the proposed joint ESPRIT algorithm is derived to be less than that of conventional two dimension multiple signal classification (2D-MUSIC) and reduced dimension multiple signal classification. The authors' simulation results demonstrate that the proposed algorithm achieves performance very close to that of 2D-MUSIC and better performance than that of the ESPRIT algorithm.

DOA and DOD Estimation Based on Double 1-D Root-MVDR Estimators for Bistatic MIMO Radars

“…Next, we can use the root finding method again to find the roots of polynomial (7), and the desired rootẑ t;k inside and closest to unit circle. Therefore, the estimated DOD angle of the kth target is given bŷ h t;k ¼ sin À1 ½ðk=2pd t Þ argðẑ t;k Þ. Asĥ t;k is obtained throughĥ r;k ,ĥ r;k andĥ t;k , k ¼ 1; 2; .…”

“…In particular, target localization using bistatic MIMO radars for which the transmitter and receiver arrays are separated has attracted much attention. Some adaptive techniques were applied to MIMO radar for estimating the direction of arrival (DOA) and direction of departure (DOD) angles [3][4][5][6][7][8][9][10][11][12][13][14]. The two-dimensional (2-D) minimum variance distortionless response (MVDR) [3] and the 2-D multiple signal classification (MUSIC) [4] are both high resolution methods for DOA and DOD estimation with peak searches in bistatic MIMO radars.…”

“…However, it is time consuming and the required number of search grids is not clear to determine. In [5][6][7], the estimation of signal parameters via rotational invariance technique (ESPRIT) technique were applied to the joint estimation of target DOA and DOD, avoiding the peak searching process of the MVDR and MUSIC methods and thus reducing much of the computational load. These methods can also solve the auto-pairing problem.…”

Sparse DOD/DOA Estimation in a Bistatic MIMO Radar With Mutual Coupling Effect

“…In [12,13], the DOD/DOA estimation method for the scenario with unknown correlated noise has been proposed, where the estimation method is based on the canonical correlation decomposition and the shift-invariance properties of Kronecker product. Additionally, some studies [14][15][16][17] have proposed algorithms based on the multiple signal classification (MUSIC) and the estimation of signal parameters via rotational invariance techniques (ESPRIT) to estimate DOD/DOA in MIMO radar systems. However, these studies have not considered the mutual coupling between antennas in transmitter and receiver.…”

DOA Estimation for Multiple Targets in MIMO Radar with Nonorthogonal Signals

“…In the existing works, many methods have been proposed to estimate the target direction of arrival (DOA). For example, in the colocated MIMO radar system, a reduced-dimension transformation is used to reduce the complexity in the DOA estimation based on the estimation of signal parameters via rotational invariance technique (ESPRIT) [9]; a computationally efficient DOA estimation algorithm is given for the monostatic MIMO radar based on the covariance matrix reconstruction in [10]; a joint DOA and direction of departure (DOD) estimation method based on ESPRIT is proposed in [11]. Additionally, in the coprime MIMO radar system, a reduced-dimension multiple signal classification (MUSIC) algorithm is proposed [12] for both DOA and DOD estimation; a combined unitary ESPRIT-based algorithm is given for the DOA estimation [13].…”