Joint Transmission and Reception Diversity Smoothing for Direction Finding of Coherent Targets in MIMO Radar

Abstract

Abstract-The direction estimation problem of coherent targets in multiple-input multiple-output (MIMO) radar systems is studied and a scheme with joint transmission and reception diversity smoothing is proposed. When both the transmitting and receiving antenna arrays are located closely in space, the new approach leads to much more available covariance matrices for spatial smoothing to decorrelate the coherent signals. As a result, a better estimation performance is achieved compared to the existing transmission diversity smoothing (TDS) method. It can also identify more coherent targets when sparse antenna arrays are employed. On the other hand, the proposed approach can be applied to joint direction of arrival (DOA) and direction of departure (DOD) estimation using existing direction estimation algorithms when the transmit and receive arrays are separated far away from each other (i.e. the bistatic case). Two specific methods are proposed under the scheme, one is based on forwardonly (FO) spatial smoothing and one is based on forwardbackward (FB) processing. Due to the increased number of covariance matrices for spatial smoothing, a further improved performance is achieved by the FB-based one.

Millimeter-Wave Beamformed Full-Dimensional MIMO Channel Estimation Based on Atomic Norm Minimization

“…Finally, each channel path's coefficient, i.e., σ l can be estimated via the least-squares (LS) method. The MUSIC algorithm has been popular for its good resolution and accuracy in AoD/AoA estimation [30], [31]. However, it is also reported that the off-grid CS method [16] can outperform the MUSIC algorithm in terms of estimation accuracy in noisy environments [19], [32].…”

Spatial and Polarization Angle Estimation of Mixed-Targets in Mimo Radar

“…2, we consider L = 100 snapshots, signal to noise ratio (SNR) is 5 dB, and K = 3 coherent targets (i.e., K u = 0, K p = 0, K c = 3). The reflectivities of the targets are chosen as s c (l) = s 1 (l)ρ 1 , where s 1 (l) is generated by the complex Gaussian with zero-mean and unit-variance and ρ 1 The methods proposed in [8] (denoted as JTRDS-SS) and in [9] (denoted as JTRDS-EVS) estimate only the elevation angles of targets. Thus, for measuring and comparing the RP, threshold δ is constructed based on a single parameter that is elevation angle, and the performance is depicted in Fig.…”

“…For localization of the targets, direction estimation is a key issue and has found many investigations in the literature [2][3][4][5][6][7][8][9]. Majority of these investigations focus on the estimation of direction-of-departure (DOD) and direction-of-arrival (DOA) of uncorrelated targets [2][3][4][5][6][7] and coherent targets [8,9]. Two-dimensional (2D) DOD and 2D-DOA estimation have also been investigated for the case of uncorrelated targets [10][11][12].…”

Cross-correlation matrix Root-MUSIC algorithm for bistatic multiple-input multiple-output radar

“…With the development of the bistatic multiple-input multiple-output (MIMO) radar, the direction of departure (DOD) and direction of arrival (DOA) estimation has attracted the interests of many researchers and many sub-space algorithms based on eigendecomposition are developed as a solution to this problem [1][2][3][4][5][6][7][8][9][10][11]. Two-dimension multiple signal classification (MUSIC) algorithm [1] is proposed to estimate 2-D angles utilizing 2-D angle search, which can obtain good angle estimation performance under Gaussian noise, though the algorithm has a huge computational complexity.…”