scholarly journals Efficient angle and polarization parameter estimaiton for electromagnetic vector sensors multiple-input multiple-output radar by using sparse array

2020 ◽  
Vol 69 (7) ◽  
pp. 074302
Author(s):  
Qian-Peng Xie ◽  
Xiao-Yi Pan ◽  
Ji-Yuan Chen ◽  
Shun-Ping Xiao
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yucai Pang ◽  
Song Liu ◽  
Yun He

Larger array aperture is provided by sparse arrays than uniform ones, which can improve the angle estimation resolution and reduce the cost of system evidently. However, manifold ambiguity is introduced due to the array sparsity. In this paper, a Power Estimation Multiple-Signal Classification (PE-MUSIC) algorithm is proposed to solve the manifold ambiguity of arbitrary sparse arrays for uncorrelated sources in Multiple-Input Multiple-Output (MIMO) radar. First, the paired direction of departure (DOD) and direction of arrival (DOA) are obtained for all targets by MUSIC algorithm, including the true and spurious ones; then, the well-known Davidon–Fletcher–Powell (DFP) algorithm is applied to estimate all targets’ power values, among which the value of a spurious target trends to zero. Therefore, the ambiguity of sparse array in MIMO radar can be cleared. Simulation results verify the effectiveness and feasibility of the method.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yongqiang Yang ◽  
Ningjun Ruan ◽  
Guanjun Huang ◽  
Junpeng Shi ◽  
Fangqing Wen

In this paper, a novel two-dimensional (2D) direction-of-departure (DOD) and 2D direction-of-arrival (DOA) estimate algorithm is proposed for bistatic multiple-input multiple-output (MIMO) radar system equipped with coprime electromagnetic vector sensors (EMVS) arrays. Firstly, we construct the propagator to obtain the signal subspace. Then, the ambiguous angles are estimated by using rotation invariant technique. Based on the characteristic of coprime array, the unambiguous angles estimation is achieved. Finally, all azimuth angles estimation is followed via vector cross product. Compared to the existing uniform linear array, coprime MIMO radar is occupying large array aperture, and the proposed algorithm does not need to obtain signal subspace by eigendecomposition. In contrast to the state-of-the-art algorithms, the proposed algorithm shows better estimation performance and simpler computation performance. The proposed algorithm’s effectiveness is proved by simulation results.


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