Fan Jin-Yu, Gu Hong, Su Wei-Min, Wang Zhao. MIMO Radar Multi-dimension Angle Estimation with Electromagnetic Vector Sensors of Noncollocating Dipoles/Loops[J]. Journal of Electronics & Information Technology, 2013, 35(8): 1841-1846. doi: 10.3724/SP.J.1146.2012.016648
Citation:
Fan Jin-Yu, Gu Hong, Su Wei-Min, Wang Zhao. MIMO Radar Multi-dimension Angle Estimation with Electromagnetic Vector Sensors of Noncollocating Dipoles/Loops[J]. Journal of Electronics & Information Technology, 2013, 35(8): 1841-1846. doi: 10.3724/SP.J.1146.2012.016648
Fan Jin-Yu, Gu Hong, Su Wei-Min, Wang Zhao. MIMO Radar Multi-dimension Angle Estimation with Electromagnetic Vector Sensors of Noncollocating Dipoles/Loops[J]. Journal of Electronics & Information Technology, 2013, 35(8): 1841-1846. doi: 10.3724/SP.J.1146.2012.016648
Citation:
Fan Jin-Yu, Gu Hong, Su Wei-Min, Wang Zhao. MIMO Radar Multi-dimension Angle Estimation with Electromagnetic Vector Sensors of Noncollocating Dipoles/Loops[J]. Journal of Electronics & Information Technology, 2013, 35(8): 1841-1846. doi: 10.3724/SP.J.1146.2012.016648
A novel algorithm for estimation of Azimuth Direction Of Departure (ADOD), Azimuth Direction Of Arrival (ADOA) and Elevation Direction Of Arrival (EDOA) based on bistatic MIMO radar with electromagnetic vector sensors is presented. The linear transmit array composes of multiple scalar sensors with uniform distribution, while the 2D receive array consist of several electromagnetic vector sensor subarrays. Each subarray contains six orthogonally oriented but spatially noncollocating dipoles/loops. With the application of tensor decomposition, the transmit/receive array manifolds are estimated. From the former, a group of multi-targets DODs are calculated with an ESPRIT algorithm. An improved vector cross product direction finding algorithm is presented to estimate the targets 2D-DOAs, based on the 2D receive array constructed with a presented arrangement of subarrays. The proposed array configuration has great advantage, in spatial aperture extending to refine the estimation accuracy, and in reducing mutual coupling. Corresponding algorithm avoid peak searching and parameter pairing processes. Simulation results are presented to verify the effectiveness of the proposed method.