Computational Complexity Reduction and AOA Estimation Improvement in the Presence of Multipath for a Multibeam Radar Using Experimental Data

Computational Complexity Reduction and AOA Estimation Improvement in the Presence of Multipath for a Multibeam Radar Using Experimental Data

—: Finding the precise elevation angle of arrival (AOA) of targets in the presence of the multipath effect- when the reflections from the target and the multipath are received in the same beam, range cell and Doppler bin- is one of the most important challenges in air surveillance radars. There is a lot of issues about the effectiveness of high resolution AOA techniques in correlated target scenarios. Here the authors use a practical approach for AOA estimation in low altitude scenario for a surveillance radar. In this paper, monopulse technique and high resolution (data dependent) techniques such as maximum likelihood (ML) or multiple signal classification (MUSIC) are combined to find AOA in the presence of multipath in multibeam radars. In the proposed technique which leads to AOA estimation improvement and computational complexity reduction, targets are detected firstly by multi-beam radars structure. Then, an approximate estimation of the targets’ elevation angle is done by monopulse technique in order to reduce the search zone and subsequently computational complexity in data dependent techniques. The number of uncorrelated targets is estimated in the desired range cell in the next step by the eigenvalue gradient method (EGM) algorithm. Finally, the angles of targets are precisely estimated by high resolution data dependent techniques. MSE of the elevation angle estimation is calculated by comparing the experimental radar data and the secondary surveillance radar (SSR) data (as reference). SSR is located on the radar system.