A beamspace maximum likelihood algorithm for target height estimation for a bistatic MIMO radar

This paper discusses beamspace target height estimation for bistatic multiple-input multiple-output (MIMO) radars. Beamspace super-resolution algorithms for target height estimation have attracted significant attention due to low data transmission, storage, and computation. However, current literature has not yet considered beamspace target height estimation for a bistatic MIMO radar. Although target height estimation algorithms can be directly applied to a bistatic MIMO radar after minor modifications, such a direct application does not afford optimum performance. Therefore, we develop a threedimensional beamspace maximum likelihood data fusion (3D-BMLF) algorithm appropriate for the target height estimation algorithm of a bistatic MIMO radar. The 3D-BMLF algorithm first converts target signals from the element space to the 3D beamspace, separates the transmitter and the receiver signals, and obtains two closed-form solutions of target height using the beamspace ML algorithm. Finally, the proposed method fuses the two closed-form solutions by minimizing the mean square error (MSE) of estimation. As a result, the 3D-BMLF algorithm has a very low computational burden and good estimation accuracy. Our computational complexity analysis and simulation results demonstrate the suitability of the 3D-BMLF algorithm for engineering applications.(C) 2021 Elsevier Inc. All rights reserved.

Automated summary

This paper discusses beamspace target height estimation for bistatic multiple-input multiple-output (MIMO) radars. The proposed three-dimensional beamspace maximum likelihood data fusion (3D-BMLF) algorithm provides a low computational burden and good estimation accuracy for target height estimation. It is suitable for engineering applications in a bistatic MIMO radar.