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http://dx.doi.org/10.4218/etrij.2019-0253

Fast-convergence trilinear decomposition algorithm for angle and range estimation in FDA-MIMO radar  

Wang, Cheng (College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics)
Zheng, Wang (College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics)
Li, Jianfeng (College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics)
Gong, Pan (College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics)
Li, Zheng (College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics)
Publication Information
ETRI Journal / v.43, no.1, 2021 , pp. 120-132 More about this Journal
Abstract
A frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle-range-dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast-convergence trilinear decomposition (FC-TD) algorithm to jointly estimate FDA-MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC-TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramer-Rao bounds are presented and simulation results are provided to validate the proposed FC-TD algorithm effectiveness.
Keywords
fast convergence; FDA-MIMO radar; joint angle and range estimation; propagator method; trilinear decomposition;
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