Joint 2-D DOA Tracking for Multiple Moving Targets using Adaptive Frequency Estimation
Jun Liu, Xiangqian Liu · 2007
In this paper, we propose a low-complexity adaptive two-dimensional (2-D) frequency estimation algorithm to jointly track 2-D direction-of-arrivals (DOAs) of multiple moving targets with a uniform rectangular array (URA). The LOAFRI subspace tracking algorithm is applied to estimate the signal subspace recursively, then an adaptive eigenvector-based frequency estimation approach is used to resolve the 2-D DOAs from the estimated signal subspace. The eigenvectors are obtained from the eigen-decomposition of an adaptively weighted matrix, whose weighting factors are updated according to the current DOA estimates and the optimization criterion derived from the perturbation analysis to minimize estimation error variance. The complexity order of the proposed algorithm is analyzed in detail to demonstrate its low computation cost, and the tracking performance is validated by simulation results.