Two-dimensional direction tracking of coherent signals with two parallel uniform linear arrays

In some practical applications, the two-dimensional (2-D) direction-of-arrivals (DOAs) of incident signals should be estimated adaptively or the time-varying 2-D DOAs should be tracked promptly from the noisy array data, and multipath propagation is usually encountered due to various reflections, where the incident signals are caused to be coherent (i.e., fully correlated). In this paper, we propose a new computationally efficient subspace-based adaptive algorithm for 2-D DOA tracking of multiple coherent incident signals by using two parallel uniform linear arrays (ULAs). In the proposed algorithm, the computationally expensive eigendecomposition and the pair-matching of estimated 2-D DOAs are avoided, and the association of estimated 2-D DOAs at two successive time instants is accomplished by employing the Luenberger observer and dynamic model of direction trajectories. The effectiveness of the proposed algorithm are verified through numerical examples.