Low complexity subspace-based two-dimensional direction-of-arrivals tracking of multiple targets

This paper deals with the problem of tracking the two-dimensional (2-D) direction-of-arrivals (DOAs) (i.e., azimuth and elevation angles) of multiple moving targets with crossover points on their trajectories, and we propose an new computationally efficient subspace-based 2-D DOA tracking algorithm for the L-shaped sensor array structured by two uniform linear arrays (ULAs). First, a new computationally efficient cross-correlation based 2-D DOA estimation with automatic pair-matching (CODEC) batch method is developed for noncoherent narrowband signals, where the computationally expensive procedures of eigendecomposition in subspace estimation and pair-matching of the estimated azimuth and elevation angles are avoided. Then a new 2-D DOA tracking algorithm is proposed, the association of the estimated azimuth and elevation angles at two successive time instants is accomplished by employing a dynamic mode and the Luenberger state observer. The simulation results show that the proposed tracking algorithm has good adaptability and tracking capability.