Direct Multi-Target Tracking and Multisensor Fusion Using Antenna Arrays
نویسنده
چکیده
This paper investigates a direct Target Motion Analysis (TMA) estimator for the problem of calculating the states (i.e. source positions, velocities, etc.) of multiple sources from measurements made with multiple (fixed or moving) antenna arrays. We use the novel Subspace Data Fusion (SDF) approach and extend it to the multisensor case. In the SDF approach, subspaces are formed in a first pre-processing step from the raw antenna outputs. Then, the parameters of interest are estimated directly from a single cost function, which results from fusing all subspaces. This approach requires only a single low-dimensional optimization and completely circumvents the bearing data association problem inherent in traditional TMA approaches. We derive the Cramér-Rao Bound (CRB) for the direct multitarget tracking problem. In Monte Carlo simulations we find that the SDF estimator approaches the CRB and always performs better than or equal to the traditional TMA approach. We show that the state estimation accuracy can be improved by using multiple antenna arrays.
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