Track association for over-the-horizon radar with a statistical ionospheric model
Over-the-horizon (OTH) radar exploits the refractive nature of high-frequency radio-wave propagation through the ionosphere for the purpose of wide-area surveillance. In order to localize targets, however, multipath slant tracks from different ionospheric layers, but the same target must be combined. The process of track association is complicated both by uncertainty in down-range ionospheric conditions and by the fact that in multiple target cases, the associations of slant tracks to targets are unknown. This paper proposes a method for joint multiple target ground track estimation and slant track association, or mode linking, with uncertain ionospheric conditions where the slant-track-to-target assignments and slant tracks' ray mode paths are unknown. Maximum a posteriori (MAP) mode linking exploits the statistical dependence between slant tracks on different ray mode paths to provide accurate mode linking decisions and ray path assignments and, thus, accurate ground track estimates. The approach uses Markov modeling for the dependence between different ray path types as well as for the temporal correlation between mode linking hypotheses at different revisits to obtain consistent mode linking decisions. Monte Carlo simulation results suggest that MAP mode linking can potentially provide a significant improvement in ground track accuracy over conventional mode linking with higher probabilities of correct track associations and ray mode assignments. Results with real OTH radar slant track data of multiple slant tracks from multiple targets and validated against ground truth that support the simulation study are presented.
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