Multi-path multi-rate filter for OTHR based tracking systems

The OTHR (over-the-horizon radar) based tracking methods have a common prerequisite that the virtual ionospheric height, as the key ionosphere state, should be obtained either by ionosondes or external sources. However, ionosondes can not be deployed arbitrarily and external sources may not be always available, which results in the situation that the ionosphere state is unknown. This motivates us to study the problem of joint estimation of target state and ionospheric state in clutters without ionosondes and external sources. First, the considered problem is formulated as a multi-rate estimation one, and a multi-rate filter(MRF) is derived in the linear minimum mean square error (LMMSE) sense. Then the MRF is extended to the nonlinear case via the iterative optimization provided that measurements are received from one deterministic mode. By taking into account the multi-path data association hypothesis, the idea of convex optimization combination is used to fuse the estimates from different propagation modes to achieve the estimates for one single data association hypothesis. Finally, by updating the estimates of all association hypotheses, we obtain the multi-path multi-rate filter (MPMRF). The proposed MPMRF is shown effective in the simulation about tracking one target in the case of four resolvable propagation modes.