Joint estimation of target state and ionosphere state for OTHR based tracking

In over-the-horizon radars (OTHRs), the target state updates at a fast rate while the ionosphere state (e.g. The ionospheric height) evolves intermittently and all OTHR based tracking methods have the same prerequisite that the virtual ionospheric height, as the key model parameter in estimating the target 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, resulting in the situation that the ionosphere state is unknown. It motivates us to consider the novel problem of multi-path target tracking in clutters without the help of ionosondes and external sources. The considered problem is formulated as the multi-rate state estimation with random coefficient matrices. First, the multirate state filter (MSF) with causality constraints is established for the multi-rate linear model. For the non-linear measurement model of OTHR, the derived MSF is extended to an iterative multi-rate state filter (IMSF) via the iterative optimization of joint state estimation and parameter identification (the linearized measurement matrix). In a numerical simulation about tracking two targets in four resolvable propagation modes our IMSF is testified.