Research Of Multipath Data Fusion Method For Over-The-Horizon Radar

The sky-wave Over-the-Horizon Radar (OTHR) and the sky-transmit- ground-receive OTHR, which utilize the ionosphere as the medium, will inevitably produce multipath data fusion problem. Multipath data fusion is composed of multipath data association and multipath trajectory association, and usually the trajectory association is the subsequence of the data association. However, a novel method named Multi-Model based Multipath Data Association (MM-MDA) presented in this thesis can put the multipath data and trajectory association into a uniform structure.Firstly, the measurement model of sky-transmit-ground-receive OTHR, which is similar with that of the sky-wave OTHR, is deduced in this thesis. And then the layer structure of ionosphere, which is the souce of multipath, and the effect of ionospheric uncertainty are introduced in this thesis. Besides, the uniform-Poisson statistic model is used to describe clutter, which together with OTHR measurement model make up of the integrated OTHR multipath model.Secondly, based on the OTHR model, the problem of tracking target in multipath is stated, and the relationship between tracking filtering and data association is also indicated. And then the filtering structure and the trajectory management stretagy of MM-MDA, which are the main innovations in this thesis, are introduced in detail. The modified version of algorithm taking the ionospheric uncertainty into account is also stated. Besides, as contrast, the classical Multipath Probabilsitic Data Association (MPDA) is also introdued in brief.Finally, the performance of different OTHR structure and different fusion method is illustrated and compared in many different scenarios. The simulation results indicate that: the sky-transmit-ground-receive OTHR has better trajectory tracking and management performance than sky-wave OTHR, which is due to its less number of multipaths; meanwhile the trajectory tracking performance of MM-MDA is similar with that of MPDA, but MM-MDA has more efficient trajectory management performance, because it is able to complete trajectory association through deleting illusive multipath track copies effectively.