Using particle filter to track horizontal variations of atmospheric duct structure from radar sea clutter

[摘要] This paper addresses the problem of estimating range-varying parameters ofthe height-dependent refractivity over the sea surface from radar seaclutter. In the forward simulation, the split-step Fourier parabolicequation (PE) is used to compute the radar clutter power in the complexrefractive environments. Making use of the inherent Markovian structure ofthe split-step Fourier PE solution, the refractivity from clutter (RFC)problem is formulated within a nonlinear recursive Bayesian state estimationframework. Particle filter (PF), which is a technique for implementing arecursive Bayesian filter by Monte Carlo simulations, is used to trackrange-varying characteristics of the refractivity profiles. Basic ideas ofemploying PF to solve RFC problem are introduced. Both simulation and realdata results are presented to confirm the feasibility of PF-RFCperformances.

[学科分类] 几何与拓扑