Tracking wild maneuvers at low data-rate, using curved-track state parameters

Abstract

A rapidly adapting tracking filter, working with a comparatively low data-rate, is described. The filter uses position, course, turn rate, speed and speed rate as the state parameters to handle the curved parts of the trajectory better. The trajectory is continually modeled as moving under a transverse acceleration and a longitudinal acceleration, each large or negligible, which change the turn rate and the speed rate accordingly. Wild maneuvers are detected and corrected rapidly to a large extent, with a high confidence level, mild maneuvers are left to a gradual correction through small filter gains, as in steady state filter algorithms, and medium maneuvers are gracefully fitted in between, through an innovation-based common algorithm.