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
Keywords :
adaptive filters; parameter estimation; radar detection; radar theory; radar tracking; state estimation; target tracking; tracking filters; adaptive tracking filter; course; curved-track state parameters; data rate; detection; gradual correction; innovation-based common algorithm; longitudinal acceleration; position; small filter gains; speed rate; steady state filter algorithms; transverse acceleration; turn rate; wild maneuver tracking; Acceleration; Change detection algorithms; Error correction; Filters; Radar detection; Radar tracking; Steady-state; Target tracking; Technological innovation; Trajectory;