Design of the Target Estimation Filter based on Particle Filter Algorithm for the Multi-Function Radar

The estimation filter in radar systems must track targets' position within low tracking error. In the Multi- Function Radar(MFR), α-β filter and Kalman filter are widely used to track single or multiple targets. However, due to target maneuvering, these filters may not reduce tracking error, therefore, may lost target tracks. In this paper, a target tracking filter based on particle filtering algorithm is proposed for the MFR. The advantage of this method is that it can track targets within low tracking error while targets maneuver and reduce impoverishment of particles by the proposed resampling method. From the simulation results, the improved tracking performance is obtained by the proposed filtering algorithm.Keywords : Multi-Function Radar(MFR, 다기능레이더), Target Estimation Filter(추적 필터), Particle Filter(파티클 필터), Importance Sampling(중요성 샘플링), Resampling(샘플 재 표집), Bayesian Estimation, Kalman Filter(칼만 필터)