해석적 방법에 의한 PDA-AI 성능의 Tight Bound.

Abstract

- In this paper, We propose a new target tracking filter which utilizes PDA-AI for data association in a clutter environment and also propose an analytic solution for ideal filter covariance which accounts for all the possible events in PDA-AI. Monte Carlo simulation for the proposed filter in a clutter environment indicates that the proposed analytic solution forms a tight lower bound for the error covariance of PDA-AI filter.