On using Bayes Risk for Data Association to Improve Single-Target Multi-Sensor Tracking in Clutter

Bayes Risk를 이용한 False Alarm이 존재하는 환경에서의 단일 표적-다중센서 추적 알고리즘

In this Paper, a new multi-sensor single-target tracking method in cluttered environment is proposed. Unlike the established methods such as probabilistic data association filter (PDAF), the proposed method intends to reflect the information in detection phase into parameters in tracking so as to reduce uncertainty due to clutter. This is achieved by first modifying the Bayes risk in Bayesian detection criterion to incorporate the likelihood of measurements from multiple sensors. The final estimate is then computed by taking a linear combination of the likelihood and the estimate of measurements. We develop the procedure and discuss the results from representative simulations.