Fuzzy logic applications in filtering and fusion for target tracking

A fuzzy Kalman filter algorithm is developed for target tracking applications and its performance evaluated using several numerical examples. The approach is relatively novel. A comparison with Kalman filter and an adaptive tuning algorithm is carried out. The applicability and usefulness of fuzzy logic in data fusion is also demonstrated. The performance of both the extended Kalman filter and fuzzy extended Kalman filter is evaluated using real data of a manoeuvering target and it is found that fuzzy extended Kalman filter shows better performance as compared to extended Kalman filter.