Conference paper Open Access

A new maneuvering target tracking algorithm with input estimation

Kun Zhou,; Zhou, Kun; Wang, Xiqin; Xiqin Wang,; Tomizuka, M.; Bin Zhang, Wei; Wei-Bin Zhang,; Chan, Ching-Yao

A new tracking algorithm is proposed. It treats the target acceleration as a nonrandom term, and consists of a constant velocity filter an input estimator and a maneuver detector implemented in parallel. The new method has the same advantages as the two-stage Kalman estimator which requires a lesser amount of computation and provides even a better performance when compared with an augmented state Kalman filter. At the same time, the new method uses a better tuning parameter and removes a difficulty in implementation of the two-stage Kalman estimator. It is shown that the new filter is a better alternative to the two-stage Kalman estimator on tracking maneuvering targets.

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