Maneuvering target tracking with high-order correlated noise - a multirate Kalman filtering approach

Dah Chung Chang, Wen-Rong Wu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

A multirate Kalman filtering algorithm for target tracking with high-order correlated noise is proposed. The measurement signal is first split into subbands using a filter bank. Then, the correlated noise in each subband is modeled using a first-order AR process and the AR parameters are identified online. Finally, a multirate Kalman reconstruction filter is used to obtain the state estimate. This method can be directly incorporated into the IMM algorithm, resulting in an effective tracking scheme. Simulations show that the new multirate processing scheme can significantly improve tracking performance.

Original languageEnglish
Pages (from-to)103-123
Number of pages21
JournalWireless Personal Communications
Volume17
Issue number1
DOIs
StatePublished - 1 Jan 2001

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