A novel approach for distributed maneuver detection

Research output: Chapter in Book/Entry/PoemConference contribution


Quickest and accurate maneuver detection is critical to modern tracking systems. In this paper, the target maneuver detection problem when using multiple sensors is investigated. The target dynamic model and measurement model may exhibit complex nonlinearity and non-Gaussianity. Therefore, particle filters are implemented at the local sensors to predict the target state. At each time step, local sensors transmit binary data to the fusion center, where decision fusion is performed to detect the potential occurrence of target maneuver. Since the sensors observe the same dynamic process, their measurements, and thus the local decisions, are correlated, which has to be taken into account at the fusion center. By considering correlation and using the Bahadur-Lazarsfeld expansion in the fusion rule, we can achieve better system design (local decision rules and fusion rule) than that achieved by assuming independence between sensors. Experimental results show that the distributed maneuver detection system achieves much better performance than using only a single sensor; the correlated design outperforms the independent design, and is very close to the optimal performance, especially for high correlation scenarios.

Original languageEnglish (US)
Title of host publication2006 IEEE Radar Conference
Number of pages7
StatePublished - Nov 21 2006
Event2006 IEEE Radar Conference - New York, United States
Duration: Apr 24 2006Apr 26 2006

Publication series

NameCIE International Conference of Radar Proceedings


Other2006 IEEE Radar Conference
Country/TerritoryUnited States
CityNew York

ASJC Scopus subject areas

  • General Engineering


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