Distributed data association for multi-target tracking in sensor networks

Chen, Lei and Çetin, Müjdat and Willsky, Alan S. (2005) Distributed data association for multi-target tracking in sensor networks. In: International Conference on Information Fusion, Philadelphia, Pennsylvania

[thumbnail of chen_FUSION05.pdf] PDF

Download (455kB)


Associating sensor measurements with target tracks is a fundamental and challenging problem in multi-target tracking. The problem is even more challenging in the context of sensor networks, since association is coupled across the network, yet centralized data processing is in general infeasible due to power and bandwidth limitations. Hence efficient, distributed solutions are needed. We propose techniques based on graphical models to efficiently solve such data association problems in sensor networks. Our approach scales well with the number of sensor nodes in the network, and it is well--suited for distributed implementation. Distributed inference is realized by a message--passing algorithm which requires iterative, parallel exchange of information among neighboring nodes on the graph. So as to address trade--offs between inference performance and communication costs, we also propose a communication--sensitive form of message--passing that is capable of achieving near--optimal performance using far less communication. We demonstrate the effectiveness of our approach with experiments on simulated data.
Item Type: Papers in Conference Proceedings
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Müjdat Çetin
Date Deposited: 27 Dec 2005 02:00
Last Modified: 26 Apr 2022 08:34
URI: https://research.sabanciuniv.edu/id/eprint/1339

Actions (login required)

View Item
View Item