In this paper, we consider a sensor network with limited sensing range and present a sensor selection algorithm for multi-target tracking problem. The proposed algorithm is based on the multi-Bernoulli filtering and a collection of sub-selection problems for individual target. A sub-selection problem for each target is investigated under the framework of partially observed Markov decision process. Each sub-selection problem is solved using a combination of information theoretic method and limited sensing range. Numerical studies validate the effectiveness of our method for multi-target tracking scenario in a sensor network.
Kim, D.Y. and Ma, L. and Jeon, M. 2015. Multi-Bernoulli filter based sensor selection with limited sensing range for multi-target tracking, in Proceedings of the International Conference on Control, Automation and Information Sciences (ICCAIS), Oct 29-31 2015, pp. 74-79. Changshu, China: IEEE.