A sensor selection approach to maneuvering target tracking based on trajectory function of time

Changyi Liu, Kuangyu Di, Tiancheng Li*, Victor Elvira

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

In this paper, we propose a computationally efficient sensor selection approach for maneuvering target tracking using a sensor network with communication bandwidth constraints, given limited prior information on the target maneuvering models. We formulate the stochastic sensor selection problem as a linear programming problem which consists of two easily implementable steps. First, the Cramér–Rao lower bound corresponding to the sensor subset is derived as the objective function of the proposed sensor selection method based on a partially observable Markov decision process. Second, the target trajectory is modeled by a function of time to enable online target tracking which is free of the conventional, a priori Markov modeling of the target dynamics. We demonstrate the effectiveness of our method through several numerical examples.
Original languageEnglish
Article number72
Number of pages14
JournalEURASIP Journal on Advances in Signal Processing
Volume2022
DOIs
Publication statusPublished - 3 Sept 2022

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