Abstract
This chapter studies the problem of sensor selection for target tracking in a wireless sensor network from an information-theoretic perspective. To balance the computation cost and tracking performance, a sensor selection metric based on mutual information (MI) upper bound is proposed. The performance of the proposed metric is compared with a Fisher Information and a MI-based sensor selection metric. Fisher information-based sensor selection is simple but achieves lower computational complexity, while MI-based sensor selection provides better tracking accuracy but is computationally expensive. Furthermore, a multiobjective optimization framework is considered for information fusion to reveal trade-offs between the number of active sensors and tracking performance.
Original language | English (US) |
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Title of host publication | Information-Theoretic Radar Signal Processing |
Publisher | Wiley |
Pages | 217-249 |
Number of pages | 33 |
ISBN (Electronic) | 9781394216956 |
ISBN (Print) | 9781394216925 |
DOIs | |
State | Published - Jan 1 2024 |
Keywords
- Fisher information
- information fusion
- information theory
- multiobjective optimization
- mutual information
- sensor selection
- target tracking
ASJC Scopus subject areas
- General Engineering
- General Computer Science