Distributed energy-efficient target tracking with binary sensor networks
ACM Transactions on Sensor Networks (TOSN)
Distributed target tracking with directional binary sensor networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Robust target tracking with quantized proximity sensors
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
Adaptive quantized target tracking in wireless sensor networks
Wireless Networks
Genetic Algorithm-based Adaptive Optimization for Target Tracking in Wireless Sensor Networks
Journal of Signal Processing Systems
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Target tracking in wireless sensor networks (WSN) has brought up new practical problems. The limited energy supply and bandwidth of WSN have put stringent constraints on the complexity and inter-node information exchange of the tracking algorithm. In this paper, we propose a binary variational algorithm outperforming existing target tracking algorithms such as Kalman and Particle filtering. The variational formulation allows an implicit compression of the exchanged statistics between leader nodes, enabling thus a distributed decision-making. Its binary extension further reduces the resource consumption by locally exchanging only few bits.