Distributed state representation for tracking problems in sensor networks

This paper investigates the problem of designing decentralized representations to support monitoring and inferences in sensor networks. State-space models of physical phenomena such as those arising from tracking multiple interacting targets, while commonly used in signal processing and control, suffer from the curse of dimensionality as the number of phenomena of interest increases. Furthermore, mapping an inference algorithm onto a distributed sensor network must appropriately allocate scarce sensing and communication resources. We address the state-space explosion problem by developing a distributed state-space model that switches between factored and joint state spaces as appropriate. We decollaborative group abstraction as a mechanism to effectively support the information flow within and across subspaces of the state-space model, which can be efficiently supported in a communication-constrained network. The approach has been implemented and demonstrated in a simulation of tra...

• Type: Conference
• Year: 2004
• Where: IPSN
• Authors: Juan Liu, Maurice Chu, Jie Liu, Jim Reich, Feng Zhao
• Keywords: IPSN 2004, Multiple Interacting Targets, Sensor Network, Sensor Networks, State-space Model