An Information Based Approach to Decentralized Multi-platform Sensor Management

摘要

This paper describes a decentralized low communication approach to multi-platform sensor management. The method is based on a physicomimetic relaxation to a joint information theoretic optimization, which inherits the benefits of information theoretic scheduling while maintaining tractability. The method uses only limited message passing, only neighboring nodes communicate, and each node makes its own sensor management decisions. We show by simulation that the method allows a network of sensor nodes to automatically self organize and perform a global task. In the model problem, a group of unmanned aerial vehicles (UAVs) hover above a ground surveillance region. An initially unknown number of moving ground targets inhabit the region. Each UAV is capable of making noisy measurements of the patch of ground directly below, which provide evidence as to the presence or absence of targets in that sub-region. The goal of the network is to determine the number of targets and their individual states (positions and velocities) in the entire surveillance region through repeated interrogation by the individual nodes. As the individual nodes can only see a small portion of the ground, they must move in a manner that is both responsive to measurements and coordinated with other nodes.