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POMDP multi-armed bandit formulation for energy minimization in sensor networks

In network centric warfare, sensor platforms with active sensing equipment such as radars can betray their existence, by emitting energy that can be intercepted by enemy surveillance sensors thereby increasing the vulnerability of the entire combat system. To achieve the important tactical requirement of low probability of intercept (LPI), requires dynamically controlling the emission energy of sensors. In this paper, we propose computationally efficient dynamic emission control and management algorithms for multiple networked heterogenous sensors. By formulating the problem as a partially observed Markov decision process (POMDP) with an on-going multi-armed bandit structure, near optimal sensor management algorithms are developed for controlling the active sensor emission to minimize the threat.