Adaptive search for sparse targets with informative priors

ACT This works considers the problem of efficient energy allocation of resources in a continuous fashion in determining the location of targets in a sparse environment. We extend the work of Bashan [1] to analyze the use of non-uniform prior knowledge for the location of targets. We show that in the best-case scenario (i.e., when the known prior knowledge is also the underlying prior), then we can get significant gains (several dB) by using a two-level piecewise uniform prior over using the uniform prior that is assumed in [1]. Moreover, even when we have uncertainty in our prior knowledge, we show that we can always do at least as well as the uniform alternative in terms of worst-case and expected gains. In future work, we plan to extend our analysis to general piecewise uniform priors in order to develop multistage (i.e., greater than 2) adaptive energy allocation policies.

• Type: Conference
• Year: 2010
• Where: ICASSP
• Authors: Gregory Newstadt, Eran Bashan, Alfred O. Hero III
• Keywords: Energy Allocation, ICASSP 2010, Prior Knowledge, Signal Processing, Uniform Priors