Sensing Method for Two-Target Detection in Time-Constrained Vector Poisson Channel

TL;DR

This paper investigates optimal sensing strategies for two Poisson sources with known rates, focusing on how to allocate observation time between individual and joint sensing to maximize information or detection probability.

Contribution

It introduces a sensor scheduling framework for two-target detection in a Poisson channel, optimizing time allocation based on mutual information and detection probability.

Findings

Optimal time allocation varies with the chosen metric.

Results show similar but not identical scheduling strategies under different optimization criteria.

Computational results demonstrate the effectiveness of the proposed approach.

Abstract

It is an experimental design problem in which there are two Poisson sources with two possible and known rates, and one counter. Through a switch, the counter can observe the sources individually or the counts can be combined so that the counter observes the sum of the two. The sensor scheduling problem is to determine an optimal proportion of the available time to be allocated toward individual and joint sensing, under a total time constraint. Two different metrics are used for optimization: mutual information between the sources and the observed counts, and probability of detection for the associated source detection problem. Our results, which are primarily computational, indicate similar but not identical results under the two cost functions.