Quality over quantity: Target identifiability in directional sensor networks

Existing algorithms for orienting sensors in directional sensor networks have primarily concerned themselves with the problem of maximizing the number of covered targets, assuming that target identification as a non-issue. Such an assumption however, does not hold true in all situations. In this paper, three heuristic algorithms for choosing active sensors and orienting them with the goal of balancing coverage and identifiability are presented. The first algorithm is parameterizable, allowing users to specify the desired level of trade-off between coverage and identifiability. The other two algorithms are not parameterizable, and are more suited for situations where coverage is preferred over identifiability. The performance of the algorithms are verified via simulations, and shown through simulations to confer increased target identifiability compared to algorithms originally designed to simply maximize the number of targets covered.