An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
Poster abstract: entropy-based sensor selection for localization
Proceedings of the 1st international conference on Embedded networked sensor systems
Collaborative in-network processing for target tracking
EURASIP Journal on Applied Signal Processing
Energy based acoustic source localization
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
On the error characteristics of multihop node localization in ad-hoc sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
IEEE Transactions on Signal Processing
| Hi-index | 0.00 |
In distributed sensor networks, the tradeoff between application performance and resource consumption is a fundamental issue. In this paper, we analyse the tradeoff in the context of localisation problems. In particular, the localisation performance is characterised using the Cramer-Rao lower bound which reflects the performance limit in the family of unbiased estimators. For a variety of distance-sensitive sensing models, the bound comes in closed-form. In view of the tradeoff, we design a circular incremental inclusion scheme for efficient sensor tasking and propose to use the theoretical Cramer-Rao lower bound as a guiding heuristic. Our results reveal that there is a performance limit for collaborative sensing, and the expansion of sensing group size incurs fast diminishing returns on performance. The study results in new insights and provides general guidelines for sensor tasking in practical applications.