Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Numerical Methods Using MATLAB
Numerical Methods Using MATLAB
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
Cramer-Rao Bound Analysis of Quantized RSSI Based Localization in Wireless Sensor Networks
ICPADS '05 Proceedings of the 11th International Conference on Parallel and Distributed Systems - Workshops - Volume 02
Fundamentals of wireless communication
Fundamentals of wireless communication
MIMO Wireless Communications
Maximum likelihood methods for bearings-only target localization
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
Energy-based collaborative source localization using acoustic microsensor array
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
IEEE Transactions on Signal Processing
Target Location Estimation in Sensor Networks With Quantized Data
IEEE Transactions on Signal Processing
Channel aware decision fusion in wireless sensor networks
IEEE Transactions on Signal Processing
Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks
IEEE Transactions on Signal Processing
On Energy-Based Acoustic Source Localization for Sensor Networks
IEEE Transactions on Signal Processing
Fusion of censored decisions in wireless sensor networks
IEEE Transactions on Wireless Communications
Detection Performance Limits for Distributed Sensor Networks in the Presence of Nonideal Channels
IEEE Transactions on Wireless Communications
IEEE Transactions on Information Theory
Channel-optimized quantizers for decentralized detection in sensor networks
IEEE Transactions on Information Theory
Tracking in wireless sensor networks using particle filtering: physical layer considerations
IEEE Transactions on Signal Processing
Optimizing network lifetime for distributed tracking with wireless sensor networks
Proceedings of the 6th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks
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In this paper, we propose a new maximum-likelihood (ML) target localization approach which uses quantized sensor data as well as wireless channel statistics in a wireless sensor network. The novelty of our approach comes from the fact that statistics of imperfect wireless channels between sensors and the fusion center along with some physical layer design parameters are incorporated in the localization algorithm. We call this approach "channel-aware target localization." ML target location estimators are derived for different wireless channel models and receiver architectures. Furthermore, we derive the Cramér-Rao lower bounds (CRLBs) for our proposed channel-aware ML location estimators. Simulation results are presented to show that the performance of the channel-aware ML location estimators are quite close to their theoretical performance bounds even with relatively small number of sensors and their performance is superior compared to that of the channel-unaware ML estimators.