Radio imaging allows to locate and track passive targets (i.e., not carrying electronic device) moving in an area monitored by a dense network of low-power and battery-operated wireless sensors. The technology is promising for a wide number of applications ranging from intrusion detection to emergency and rescue operations in critical areas. In this paper, a new approach is proposed where both the average and the variance of the fluctuations of the received signal strength (RSS) induced by the target movement over the links are jointly and optimally exploited for sensing the target location. A link-layer protocol is developed on top of an existing IEEE 802.15.4 compliant PHY/MAC layer to allow the wireless nodes to cooperatively exchange RSS measurements. A log-normal model is defined to relate these measurements to the target location. Grid-based Bayesian estimation is proposed for real-time mobile positioning. The proposed system is validated by an indoor experimental study that analyzes the problem of model calibration and compares the performance of different localization algorithms.
Radio Imaging by Cooperative Wireless Network: Localization Algorithms and Experiments
SAVAZZI, STEFANO;NICOLI, MONICA BARBARA;
2012-01-01
Abstract
Radio imaging allows to locate and track passive targets (i.e., not carrying electronic device) moving in an area monitored by a dense network of low-power and battery-operated wireless sensors. The technology is promising for a wide number of applications ranging from intrusion detection to emergency and rescue operations in critical areas. In this paper, a new approach is proposed where both the average and the variance of the fluctuations of the received signal strength (RSS) induced by the target movement over the links are jointly and optimally exploited for sensing the target location. A link-layer protocol is developed on top of an existing IEEE 802.15.4 compliant PHY/MAC layer to allow the wireless nodes to cooperatively exchange RSS measurements. A log-normal model is defined to relate these measurements to the target location. Grid-based Bayesian estimation is proposed for real-time mobile positioning. The proposed system is validated by an indoor experimental study that analyzes the problem of model calibration and compares the performance of different localization algorithms.File | Dimensione | Formato | |
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