An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Dynamic fine-grained localization in Ad-Hoc networks of sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
iTPS: an improved location discovery scheme for sensor networks with long-range beacons
Journal of Parallel and Distributed Computing
Identification of Low-Level Point Radiation Sources Using a Sensor Network
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Accurate localization of low-level radioactive source under noise and measurement errors
Proceedings of the 6th ACM conference on Embedded network sensor systems
Fault tolerant target tracking in sensor networks
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
A computational geometry method for localization using differences of distances
ACM Transactions on Sensor Networks (TOSN)
Least squares estimation techniques for position tracking of radioactive sources
Automatica (Journal of IFAC)
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
| Hi-index | 0.00 |
Identification of a low-level point radioactive source amidst background radiation is achieved by a network of radiation sensors using a two-step approach. Based on measurements from three or more sensors, a geometric difference triangulation method or an N-sensor localization method is used to estimate the location and strength of the source. Then a sequential probability ratio test based on current measurements and estimated parameters is employed to finally decide: (1) the presence of a source with the estimated parameters, or (2) the absence of the source, or (3) the insufficiency of measurements to make a decision. This method achieves specified levels of false alarm and missed detection probabilities, while ensuring a close-to-minimal number of measurements for reaching a decision. This method minimizes the ghost-source problem of current estimation methods, and achieves a lower false alarm rate compared with current detection methods. This method is tested and demonstrated using: (1) simulations, and (2) a test-bed that utilizes the scaling properties of point radioactive sources to emulate high intensity ones that cannot be easily and safely handled in laboratory experiments.