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| Content Provider | ACM Digital Library |
|---|---|
| Author | Yang, Yong Hou, Jennifer C. Shankar, Mallikarjun Chin, Jren-Chit Yau, David K. Y. Rao, Nageswara S. V. Iyengar, S. Sitharama Srivathsan, Srinivasagopalan |
| Abstract | Identification of a low-level point radiation source amidst background radiation is achieved by a network of radiation sensors using a two-step approach. Based on measurements from three sensors, the geometric difference triangulation 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 radiation sources to emulate high intensity ones that cannot be easily and safely handled in laboratory experiments. |
| Starting Page | 493 |
| Ending Page | 504 |
| Page Count | 12 |
| File Format | |
| ISBN | 9780769531571 |
| DOI | 10.1109/IPSN.2008.19 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2008-04-22 |
| Access Restriction | Subscribed |
| Subject Keyword | Point radiation source detection and localization sequential probability ratio test |
| Content Type | Text |
| Resource Type | Article |
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