Combining Determinism and Intuition through Univariate Decision Strategies for Target Detection from Multi-sensors
Overview & Synopsis
In many surveillance systems, an operator will have to make a decision on whether a target is present or not from the outputs of a sensor. Here, we assume that such an operator has at his or her disposal two sensors to give him or her more confidence in his decision-making process. In addition, we propose several univariate decision strategies which combine sensor characteristics, target probabilities and reward schemes together with deterministic and intuitive operator decision-making parameters. Further, using Chebyshev's inequality we develop a method for selecting the most robust strategy that mitigates poor performance. We illustrate through examples how different strategies will be more advantageous over others depending on the reward scheme and sensor parameters.
hal.science)
← / → for pages • + / - for zoom • 0 to fit width
Powered by Mozilla PDF.js v3.11
Document Information
| Document Title | Combining Determinism and Intuition through Univariate Decision Strategies for Target Detection from Multi-sensors |
|---|---|
| Author / Organization | Edwin El-Mahassni |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2010 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-223366 |
| Original Source Link | Visit Source Page on hal.science » |