M.S. (Master of Science)
Department of Electrical Engineering
This thesis discusses the optimization of distributed sensor systems to maximizedetection of an emitter at an unknown location. More specifically, this thesis discusses the creation of an algorithm that seeks to optimize the spatial positions of sensors in a distributed sensor array in order to maximize the chance of detecting an emitter even if it were to occur in the worst possible location for detection. Two versions of this algorithm are discussed. The first algorithm considers a fusion rule that detects the emitter based on the sum of all sensor measurements. The second algorithm considers the scan statistic fusion rule. Both versions implement a local search algorithm designed by Torczon. Both versions of the algorithm showed that it is possible to improve the worst-case detection of sensor detection systems over a grid pattern. In the conditions tested, the worst-case detection increased by up to 23%, or an increase factor of 2.11, under different conditions when compared with a standard grid pattern. Testing proved that as long as the sensor array is not too large, these algorithms are able to improve the worst-case detection of sensor systems within a reasonable amount of time.
Vegrzyn, Ryan Taylor, "Optimizing Sensor Locations to Improve The Worst Case Detection Performance of Sensor Detection Systems" (2021). Graduate Research Theses & Dissertations. 7753.
Northern Illinois University
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