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Sensor relocation for improved target tracking

Sensor relocation for improved target tracking

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In many practical scenarios, targets tend to have certain mobility trends such as following a traverseable terrain, having a common starting/destination locations, or moving in a region with abundant resources. This work is interested in exploring the possible gain from sensor relocation in improving the localisation accuracy of targets that follow mobility trends similar to those previously observed. This objective is tackled using a three-phase approach. In the first phase, the wireless sensor network tracks the targets based on the initial deployment. The second phase uses the location estimates from phase 1 to form a region of interest (ROI). The last phase carries out the sensor relocation to the ROI. Two fitness functions are explored for optimising sensors’ locations in the ROI, namely geometric dilution of precision and K-coverage. K-coverage offered the best performance especially for sensors with a short-to-medium detection range. The uniform random relocation offered a comparable performance with a relatively low computational complexity. Results also revealed the degradation in coverage rate due to relocating sensors to the ROI, and how optimising sensor locations outside the ROI can help in mending coverage holes.

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