This work compares the performance of indoor positioning systems suitable forlow power wireless sensor networks. The research goal is to study positioningtechniques that are compatible with real-time positioning in wireless sensornetworks, having low-power and low complexity as requirements. Map matching,approximate positioning (weighted centroid) and exact positioning algorithms(least squares) were tested and compared in a small predefined indoorenvironment. We found that, for our test scenario, weighted centroid algorithmsprovide better results than map matching. Least squares proved to be completelyunreliable when using distances obtained by the one-slope propagation model.Major improvements in the positioning error were found when body influencewas removed from the test scenario. The results show that the positioning errorcan be improved if the body effect in received signal strength is accounted for inthe algorithms.
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