Evaluation of Self-Positioning Algorithms for Time-of-Flight based Localization
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Self-localization systems based on the Time-of-Flight (ToF) of radio signals are highly susceptible to noise and their performance therefore heavily rely on the design and parametrization of robust algorithms. In this work, we study the noise sources of GPS and WiFi ToF ranging techniques and compare the performance of different self-positioning algorithms at a mobile node using those ranges. Our results show that the localization error varies greatly depending on the ranging technology, algorithm selection, and appropriate tuning of the algorithms. We characterize the localization error using real-world measurements and different parameter settings to provide guidance for the design of robust location estimators in realistic settings.