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Numerous applications require accurate personal navigation for environments where neither GPS signals nor infrastructure beacons, such as WiFi, are available. Inertial navigation using low-cost sensors suffers from the noisy readings which leads to drifting errors over time. In this paper, we introduce a novel inertial navigation approach ProbIN using Bayesian probabilistic framework. ProbIN models...
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