Kriangkrai Maneerat
ABSTRACT
One of challenging problems for indoor wireless multi-floor positioning systems is a presence of Reference Node (RN) failures, which causes the missing of the values of Received Signal Strength (RSS) during the online positioning phase of the fingerprinting technique. This leads to performance degradation in terms of floor accuracy which affects other localization procedures. This paper presents a robust floor determination algorithm called Robust Confidence Interval Sum-RSS (RCIS), which can accurately determine the floor where mobile objects located and can work under either the fault-free scenario or the RN-failure scenarios. The proposed fault tolerance floor algorithm is based on the confidence interval of the summation of the strongest RSS obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSNs) during the online phase. The performance of the proposed algorithm is compared with those of different floor determination algorithms in literature. The experimental results show that the proposed robust floor determination algorithm outperformed the other floor algorithms and can achieve the highest percentage of floor determination accuracy in all tested scenarios. Specifically, the proposed algorithm can achieve 100% correct floor determination under the scenario in which 40% of RNs failed.
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Digital Library
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- Floor Determination Algorithm with Node Failure Consideration for Indoor Positioning Systems
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