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Signal strength fluctuation is one of the major problems in a fingerprint-based localization system. To alleviate this problem, we propose a scrambling method to exploit temporal diversity and spatial dependency of collected signal samples. We present how to apply these properties to enhance the positioning accuracy of several existing schemes. Simulation studies and experimental results show that the scrambling method can greatly improve positioning accuracy, especially when the tracked object has some degree of mobility.
Context Awareness, Location-Based Service, Pervasive Computing, Sensor network, Indoor Positioning, Location Tracking.

Y. Tseng and S. Kuo, "A Scrambling Method for Fingerprint Positioning Based on Temporal Diversity and Spatial Dependency," in IEEE Transactions on Knowledge & Data Engineering, vol. 20, no. , pp. 678-684, 2007.
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