Landmark-based position and movement detection of wireless sensor network devices

The demand for reliable indoor positioning of mobile devices is wide and the computing and communication hardware are evolving rapidly. Thus, it is meaningful to consider a spectrum of techniques that reflect different constraints and tradeoffs of hardware investment, computational complexity, set-up cost, and positioning accuracy. The present paper strives to achieve high accuracy with low hardware investment and moderate set-up cost, but with somewhat sophisticated computations. We not only describe a successful positioning system, but also suggest a set of formal techniques that proved to work well in the real setting, and can be implemented using standard wireless sensor network hardware. The overall philosophy of utilizing the full distribution information of signal measurements at each location (proved implementable after careful algorithm design) distinguishes sharply from most existing works. Compared with the earlier work within our group, the present paper introduces new elements such as profiling the signal measurement distributions over the coverage area using a special interpolation technique; a two-tier tracking scheme that improves the efficiency of localization (in the commonly used sense) by adding movement detection (lower energy cost); and the joint clusterhead placement optimization for both localization and movement detection. Experimentally, our system achieved an accuracy equivalent to 95% < 5 meters and 87% < 3 meters, which should be considered a high-quality result compared to well-known contemporary systems that use similar low-cost hardware.