Range-based localization with area verification for sparse distributed Wireless Sensor Networks

In centralized range-based localization techniques, sufficiency of inter-node range information collected by the base station strongly affects node position estimation results. In an evenly distributed network, which every node can accurately measure ranges each other, it is easy to calculate every node position using range-based, since there be only one possibility of local minimum. Unfortunately, in real flooded nodes deployment WSNs, it is difficult to find the uniformity. The density of network will be varying from part to part. Nodes sparse in low density part will potentially have insufficient or even none range information. In such condition, localization program will find more than one possibilities of local minimum, the range based localization program will have difficulties to resolve nodes positions, and further, it also influences entire nodes localization. Therefore, this research proposed a new approach in overcoming sparse condition by utilizing non-range information as tool to verify whether a local minimum occurred is correct. This technique resulted in a more successful localization in sparse distributed WSNs.