A comparative study on indoor localization based on RSSI measurement in wireless sensor network

This paper studies on the localization techniques using in wireless sensor network (WSN) for an indoor environment. We compare two main categories of localization techniques: range-based and fingerprinting-based techniques on a single experimental environment. The received signal strength indicator (RSSI) received at sensor nodes are used for all localization techniques. For the range-base techniques, the location estimation approach based on the lateration estimation and the min-max approach are employed. For the fingerprinting based techniques, two pattern matching approaches are used: one is the simple nearest neighbor algorithm and another one is the k-nearest-nearest neighbor algorithm. The experiments are conducted in a meeting room where is a small number of obstacles inside to evaluate the performance of each technique. The results demonstrate that the location estimation algorithm using lateration estimation gives the best accuracy and also less computational time compared to other techniques.