Comparison of dv-hop based indoor positioning methods in wireless sensor networks and new approach with K-means plus plus clustering method

Abstract

With the great need for indoor positioning technology, new techniques have been searched for, and studies are being carried out on methods that can achieve the success of GPS (Global Positioning System) outdoor positioning. However, due to the objects and architectural structure of the interior, it is difficult to break down the signals and give the correct results to this method. Many methods have been tried and appropriate solutions are being sought to overcome this problem. A wireless sensor network is one of the technologies used for this. When positioning in sensor networks, anchor nodes that have their own position information are used, and their features such as power, arrival time, arrival angle and how many different nodes are used while the signal is transmitted can be used for positioning. One of these methods, Dv-hop method, has been studied in this study and it has been compared with different methods in terms of performance. It has been observed that when this comparison is made, it is necessary to use an appropriate clustering method to create an appropriate topology when node points distributed around the center facilitate transmission. At this point k means ++ clustering method was proposed and it was seen that the accuracy rate could be increased up to 50% when probing.