Wireless positioning using ellipsoidal constraints

Indoor location-based positioning systems have attracted notable interest during recent years for a wide range of personal and commercial applications. As is well known, the GPS systems does not allow for accurate positioning indoors, resulting in the development of various forms of indoor positioning techniques, mostly being based on radio frequency measurements. In this paper, we examine a novel way to reduce the positioning error by using the notion of separating ellipsoids in the context of received signal strength (RSS) fingerprinting. To avoid excessive computational complexity, the algorithm is paired with the A∗ algorithm, exploiting mapping information of the building of interest, to take into account obstacles such as walls. The proposed algorithm is evaluated on RSS measurements made in a shopping mall, and found to offer an improved positioning accuracy as compared to the Gaussian kernel approach.