Localization Using Extended Kalman Filters in Wireless Sensor Networks

Abstract

Localization arises repeatedly in many location-aware applications such as navigation, autonomous robotic movement, and asset tracking. Analytical localization methods include triangulation and trilateration. Triangulation uses angles, distances, and trigonometric relationships to locate an object. Trilateration, on the other hand, uses only distance measurements to identify the position of the target. Figure Using three reference points S 1 , S 2 , and S 3 with known locations and distances d 1 , d 2 , and d 3 to the target object, the object can be located at the intersecting point of the three circles. However, in a dynamic system where distance measurements are noisy and fluctuate, the task of localizing becomes difficult. This can be seen in Figure In this case, rather than the object being located at a single point at the intersection of the circles as in Figure