Abstract
Target tracking is one of the very important applications of WSNs (wireless sensor networks). Traditionally, Kalman filter and its derivatives are some of the most popular algorithms in solving the signal tracking problem. In a WSNs tracking application, the target motion/state update dynamics might be linear or nonlinear depending on the specific scenario. The observation model might vary across the sampling interval. This paper compares the effectiveness, limitations and other related implementation issues in applying Kalman filter and extended Kalman filter to tackle target tracking problem in WSNs.
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