Abstract
This paper mainly studied the mobile node localization and tracking in Wireless Sensor Networks (WSNs). Monte Carlo Localization algorithm (MCL) is widely for mobile node localization and tracking. However, MCL doesn’t consider the influence of different anchor nodes. Thus, we proposed a binary-detection Monte Carlo Localization algorithm (BD MCL), which combines binary-detection with MCL. Our algorithm mainly uses the time of target detection as the node weights in sampling process to enhance the influence of nearer anchor nodes. Simulations show that this new algorithm exhibits better performance than traditional MCL with regards to motion forecast and localization precision.
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