Linfang Feng

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Maneuvering target tracking is an important application in wireless sensor network (WSN). Usually, Kalman filter (KF) or extended Kalman filter (EKF) is used to predict and estimate target states. However, when a target has high maneuverability, KF or EKF always does not work well. In this paper, we employ distributed interactive multiple model (IMM) filter(More)
An energy-balanced multiple-sensor collaborative scheduling is proposed for maneuvering target tracking in wireless sensor networks (WSNs). According to the position of the maneuvering target, some sensor nodes in WSNs are awakened to form a sensor cluster for target tracking collaboratively. In the cluster, the cluster head node is selected to implement(More)
This paper is concerned with the filtering problem for both discrete-time stochastic linear (DTSL) systems and discrete-time stochastic nonlinear (DTSN) systems. In DTSL systems, an linear optimal filter with multiple packet losses is designed based on the orthogonal principle analysis approach over unreliable wireless sensor networks (WSNs), and the(More)
Limited resource allocation and scheduling are important problems in distributed wireless sensor networks (WSNs). Saving energy and real-time performance deserve research for low-cost sensor nodes in the target tracking application. In this paper, we propose a new dynamic-group idea and apply it to our scheduling scheme. An Extended Kalman Filter (EKF) is(More)
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