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Energy based detection measures sensor received signal strength (RSS) transmitted from a target. In this paper, we propose a new approach for estimating a moving target trajectory over a sensor field via energy based detections as an alternative to trilateration positioning or nonlinear estimation. In 2D case, possible target locations described by a RSS ratio from two sensors are approximated using...
Target tracking from incomplete measurements of distinct sensors in a sensor network is a task of data fusion, present in a lot of applications. Difficulties in tracking using extended Kalman filters lead to unstable behavior, mainly caused by difficult initialization. Instead of using numerical batch-estimators, we offer an analytical approach to initialize the filter from a minimum number of observations...
It is a critical consideration to collect and fuse sensed information in an energy efficient manner for obtaining a long lifetime of the sensor network. Based on our findings that the conventional methods of direct transmission, shortest path routing, and Dempster-Shafer tool may not be optimal for data fusion of sensor networks, we propose LEECF (low-energy event centric fusion), a event-centric-based...
In the condition of sensor network (SN), to associate local tracks front multiple sensors is a complex task, due to the combination explosion caused by the increasing number of sensors and targets. A new graphical models-based technique for track association is proposed in this paper to deal with the problem. Firstly, by means of the sparse structure inherent in multisensor multitarget tracking scenario,...
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