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Device-free localization (DFL) is an emerging wireless network target localization technique that does not need to attach any electronic device with the target. It is remaining as a challenging research problem due to the weak wireless signals and the uncertain wireless communication environment. In this paper, a novel Gaussian Process (GP) based wireless propagation model is proposed to describe...
In this paper, consensus-based Kalman filtering is extended to deal with the problem of joint target tracking and sensor self-localization in a distributed wireless sensor network. The average weighted Kullback-Leibler divergence, which is a function of the unknown drift parameters, is employed as the cost to measure the discrepancy between the fused posterior distribution and the local distribution...
We propose a diffusion expectation-maximization algorithm with adaptive combiner for distributed estimation over sensor networks. Due to the spatial distribution of the nodes, variation of node profile across the network is a common phenomena in real applications. The unreliable nodes exist and provide inaccurate estimates, which may be caused by high levels of noise or malicious attacks. Instead...
Spatial outlier detection in wireless sensor network (WSN) can detect the objects whose non-spatial attributes are significantly different from their spatial neighbors, so as to ensure the reliability and accuracy of sensor data before decision-making process. The main drawback of existing spatial outlier detection algorithms is high user-dependency, which is not suitable for dynamic WSN data. This...
Device-free localization (DFL) is an emerging wireless localization technique where the target does not equip with any electronic tag for communicating with the localization system. It has been found numerous practical applications such as human health and medical care with the help of location detection and behavior analysis, intrusion detection, security safeguard, and emergency rescue. In the DFL...
In this paper, sparsity-promoting sensor selection algorithms for target tracking with quantized data are developed. We formulate sensor selection as an optimization problem that aims to strike a balance between estimation accuracy and the number of selected sensors. To cope with sensor selection problems in large-scale wireless sensor networks (WSNs), we propose a fast centralized optimization algorithm...
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