Sensor selection based on maximum entropy fuzzy clustering for target tracking in large‐scale sensor networks

2017 ◽  
Vol 11 (5) ◽  
pp. 613-621 ◽  
Author(s):  
Junjun Guo ◽  
Xianghui Yuan ◽  
Chongzhao Han
Keyword(s):  
Sensor Networks ◽  
Target Tracking ◽  
Maximum Entropy ◽  
Fuzzy Clustering ◽  
Large Scale ◽  
Sensor Selection

scholarly journals Sensor Selection for Decentralized Large-Scale Multi-Target Tracking Network

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4115 ◽  
Author(s):  
Feng Lian ◽  
Liming Hou ◽  
Bo Wei ◽  
Chongzhao Han
Keyword(s):  
Target Tracking ◽  
Large Scale ◽  
Sequential Monte Carlo ◽  
Signal To Noise Ratio ◽  
Computational Cost ◽  
Gaussian Mixture ◽  
Descent Method ◽  
Sensor Selection ◽  
Multi Target Tracking ◽  
Finite Set

A new optimization algorithm of sensor selection is proposed in this paper for decentralized large-scale multi-target tracking (MTT) network within a labeled random finite set (RFS) framework. The method is performed based on a marginalized δ-generalized labeled multi-Bernoulli RFS. The rule of weighted Kullback-Leibler average (KLA) is used to fuse local multi-target densities. A new metric, named as the label assignment (LA) metric, is proposed to measure the distance for two labeled sets. The lower bound of LA metric based mean square error between the labeled multi-target state set and its estimate is taken as the optimized objective function of sensor selection. The proposed bound is obtained by the information inequality to RFS measurement. Then, we present the sequential Monte Carlo and Gaussian mixture implementations for the bound. Another advantage of the bound is that it provides a basis for setting the weights of KLA. The coordinate descent method is proposed to compromise the computational cost of sensor selection and the accuracy of MTT. Simulations verify the effectiveness of our method under different signal-to- noise ratio scenarios.

SENSOR SELECTION FOR TARGET TRACKING IN SENSOR NETWORKS

2009 ◽  
Vol 95 ◽  
pp. 267-282 ◽  
Author(s):  
Hong-Qing Liu ◽  
Hing-Cheung So ◽  
Kenneth Wing Kin Lui ◽  
Frankie Kit Wing Chan
Keyword(s):  
Sensor Networks ◽  
Target Tracking ◽  
Sensor Selection ◽  
Selection For
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