利用Chernoff信息对高斯混合模型进行鲁棒、分布式融合的实证研究

2006 9th International Conference on Information Fusion Pub Date : 2006-07-10 DOI:10.1109/ICIF.2006.301755

S. Julier

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引用次数: 111

摘要

本文研究了利用Chernoff信息开发高斯混合模型分布式融合算法的问题。我们推导了一阶近似，并表明，在传感器节点仅配备距离或方位传感器的分布式跟踪问题中，它产生一致的估计

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An Empirical Study into the Use of Chernoff Information for Robust, Distributed Fusion of Gaussian Mixture Models

This paper considers the problem of developing algorithms for the distributed fusion of Gaussian mixture models through the use of Chernoff information. We derive a first order approximation and show that, in a distributed tracking problem in which sensor nodes are equipped with only range-only or bearing-only sensors, it yields consistent estimates

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2006 9th International Conference on Information Fusion

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