摘要翻译：
本文定义并实现了一种非贝叶斯融合规则，用于将局部（非线性）滤波器估计的概率密度结合起来，用于被动传感器跟踪运动目标。该规则是对DSmT框架中最近发展起来的、有效的比例冲突再分配规则no.5(PCR5)的严格概率范式的限制，用于融合基本信念分配。定义了概率PCR5(p-PCR5)的抽样方法。结果表明，p-PCR5对错误建模具有较强的鲁棒性，并能在保持局部密度模式的同时尽可能地保留各密度固有的整体信息进行组合。特别地，p-PCR5能够在融合后保持多个假说/模式，当假说的偏差太远时。在一个简单的分布式非线性滤波应用实例上，对新的p-PCR5规则进行了测试，以显示这种方法对未来发展的兴趣。通过基本粒子滤波技术实现了非线性分布式滤波器。仿真结果表明，这种基于P-PCR5的滤波器即使在初始化模型和真实电影模型不一致的情况下也能跟踪目标。
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英文标题：
《Application of probabilistic PCR5 Fusion Rule for Multisensor Target
  Tracking》
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作者：
Alois Kirchner, Frederic Dambreville (DGA/CTA/DT/GIP), Francis Celeste
  (DGA/CTA/DT/GIP), Jean Dezert, Florentin Smarandache
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最新提交年份：
2007
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分类信息：

一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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英文摘要：
  This paper defines and implements a non-Bayesian fusion rule for combining densities of probabilities estimated by local (non-linear) filters for tracking a moving target by passive sensors. This rule is the restriction to a strict probabilistic paradigm of the recent and efficient Proportional Conflict Redistribution rule no 5 (PCR5) developed in the DSmT framework for fusing basic belief assignments. A sampling method for probabilistic PCR5 (p-PCR5) is defined. It is shown that p-PCR5 is more robust to an erroneous modeling and allows to keep the modes of local densities and preserve as much as possible the whole information inherent to each densities to combine. In particular, p-PCR5 is able of maintaining multiple hypotheses/modes after fusion, when the hypotheses are too distant in regards to their deviations. This new p-PCR5 rule has been tested on a simple example of distributed non-linear filtering application to show the interest of such approach for future developments. The non-linear distributed filter is implemented through a basic particles filtering technique. The results obtained in our simulations show the ability of this p-PCR5-based filter to track the target even when the models are not well consistent in regards to the initialization and real cinematic.
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PDF链接：
https://arxiv.org/pdf/707.3013