Multi-sensor Target Tracking Using the Bernoulli Filter

被引：0

作者：

Qin, Yong ^{[1
]}

Ma, Hong ^{[1
]}

Cheng, Li ^{[1
,2
]}

Yu, De ^{[1
]}

Li, Yang ^{[1
]}

Zhou, Xueqin ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan 430074, Peoples R China

[2] Wuhan Inst Technol, Sch Elect & Informat Engn, Wuhan 430073, Peoples R China

来源：

PROCEEDINGS OF THE 2015 3RD INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND INFORMATION TECHNOLOGY APPLICATIONS | 2015年 / 35卷

关键词：

Bernoulli filter; Multi-sensor; Sequential Monte Carlo;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a novel multi-sensor Bernoulli filter (MSBF) based on the finite set statistics (FISST) for tracking a single target under the presence of detection uncertainty and clutter. The proposed algorithm is an extension of original Bernoulli filter in multi-sensor tracking. First, FISST is used to derive multi-sensor likelihood function of the MSBF, and then the sequential Monte Carlo (SMC) method is applied to implement the MSBF. Eventually, the simulation results are provided to demonstrate the effectiveness of the MSBF.

引用

页码：1399 / 1405

页数：7

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