Bayesian approach to sensor fusion in a multi-sensor land mine detection system

被引：2

作者：

Erickson, D ^{[1
]}

Kacelenga, R ^{[1
]}

Palmer, D ^{[1
]}

机构：

[1] Gen Dynam Canada Ltd, Calgary, AB T2E 8P2, Canada

来源：

SENSOR FUSION: ARCHITECTURES, ALGORITHMS, AND APPLICATIONS VI | 2002年 / 4731卷

关键词：

landmine detection; Baye's rule; Bayesian inference; conditional probability; minimum metal detector; ground penetrating radar; forward-looking infrared; multi-sensor fusion;

D O I：

10.1117/12.458390

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the present study, the investigation by General Dynamics Canada, formerly Computing Devices Canada, into Bayesian Inference shows improved sensor fusion of multiple scanning sensors in the detection of buried anti-tank (AT) mines. This algorithm uses statistical data taken from trials and constructs conditional probabilities for individual sensors in order to better discern landmines.

引用

页码：248 / 258

页数：11

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