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
收藏
页码：248 / 258
页数：11
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