Multi-sensor data fusion between radio tomographic imaging and noise radar

被引：3
|
作者：
Vergara, Christopher [1 ]
Martin, Richard K. [2 ]
Collins, Peter J. [2 ]
Lievsay, James R. [2 ]
机构：
[1] Australian Def Force, Royal Australian Air Force, Canberra, ACT, Australia
[2] Air Force Inst Technol, Dept Elect & Comp Engn, Wright Patterson AFB, OH USA
来源：
IET RADAR SONAR AND NAVIGATION | 2020年 / 14卷 / 02期
关键词：
sensor fusion; surveillance; radar imaging; image resolution; noise radar communities; multisensor data fusion; radio tomographic imaging; Tikhonov regularisation; target centroid location; target pixel dispersion; ideal solution comparison; disparate sensor technologies; TRACKING;
D O I：
10.1049/iet-rsn.2019.0092
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Radio tomographic imaging and noise radar are two proven surveillance technologies. The novelty of fusing data from radio tomographic imaging and noise radar is achieved with the derivation of a fusion technique utilising Tikhonov regularisation. Analysing the results of the Tikhonov influenced techniques reveals an average 43-47% error decrease in target centroid location, a 13-19% size decreases in target pixel dispersion and a 6-41% improvement in an ideal solution comparison. Results provide the radio tomographic imaging and noise radar communities a proof of concept for the fusion of data from two disparate sensor technologies.
引用
收藏
页码：187 / 193
页数：7
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