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

页码：187 / 193

页数：7

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