Spatial Registration Based on Weighted Fusion of Multiple Significant Targets

Yajun Zeng; Ruoshui Li; Likang Zhu; Shaoming Wei; Jun Wang; Hongyu Yi

doi:10.1109/Radar53847.2021.10028345

Spatial Registration Based on Weighted Fusion of Multiple Significant Targets

Yajun Zeng
, Ruoshui Li
, Likang Zhu
, Shaoming Wei^*
, Jun Wang
, Hongyu Yi

^*Corresponding author for this work

School of Electronic and Information Engineering

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Spatial registration algorithm deeply relies on the significant target. During the whole process of spatial registration, most registration algorithm only select one significant target and the sensor bias remains constant. However, in actual scene, the single significant target cannot be stably detected by all sensors, and the sensor bias will drift over time. Therefore, in order to accurately estimate the sensor bias in real-time, this paper proposes a registration method based on the weighted fusion of multiple significant targets. By fusing the spatial registration results of multiple significant targets, the robustness and accuracy of the registration algorithm are enhanced. Simulation results verify the effectiveness of the proposed algorithm.

Original language	English
Title of host publication	2021 CIE International Conference on Radar, Radar 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2099-2102
Number of pages	4
ISBN (Electronic)	9781665498142
DOIs	https://doi.org/10.1109/Radar53847.2021.10028345
State	Published - 2021
Event	2021 CIE International Conference on Radar, Radar 2021 - Haikou, Hainan, China Duration: 15 Dec 2021 → 19 Dec 2021

Publication series

Name	Proceedings of the IEEE Radar Conference
Volume	2021-December
ISSN (Print)	1097-5764
ISSN (Electronic)	2375-5318

Conference

Conference	2021 CIE International Conference on Radar, Radar 2021
Country/Territory	China
City	Haikou, Hainan
Period	15/12/21 → 19/12/21

Keywords

Sensor bias
Significant target
Spatial registration
Weightedfusion

Access to Document

10.1109/Radar53847.2021.10028345

Cite this

Zeng, Y., Li, R., Zhu, L., Wei, S., Wang, J., & Yi, H. (2021). Spatial Registration Based on Weighted Fusion of Multiple Significant Targets. In 2021 CIE International Conference on Radar, Radar 2021 (pp. 2099-2102). (Proceedings of the IEEE Radar Conference; Vol. 2021-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/Radar53847.2021.10028345

@inproceedings{fcfc020e6aed40d2bffdf780189778f0,

title = "Spatial Registration Based on Weighted Fusion of Multiple Significant Targets",

abstract = "Spatial registration algorithm deeply relies on the significant target. During the whole process of spatial registration, most registration algorithm only select one significant target and the sensor bias remains constant. However, in actual scene, the single significant target cannot be stably detected by all sensors, and the sensor bias will drift over time. Therefore, in order to accurately estimate the sensor bias in real-time, this paper proposes a registration method based on the weighted fusion of multiple significant targets. By fusing the spatial registration results of multiple significant targets, the robustness and accuracy of the registration algorithm are enhanced. Simulation results verify the effectiveness of the proposed algorithm.",

keywords = "Sensor bias, Significant target, Spatial registration, Weightedfusion",

author = "Yajun Zeng and Ruoshui Li and Likang Zhu and Shaoming Wei and Jun Wang and Hongyu Yi",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 CIE International Conference on Radar, Radar 2021 ; Conference date: 15-12-2021 Through 19-12-2021",

year = "2021",

doi = "10.1109/Radar53847.2021.10028345",

language = "英语",

series = "Proceedings of the IEEE Radar Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2099--2102",

booktitle = "2021 CIE International Conference on Radar, Radar 2021",

address = "美国",

}

Zeng, Y, Li, R, Zhu, L, Wei, S , Wang, J & Yi, H 2021, Spatial Registration Based on Weighted Fusion of Multiple Significant Targets. in 2021 CIE International Conference on Radar, Radar 2021. Proceedings of the IEEE Radar Conference, vol. 2021-December, Institute of Electrical and Electronics Engineers Inc., pp. 2099-2102, 2021 CIE International Conference on Radar, Radar 2021, Haikou, Hainan, China, 15/12/21. https://doi.org/10.1109/Radar53847.2021.10028345

Spatial Registration Based on Weighted Fusion of Multiple Significant Targets. / Zeng, Yajun; Li, Ruoshui; Zhu, Likang et al.
2021 CIE International Conference on Radar, Radar 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 2099-2102 (Proceedings of the IEEE Radar Conference; Vol. 2021-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Spatial Registration Based on Weighted Fusion of Multiple Significant Targets

AU - Zeng, Yajun

AU - Li, Ruoshui

AU - Zhu, Likang

AU - Wei, Shaoming

AU - Wang, Jun

AU - Yi, Hongyu

PY - 2021

Y1 - 2021

N2 - Spatial registration algorithm deeply relies on the significant target. During the whole process of spatial registration, most registration algorithm only select one significant target and the sensor bias remains constant. However, in actual scene, the single significant target cannot be stably detected by all sensors, and the sensor bias will drift over time. Therefore, in order to accurately estimate the sensor bias in real-time, this paper proposes a registration method based on the weighted fusion of multiple significant targets. By fusing the spatial registration results of multiple significant targets, the robustness and accuracy of the registration algorithm are enhanced. Simulation results verify the effectiveness of the proposed algorithm.

AB - Spatial registration algorithm deeply relies on the significant target. During the whole process of spatial registration, most registration algorithm only select one significant target and the sensor bias remains constant. However, in actual scene, the single significant target cannot be stably detected by all sensors, and the sensor bias will drift over time. Therefore, in order to accurately estimate the sensor bias in real-time, this paper proposes a registration method based on the weighted fusion of multiple significant targets. By fusing the spatial registration results of multiple significant targets, the robustness and accuracy of the registration algorithm are enhanced. Simulation results verify the effectiveness of the proposed algorithm.

KW - Sensor bias

KW - Significant target

KW - Spatial registration

KW - Weightedfusion

UR - https://www.scopus.com/pages/publications/85181126625

U2 - 10.1109/Radar53847.2021.10028345

DO - 10.1109/Radar53847.2021.10028345

M3 - 会议稿件

AN - SCOPUS:85181126625

T3 - Proceedings of the IEEE Radar Conference

SP - 2099

EP - 2102

BT - 2021 CIE International Conference on Radar, Radar 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 CIE International Conference on Radar, Radar 2021

Y2 - 15 December 2021 through 19 December 2021

ER -

Spatial Registration Based on Weighted Fusion of Multiple Significant Targets

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