Techniques on Long-Range and High-Resolution Imaging Lidar

Xiaofeng, 金晓峰 Jin; Peng, 张鹏 Zhang; Chunhua, 刘春华 Liu; Jianfeng, 孙剑锋 Sun; Liren, 刘立人 Liu

doi:10.3788/lop50.050002

“…As aerospace technology thrives, the exploration of aerial and space targets has become a hot topic. LRT system can overcome the limitation of traditional lidar systems [4] and achieve high-quality imaging results of long-distance non-cooperative targets, such as space debris or satellites [5]. In recent years, progress has been made in the research of LRT systems.…”

Section: Introductionmentioning

confidence: 99%

Hybrid regularization method for LRT image reconstruction under incomplete projections

Guo,

Zhihan,

Wang

et al. 2024

Preprint

0

View full text Add to dashboard Cite

Lidar reflective tomography (LRT) system is able to achieve long-distance target detection and collect laser projection data for target reconstruction. In target detection with laser, the projection data is often incomplete or missing, where the traditional reconstruction algorithms are no longer effective. Therefore, this paper applies the regularization model to LRT image reconstruction and proposes a hybrid regularization method for higher LRT imaging performance, to prevent the over-fitting problem of the model and improve the speed and stability of the proposed method. Meanwhile, the edge and the structural characteristics of the reconstructed target with LRT is better enhanced by using the proposed hybrid regularization method. By conducting the LRT outfield experiment and using the collected LRT projection data, the validity of the proposed method in incomplete projection reconstruction is well proved.

show abstract

“…As aerospace technology thrives, the exploration of aerial and space targets has become a hot topic. LRT systems can overcome the limitation of traditional lidar systems [4] and achieve high-quality imaging results of long-distance noncooperative targets, such as space debris or satellites [5]. In recent years, progress has been made in the research of LRT systems.…”

Section: Introductionmentioning

confidence: 99%

Hybrid regularization method for LRT image reconstruction under incomplete projections

Guo,

Zhihan,

Jiang

et al. 2024

Preprint

0

View full text Add to dashboard Cite

Lidar reflective tomography (LRT) system is able to achieve long-distance target detection and collect laser projection data for target reconstruction. In target detection with laser, the projection data is often incomplete or missing, where the traditional reconstruction algorithms are no longer effective. Therefore, this paper applies the regularization model to LRT image reconstruction and proposes a hybrid regularization method for higher LRT imaging performance, to prevent the over-fitting problem of the model and improve the speed and stability of the proposed method. Meanwhile, the edge and the structural characteristics of the reconstructed target with LRT is better enhanced by using the proposed hybrid regularization method. By conducting the LRT outfield experiment and using the collected LRT projection data, the validity of the proposed method in incomplete projection reconstruction is well proved.

show abstract