Improvement of the signal-to-noise ratio in static-mode down-looking synthetic aperture imaging ladar

Zhiyong Lu; Jianfeng Sun; Ning Zhang; Yu Zhou; Guangyu Cai; Liren Liu

doi:10.1117/12.2185902

4 September 2015 Improvement of the signal-to-noise ratio in static-mode down-looking synthetic aperture imaging ladar

Zhiyong Lu, Jianfeng Sun, Ning Zhang, Yu Zhou, Guangyu Cai, Liren Liu

Proceedings Volume 9617, Unconventional Imaging and Wavefront Sensing 2015; 96170K (2015) https://doi.org/10.1117/12.2185902
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

The static-mode down-looking synthetic aperture imaging ladar (SAIL) can keep the target and carrying-platform still during the collection process. Improvement of the signal-to-noise ratio in static-mode down-looking SAIL is investigated. The signal-to-noise ratio is improved by increasing scanning time and sampling rate in static-mode down-looking SAIL. In the experiment, the targets are reconstructed in different scanning time and different sampling rate. As the increasing of the scanning time and sampling rate, the reconstructed images become clearer. These techniques have a great potential for applications in extensive synthetic aperture imaging ladar fields.

Citation Download Citation

Zhiyong Lu, Jianfeng Sun, Ning Zhang, Yu Zhou, Guangyu Cai, and Liren Liu "Improvement of the signal-to-noise ratio in static-mode down-looking synthetic aperture imaging ladar", Proc. SPIE 9617, Unconventional Imaging and Wavefront Sensing 2015, 96170K (4 September 2015); https://doi.org/10.1117/12.2185902

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available