Maximum projection and velocity estimation algorithm for small moving target detection in space surveillance

Dalei Yao; Desheng Wen; Jianru Xue; Zhi Chen; Yan Wen; Baotan Jiang; Junyong Ma

doi:10.1117/12.2202360

8 October 2015 Maximum projection and velocity estimation algorithm for small moving target detection in space surveillance

Dalei Yao, Desheng Wen, Jianru Xue, Zhi Chen, Yan Wen, Baotan Jiang, Junyong Ma

Author Affiliations +

Proceedings Volume 9675, AOPC 2015: Image Processing and Analysis; 96752H (2015) https://doi.org/10.1117/12.2202360
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China

Abstract

The article presents a new method to detect small moving targets in space surveillance. Image sequences are processed to detect and track targets under the assumption that the data samples are spatially registered. Maximum value projection and normalization are performed to reduce the data samples and eliminate the background clutter. Targets are then detected through connected component analysis. The velocities of the targets are estimated by centroid localization and least squares regression. The estimated velocities are utilized to track the targets. A sliding neighborhood operation is performed prior to target detection to significantly reduce the computation while preserving as much target information as possible. Actual data samples are acquired to test the proposed method. Experimental results show that the method can efficiently detect small moving targets and track their traces accurately. The centroid locating precision and tracking accuracy of the method are within a pixel.

Citation Download Citation

Dalei Yao, Desheng Wen, Jianru Xue, Zhi Chen, Yan Wen, Baotan Jiang, and Junyong Ma "Maximum projection and velocity estimation algorithm for small moving target detection in space surveillance", Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96752H (8 October 2015); https://doi.org/10.1117/12.2202360

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