ship detection in strong clutter environment based on adaptive regression thresholding for hfswr
- 10.2991/iccset-14.2015.78How to use a DOI?
- HFSWR; ship detection; strong clutter environment; adaptive detection method
High Frequency Surface Wave Radar (HFSWR) has the ability to detect and track ships in real time and beyond the horizon continuously. The method of adaptive power regression thresholding (APRT) is one of good adaptive detection methods for HFSWR, and it works well in most cases. But in strong clutter environment, some strong clutters with high amplitude will raise the noise level, which would overestimate the detection threshold along Doppler cells or range cells and cause some ships become undetectable. This paper proposes an improved method to solve the problem appearing in strong clutter environment based on APRT method. It adds a process of strong clutter suppression before ship detection to eliminate its influence on estimation of noise level and detection threshold. The processing results of real measured HFSWR data show that the improved method can effectively improve the performance of detector under strong sea clutter environment.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yonggang Ji AU - Leda Xu AU - Yiming Wang AU - Xiaoliang Chu PY - 2015/01 DA - 2015/01 TI - ship detection in strong clutter environment based on adaptive regression thresholding for hfswr BT - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology PB - Atlantis Press SP - 352 EP - 355 SN - 2352-538X UR - https://doi.org/10.2991/iccset-14.2015.78 DO - 10.2991/iccset-14.2015.78 ID - Ji2015/01 ER -