Metrics to evaluate compression algorithms for raw SAR data

• Published in: IET radar, sonar & navigation sonar & navigation, 2019-03, Vol.13 (3), p.333-346
• Main Authors: Pieterse, Chané, du Plessis, Warren P, Focke, Richard W
• Format: Article
• Language: English
• Subjects: data compression; data domain; data reduction; data volume; image coding; modern synthetic aperture radar systems; radar imaging; raw SAR data; Review Article; SAR applications; SAR data‐compression algorithms; SAR mission; SAR operating modes; SAR systems; standardised quantitative performance metrics; SWAP‐C limitations; synthetic aperture radar
• ISSN: 1751-8784; 1751-8792; 1751-8792
• DOI: 10.1049/iet-rsn.2018.5213

Modern synthetic aperture radar (SAR) systems have size, weight, power and cost (SWAP-C) limitations since platforms are becoming smaller while SAR operating modes are becoming more complex. Thus, SAR systems are producing an ever-increasing volume of data that needs to be transferred to a ground station for processing. A compression algorithm seeks to reduce the data volume of the raw data; however, the algorithm can cause degradation and losses that may degrade the effectiveness of the SAR mission. This work addresses the lack of standardised quantitative performance metrics so that the performance of SAR data-compression algorithms can be objectively quantified. Therefore, metrics are established in two different domains, namely the data domain and the image domain. Since different levels of degradation are acceptable for different SAR applications, a trade-off can be made between the data reduction and the degradation caused by the algorithm. Due to SWAP-C limitations, there remains a trade-off between the performance and the computational complexity of the compression algorithm.