Synthetic aperture radar (SAR) has a wide range of applications in the field of remote sensing. Subject to the bandwidth and resource limitations of the onboard system, it is necessary to compress the raw data obtained from SAR. The traditional algorithms for the compression of SAR raw data result in loss of weak signals such as the essential subsurface signal in subsurface detection, leading to problems in practical applications. In order to solve the aforementioned problem, the present study proposes a novel SAR data compression algorithm (preserve weak signal based on block adaptive quantization) that aims to preserve the subsurface signals on the basis of the traditional block adaptive quantization algorithm and provides its corresponding field-programmable gate array implementation. The implementation of the system holds a certain application value with great advantages in the optimized resources and speed, the optional automatic working mode, and the strong scalability.
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This work is supported in part by the National Nature Science Foundation of China under Grants 61571345 and Yangtse Rive Scholar Bonus Schemes and Ten Thousand Talent Program.
All authors have participated in approval of the final version.
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Zhang, J., Sang, L., Li, X. et al. Design and Implementation of Raw Data Compression System for Subsurface Detection SAR Based on FPGA. J geovis spat anal 4, 2 (2020). https://doi.org/10.1007/s41651-019-0042-1
- SAR raw data
- Subsurface detection
- Weak signal