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| Citation: | Zhao Yao, Deng Yunkai, Wang Yu, Li Ning, Wang Wei. Study of Effect of Raw Data Compression on Azimuth Multi-channel SAR System[J]. Journal of Radars, 2017, 6(4): 397-407. doi: 10.12000/JR17030
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Study of Effect of Raw Data Compression on Azimuth Multi-channel SAR System
doi: 10.12000/JR17030
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Abstract
An effective way to achieve High Resolution and Wide Swath (HRWS) imaging capability is the multi-channel technique in azimuth. Improved resolution and swath can dramatically increase the volume of echo data in the SAR system. However, the onboard data storage and data-transmission bandwidth are limited, so data compression technique is typically used to reduce the volume of echo data. To study the effect of raw data compression on the azimuth multi-channel SAR system, in this paper, we establish a multi-channel SAR signal model based on data compression. We then derive and analyze the effects of data compression on the Signal-to-Noise Ratio (SNR) scaling factor of the multi-channel SAR system and quantization noise. Finally, we verify the validity of the proposed model and analysis results using simulation and real data and discuss the effect of data compression on the Peek-to-Ghost Ratio (PGR). The results of this paper provide an important theoretical basis for the choice of compression method in the multi-channel SAR system. -
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References
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- Figure 1. Azimuth multi-channel SAR system
- Figure 2. Signal model with thermal noise
- Figure 3. Signal model without thermal noise
- Figure 4. Flowchart of simulation experiments
- Figure 5. SNR scaling factor of adding different thermal noise over quantization bits
- Figure 6. Signal to quantization noise ratio of different non-uniform factors over quantization bits in data domain
- Figure 7. Peek-to-ghost-ratio of different non-uniform factors over quantization bits
- Figure 8. Flowchart of real data experiments
- Figure 9. Focused images for reconstructed raw data
- Figure 10. The signal to Quantization Noise Ratio over quantization bits in data domain
- Figure 11. Mean phase error over quantization bits in data domain
- Figure 12. Signal to quantization noise ratio over quantization bits in image domain
- Figure 13. Mean phase error over quantization bits in image domain