# Bistatic Sea Clutter Suppression Method Based on Compressed Sensing Optimization
## 5 Conclusions  
In this paper, we investigate the problem of bistatic sea clutter suppression and propose a new bistatic sea clutter suppression method based on compressed sensing  
Figure 8: Comparison of echo power spectra after suppression using different algorithms: (**a**) without suppression, (**b**) root method, (**c**) SVD method, (**d**) the proposed method.  
optimization. First, we analyzed and modeled the bistatic radar echo and sea clutter. To address the issue of poor reconstruction signal caused by the fixed sparse basis, we propose a sparse basis optimization algorithm based on transfer learning, which obtains an optimized adaptive sparse basis. Furthermore, we propose a sensing matrix optimization algorithm using eigenvalue decomposition and gradient descent to optimize the sensing matrix. The adaptive sparse basis and the optimized sensing matrix can improve the reconstruction accuracy of sea clutter, and then improve the effect of sea clutter cancellation and suppression. The simulation results demonstrate that the proposed method has a good effect on suppressing bistatic sea clutter. Compared with other radiation sources, spaceborne or satellite radiation sources have unique advantages in the detection of bistatic sea surface target detection and the monitoring of the sea surface, such as wide coverage and work around the clock. In this context, the bistatic sea clutter suppression method proposed in this paper has great practical significance.  
Investigation, J.L.; methodology, J.L.; validation, J.L.; writing--original draft, J.L.; writing--review and editing, Z.P. All authors have read and agreed to the published version of the manuscript.  
This article received no external funding.  
Not applicable.  
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