## 5 Conclusions  
In recent years, RFI is increasing and now represents one of the major threats to scientific uses of the spectrum. The awareness of the adverse effect of RFI is growing over the years, especially for quantitative remote sensing applications where highly sensitive measurements are required. Its adverse impacts lie on many aspects ranging from raw data collection, image formation, and subsequent interpretation process. In this review, we provide a comprehensive survey of the state-of the-art techniques for RFI mitigation in SAR systems, which can serve as a reference for future work on the implementation of most suitable RFI mitigation scheme for an airborne or space-borne SAR system. The role of frequency management and allocation is very important and requires to be further enhanced. In the future, more intelligent regulation is required, which means the electromagnetic spectrum are more efficient and dynamically controlled. Scientific interests must be actively engaged to satisfy the science needs. Although an increasing variety of successful mitigation options are available, there is a tradeoff between efficiency and accuracy when adopting the post-processing methods. Notch filtering and LMS filtering are adopted widely for its simplicity and efficiency, and is very suitable for on-board quick processing. Other refined mitigation schemes such as time-frequency domain joint filtering and sparse recovery are possible candidates for off-line ground processing due to their relatively large computational complexity. In particular, on-line real-time data processing may be preferred in a variable RFI environment, while special measures such as reference antennas and spatial filtering may be preferred for known and fixed sources of RFI. Existing post-processing mitigation schemes can be applied on the raw data or SLC data. Nevertheless, raw-data filtering is still a superior approach that should be considered whenever possible. Moreover, more attention should be paid on the evaluation of mitigation performance. It is intuitively to focus on the strong interference and its resulting obvious distortion to amplitude. However, lower power interference could also not be omitted, because its impact on phase could be detrimental. For many SAR systems, mitigating interference artifacts from imagery is not the only concern, and the phase preserving performance is important. Therefore, the chosen interference mitigation scheme must also guarantee successful restoration of the quality of the second order products, as it is highly related with the post image products, e.g., interferometric coherence, polarimetric descriptors, etc. In the foreseeable future, the RFI will remain as a great challenge to accurate remote sensing by active sensor like SAR. Current RFI mitigation technology appears to offer significant benefits to SAR remote sensing, but more refined characterization and mitigation work remains to be developed that is practical and applicable in routine operations. The development of a common set of standardized metrics connecting RFI levels to science product accuracies would be useful in assessing the costs of observing with increasing levels of RFI. Conceptualization, M.T., L.W. ; methodology, M.T., J.S., Y.H. ; formal analysis, J.S., and Y.H. ; resources, J.S., and Y.H. ; data curation, M.T., J.S., Y.H. ; writing--original draft preparation, M.T., J.S. ; writing--review and editing, M.T. ; supervision, L.W. ; funding acquisition, M.T., J.S., L.W. This work was funded by National Nature Science Foundation of China (NSFC) under Grants 618013906, 61701414 and 61901112. Also partly supported by the Science, Technology, and Innovation Commission of Shenzhen Municipality under Grant JCYJ20170306154716846 and JCYJ20170815154325384.