**5. Conclusions**

This paper proposes a recursive local summation RX algorithm for hyperspectral anomaly detection based on sliding window processing. In order for a fast implementation of a sliding window detector, a recursive update equation for the inversion of local background covariance matrices is developed. In addition, a background suppression R-BS-LS-RXD detector is also proposed in this paper, which removes the current under test pixel from the recursively update processing. This method exploits a local summation strategy in a sliding window, which could sum multiple correlated local background statistics to suppress the major background. The real hyperspectral image experiments

have proven that the R-LS-RXD and LS-RXD obtain similar detection performances, which can be competitive with that of CSA-RXD based on sliding array window background. To investigate the computational complexity issue, a comprehensive comparative analysis on the CPT of running recursive updating sliding window detector and un-recursive updating method is conducted in theory and experiments. The result shows R-LS-RXD has a significant acceleration effect for calculation. Our future work mainly focuses on deriving real-time progressive processing of anomaly detection for hyperspectral imagery that was acquired by other data formats.

**Acknowledgments:** This work was supported by the National Nature Science Foundation of China (No. 61571170), the Joint Funds of the Ministry of Education of China No. 6141A02022314), Shanghai Aerospace Science and Technology Innovation Fund (No.SAST2015033), Fundamental Research Funds for Central Universities under Grants (No. 3132017080) and the Open Research Fund of Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences(LSIT201707D).

**Author Contributions:** All the authors made significant contributions to the work. Liaoying Zhao and Weijun Lin designed the research and analyzed the results. Yulei Wang provided advice for the preparation and revision of the paper. Xiaorun Li assisted in the preparation work and validation work.

**Conflicts of Interest:** The authors declare no conflict of interest.
