Abstract
This paper considers the migrating target detection problem under spiky clutter background. Ideal generalized likelihood ratio test (GLRT) detector for point target detection under spiky clutter needs iterative operations. By analyzing the reasons for the iteration, we design a non-iterative detector, i.e., Rao detector. The Monte-Carlo experiments show that, compare with the ideal GLRT detector, the proposed detector also possesses the constant false alarm rate character and achieve the same detection performance as GLRT without iterative operations.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (grant 61601341 and 61771367), Project Funded by China Postdoctoral Science Foundation (grant 2015M582615 and 2016T90891), Program for the National Science Fund for Distinguished Young Scholars (grant 61525105), National Natural Science Foundation of Shaanxi Province, Key R&D Program–The Key Industry Innovation Chain of Shaanxi (grant 2018JM6060) and the 111 Project (B18039).
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Niu, Z., Su, T., Zheng, J., Li, W. (2020). Migrating Target Detection Under Spiky Clutter Background. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_126
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DOI: https://doi.org/10.1007/978-981-13-9409-6_126
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