Abstract
Detecting and resolving the space group targets in the main beam of radar is an urgent requirement for the air-defense and anti-missile radar system. Ground-based radar, as an important instrument for space surveillance, can be used to detect and track the space targets like grouped aircrafts, warheads and the decoys of the missiles. However, it is difficult to detect and resolve the dense targets due to the limit of the radar resolving power. To solve this problem, a space group targets detecting and resolving algorithm based on ultra-low sidelobe filtering is proposed. By exploiting the convex optimization into the pulse-Doppler radar, the problem of ultra-low sidelobe is converted into the problem of optimization. The key of this algorithm is to minimize the peak to sidelobe level (PSL) of the range sidelobes with a constraint of signal to noise ratio (SNR) loss. Then the ultra-low sidelobe filtering results are used to detect and resolve the space group targets in the main beam. Numerical and experimental results demonstrate the effectiveness of the proposed algorithm.
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Acknowledgements
The authors would like to thank all the anonymous reviewers for their valuable comments to improve the quality of this paper. This work was supported by the Postdoctoral Science Foundation of China under grant 2017M610966.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Chen, H. et al. (2019). Space Group Targets Detecting and Resolving Algorithm via Ultra-low Sidelobe Filtering. In: Li, B., Yang, M., Yuan, H., Yan, Z. (eds) IoT as a Service. IoTaaS 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-030-14657-3_31
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DOI: https://doi.org/10.1007/978-3-030-14657-3_31
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