Research Article
Space Group Targets Detecting and Resolving Algorithm via Ultra-low Sidelobe Filtering
@INPROCEEDINGS{10.1007/978-3-030-14657-3_31, author={Hongmeng Chen and Yaobing Lu and Jing Liu and Hanwei Sun and Jiahao Lin and Xiaoli Yi and Heqiang Mu and Zeyu Wang}, title={Space Group Targets Detecting and Resolving Algorithm via Ultra-low Sidelobe Filtering}, proceedings={IoT as a Service. 4th EAI International Conference, IoTaaS 2018, Xi’an, China, November 17--18, 2018, Proceedings}, proceedings_a={IOTAAS}, year={2019}, month={3}, keywords={Group targets Ultra-low sidelobe Convex optimization}, doi={10.1007/978-3-030-14657-3_31} }- Hongmeng Chen
Yaobing Lu
Jing Liu
Hanwei Sun
Jiahao Lin
Xiaoli Yi
Heqiang Mu
Zeyu Wang
Year: 2019
Space Group Targets Detecting and Resolving Algorithm via Ultra-low Sidelobe Filtering
IOTAAS
Springer
DOI: 10.1007/978-3-030-14657-3_31
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.
