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发表刊物：IET Signal Processing

摘要：Unmanned aerial vehicles (UAVs), widely used due to their low cost and versatility, pose security and privacy threats, which calls for their reliable recognition at low altitudes. However, strong ground clutter and multipath effects severely interfere with the weak radar echoes reflected off the micro-UAVs, resulting in severe degradation of recognition reliability. Based on channel modelling and UAV recognisability analysis, a time-frequency transform-aided contrastive learning model is proposed to suppress the severe ground clutter and reliably recognise low-altitude UAVs. In the proposed fr

论文类型：期刊论文

论文编号：https://doi.org/10.1049/sil2.12133

文献类型：J

卷号：16

期号：5

页面范围：588-600

是否译文：否

收录刊物：SCI

发布期刊链接：https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/sil2.12133