摘要
传统雷达目标检测方法一般将单个距离单元的目标当成单目标进行检测,而不会估计距离单元内目标的数量。针对该研究空缺,提出一种基于深度残差网络的雷达目标数量估计方法。该方法将雷达信号转换成时频图并输入至训练好的深度残差网络。残差网络根据单个目标与多个目标对应时频图的差异即可准确得到雷达目标数量的估计值。仿真表明该方法能有效地估计出雷达目标数量。
Traditional radar detection methods generally detect the target of a range cell as a single target, but do not estimate the number of targets in the range cell. Aiming at this research vacancy, a target number estimation method based on deep residual learning is proposed. The method converts the radar signal into time-frequency graph and inputs it to the trained deep residual network.The residual network can accurately estimate the number of radar targets according to the difference of time-frequency graph between single target and multiple targets. The residual network can then output an estimate of the number of radar targets. Simulation results show that this method can estimate the number of radar targets effectively.
作者
吴明华
饶彬
王伟
WU Minghua;RAO Bin;WANG Wei(School of Electronics and Communication Engineering,Sun Yat-sen University,Shenzhen Guangdong 518107,China)
出处
《太赫兹科学与电子信息学报》
2022年第3期213-217,共5页
Journal of Terahertz Science and Electronic Information Technology
关键词
残差网络
目标检测
信号处理
目标数量估计
residual network
radar detection
signal processing
target number estimation
