雷达经常发射线性调频(LFM)信号并对接收信号进行频域去斜以及傅里叶逆变换实现常规的目标距离分辨。基于雷达目标的稀疏性特征,数字回波信号经频域去斜后在傅里叶字典矩阵下可以稀疏表示,根据压缩感知理论,对去斜信号向量进行低维线性观测后可以将稀疏表示向量解算出来,其中非零元素的位置表征了目标距离,当两个非零元素之间的间隔小于瑞利限时,表明上述处理过程具有超分辨能力。基于此,文中提出了一种基于LFM 信号频域去斜和压缩感知的雷达距离超分辨方法,对LFM 回波信号进行频域去斜处理及稀疏表示,采用压缩感知技术解算稀疏表示向量以实现超分辨,并给出了仿真实例和分析。

Radar frequently transmits linear frequency modulated (LFM) signal and then carries out frequency-domain dechirp and inverse Fourier transform on the received signal to reach conventional target range resolution. Based on the sparsity feature of radar target, LFM digital echo signal can be sparsely represented under Fourier dictionary matrix after frequency-domain dechirp. According to compressive sensing theory, the sparse representation vector can be solved after low-dimension linear observation of dechirp signal vector, in which the position of non-zero element represents the target range, and when the range interval between two non-zero elements is less than the Rayleigh limit, it shows that the above processing has super-resolution capability. Based on that, a radar range super-resolution approach based on frequency-domain dechirp of LFM signal and compressive sensing is presented in this paper. Firstly, LFM echo signal is subjected to frequency-domain dechirp and sparse representation, and then the sparse representation vector is solved by the compressive sensing technique to achieve super-resolution. Finally, the simulation example and related analysis are provided.

TN953

南京工业职业技术大学引进人才科研启动基金资助项目(YK21-02-04)