宽波束高频雷达的超分辨率时-空级联处理

针对在宽波束高频雷达目标探测中传统傅立叶变换频谱分析方法多普勒分辨率较低的问题,提出了一种全超分辨率的时-空域级联信号处理方法.首先利用多重信号分类(MUSIC)算法获得频域超分辨率谱估计,构造出相应于各信号频率的信号子空间,将原始信号向各子空间进行投影变换以获得相应于各信号频率的阵列快拍,然后利用其进行空域超分辨率谱估计,获得相应的到达角.利用该方法能有效地采用短相干积累时间进行多目标的频率-到达角参数估计,从而有效地提高了宽波束高频雷达的目标探测和跟踪性能.数值仿真实验验证了该方法的有效性.

Super-resolution temporal-spatial joint processing for broad-beam high frequency radar

A novel method of temporal-spatial joint processing with super-resolution is proposed to deal with the poor resolution provided by the conventional Fourier transform method for Doppler analysis in broad-beam high frequency (HF) radars. Firstly, the multiple signal classification (MUSIC) algorithm is used in time domain to achieve the super-resolution Doppler spectrum and thus the signal frequencies. Then for each signal frequency, a signal subspace is constructed by the corresponding temporal steering vector, and the original receive signals are projected onto it to form the corresponding array snapshots. Finally the array snapshots are used to achieve the super-resolution spatial spectrum, and thus the directions of arrivals (DOA), of that frequency. The proposed method enables use of short coherent integration time (CIT) for multiple target detection, therefore can greatly improve the performance of the broad-beam HF radar on target detection and tracking. Numerical simulations show the validities of the proposed method.