Resolution Enhancement for Forward-Looking Imaging of Airborne Multichannel Radar via Space-Time Reiterative Superresolution

被引:0
|
作者
Ren, Lingyun [1 ,2 ]
Wu, Di [1 ,2 ]
Zhu, Daiyin [1 ,2 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Elect & Informat Engn, Key Lab Radar Imaging & Microwave Photon, Minist Educ, Nanjing 211106, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Shenzhen Res Inst, Nanjing 211106, Peoples R China
关键词
Radar imaging; Radar; Radar antennas; Airborne radar; Imaging; Spaceborne radar; Antenna arrays; Airborne multichannel radar; forward-looking imaging (FLI); reiterative superresolution (RISR); space-time signal processing; superresolution (SR) imaging;
D O I
10.1109/JSTARS.2024.3446568
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In forward-looking imaging (FLI) of airborne radar, the enhancement of cross-range resolution is always a major research area and many studies on superresolution (SR) approaches, relied on the real array or virtual array, are proposed to break through the Rayleigh resolution. However, the reconstruction of complex scenes is still not accurate enough limited by the degrees of freedom. In this article, a novel FLI method for airborne multichannel radar named the space-time reiterative superresolution (ST-RISR) is proposed to obtain SR images of the forward-looking area, and hence to gain improved cross-range resolution. We first establish the space-time sampling model for airborne multichannel radar, where information in both the spatial and temporal slow-time domains is included, allowing for reconstructing more accurate SR images. In addition, the effect of array errors, always present in practice, is under consideration in the model. Then, a robust estimation algorithm called reiterative SR is employed and extended to process each of the so-called space-time snapshot in FLI. After the scattering coefficient vectors are obtained via the ST-RISR, they are accumulated to generate the final two-dimensional images. Finally, as is verified by simulated and measured data, the ST-RISR algorithm significantly improves the cross-range resolution of the forward-looking area, making it feasible in practical applications.
引用
收藏
页码:15288 / 15300
页数:13
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