首页> 外文会议>IEEE Radar Conference >Radio frequency interference suppression in ultra-wideband synthetic aperture radar using range-azimuth sparse and low-rank model
【24h】

Radio frequency interference suppression in ultra-wideband synthetic aperture radar using range-azimuth sparse and low-rank model

机译:基于距离方位角稀疏和低秩模型的超宽带合成孔径雷达中的射频干扰抑制

获取原文

摘要

Ultra-wideband (UWB) Synthetic Aperture Radars (SAR) operate over a large bandwidth ranging from under 100 MHz to over a few Ghz. They often share spectrum with other systems such as radio, TV and cellular networks. The mitigation of radio frequency interference(RFI) from these sources is an important problem for UWB SAR systems. Traditional RFI suppression techniques such as notch filtering introduce side effects such as large sidelobes or poor peak-to-sidelobe ratio. More recently, methods based on sparsity and compressive sensing that do not have these side effects have been proposed. In particular, a sparse and low-rank method that models SAR data as a linear combination shifted SAR pulses and RFI to be of low-rank has been found to be effective. This model however uses the structure of SAR data in down-range direction only and ignores the structure in azimuth direction. In this paper, we propose to replace the data model with a new sparse model that incorporates structure in azimuth direction as well. We demonstrate that the new model has significantly better performance than the previously proposed model. It performs robustly even in the presence of high level of noise(-20 dB SNR) and does not suppress small targets like the previously proposed model did.
机译:超宽带(UWB)合成孔径雷达(SAR)的工作带宽范围从100 MHz以下到几GHz以上。他们经常与其他系统共享频谱,例如广播,电视和蜂窝网络。这些来源的射频干扰(RFI)的缓解是UWB SAR系统的重要问题。传统的RFI抑制技术(例如陷波滤波)会带来副作用,例如较大的旁瓣或较差的峰旁瓣比。最近,已经提出了基于稀疏性和压缩感测的不具有这些副作用的方法。特别地,已经发现有效的是稀疏和低秩方法,该方法将SAR数据建模为移位SAR脉冲和RFI的线性组合,具有低秩。但是,该模型仅使用下方向的SAR数据结构,而忽略了方位方向的结构。在本文中,我们建议将数据模型替换为新的稀疏模型,该模型也包含在方位方向上的结构。我们证明,新模型比以前提出的模型具有明显更好的性能。即使在存在高噪声水平(-20 dB SNR)的情况下,它仍具有出色的性能,并且不会像以前提出的模型那样抑制小的目标。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号