摘要
在合成孔径雷达系统中,要提高分辨率就意味着产生大量的回波数据,从而加重了数模转换器和存储设备的负担。压缩感知理论的目的是在保证恢复稀疏信号的前提下降低采样率,而本文的目的是降低总的比特率。本文提出了一种基于压缩感知的单比特合成孔径雷达成像算法,并通过仿真实验验证了该算法的性能。与匹配滤波算法相比,该算法不仅能减少数据的总比特率,而且还能有效抑制目标的旁瓣和虚假目标。并且在低信噪比条件下,该算法比传统的多比特压缩感知算法展现出更强的鲁棒性。
In synthetic aperture radar( SAR) system,the requirement of high resolution always leads to large amount of echo data,which is a burden on analog-to-digital convertor( ADC) and onboard memory. In the compressive sensing( CS) framework,the goal is to reconstruct sparse signals at reduced sampling rate,while in this paper,the total bit rate that is taken into account can be reduced. This paper proposes a compressive sensing method for one bit coded SAR imaging.Simulation experiments verify the effectiveness of the proposed method. Compared with the matched filtering approach,this method cannot only reduce the total bit rate but also suppress the sidelobes and false targets. Moreover,this method also outperforms traditional multi-bit CS approaches when the signal to noise ratio( SNR) is low.
出处
《微波学报》
CSCD
北大核心
2015年第6期71-77,共7页
Journal of Microwaves
基金
国家自然科学基金重点项目(61431016)
