雷达学报
雷達學報
뢰체학보
JOURNAL OF RADARS
2013年
3期
265-270
,共6页
赵曜%张冰尘%洪文%吴一戎
趙曜%張冰塵%洪文%吳一戎
조요%장빙진%홍문%오일융
稀疏微波成像%RIPless%压缩感知%波形分析
稀疏微波成像%RIPless%壓縮感知%波形分析
희소미파성상%RIPless%압축감지%파형분석
Sparse microwave imaging%RIPless%Compressed sensing%Waveform analysis
稀疏微波成像回波数据可以建模为Toeplitz矩阵与地面场景的乘积,Toeplitz矩阵中的行向量为发射信号的时延。由于难于验证Toeplitz矩阵是否符合经典的稀疏信号处理中RIP等重建条件,因而分析稀疏微波成像采样数与发射波形的关系十分困难。近年提出的RIPless理论表明如果矩阵的行向量是对一个概率分布的随机抽取,并且该概率分布满足一定的条件,那么可以从少量的采样数据中恢复稀疏信号。Toeplitz矩阵适用于RIPless理论。该文首先介绍稀疏微波成像中观测矩阵的构造,然后利用稀疏信号处理中的RIPless理论分析波形中信号脉宽、带宽和信号形式与稀疏微波成像采样数的关系,进而比较不同波形对稀疏微波成像中的性能,最后通过仿真验证了该方法的有效性。
稀疏微波成像迴波數據可以建模為Toeplitz矩陣與地麵場景的乘積,Toeplitz矩陣中的行嚮量為髮射信號的時延。由于難于驗證Toeplitz矩陣是否符閤經典的稀疏信號處理中RIP等重建條件,因而分析稀疏微波成像採樣數與髮射波形的關繫十分睏難。近年提齣的RIPless理論錶明如果矩陣的行嚮量是對一箇概率分佈的隨機抽取,併且該概率分佈滿足一定的條件,那麽可以從少量的採樣數據中恢複稀疏信號。Toeplitz矩陣適用于RIPless理論。該文首先介紹稀疏微波成像中觀測矩陣的構造,然後利用稀疏信號處理中的RIPless理論分析波形中信號脈寬、帶寬和信號形式與稀疏微波成像採樣數的關繫,進而比較不同波形對稀疏微波成像中的性能,最後通過倣真驗證瞭該方法的有效性。
희소미파성상회파수거가이건모위Toeplitz구진여지면장경적승적,Toeplitz구진중적행향량위발사신호적시연。유우난우험증Toeplitz구진시부부합경전적희소신호처리중RIP등중건조건,인이분석희소미파성상채양수여발사파형적관계십분곤난。근년제출적RIPless이론표명여과구진적행향량시대일개개솔분포적수궤추취,병차해개솔분포만족일정적조건,나요가이종소량적채양수거중회복희소신호。Toeplitz구진괄용우RIPless이론。해문수선개소희소미파성상중관측구진적구조,연후이용희소신호처리중적RIPless이론분석파형중신호맥관、대관화신호형식여희소미파성상채양수적관계,진이비교불동파형대희소미파성상중적성능,최후통과방진험증료해방법적유효성。
Echo data can be modeled as the product of the Toeplitz matrix and reflectivity of the observed scene. The row of the Toeplitz matrix is the time shift of the transmitted signal. Because it is difficult to verify whether the Toeplitz matrix satisfies the reconstruction condition (such as restricted isometry property) of sparse microwave imaging, analyzing the performance of the transmitted signal in sparse microwave imaging is a problem. RIPless, a new progress in sparse signal processing, shows that if the row of the matrix is an independent and identically distributed (i.i.d.) random vector drawn from a distribution, and this distribution satisfies certain conditions, then one can faithfully recover approximately sparse signals from a minimal number of measurements. The Toeplitz matrix satisfies RIPless. In this paper, we introduce the construction of the measurement matrix in sparse microwave imaging. Further, the relationship between pulse duration, bandwidth and waveform type, and the number of measurements in sparse microwave imaging are analyzed. The simulation results show the effectiveness of the proposed method.