基于HAF的参数化SAR宽带干扰抑制
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摘要
宽带干扰(wideband interference,WBI)是合成孔径雷达(synthetic aperture radar,SAR)中常见的干扰形式之一,它的存在极大地损害了SAR图像的质量,且WBI抑制一直是SAR干扰抑制中的一个难题。首先,针对WBI难以识别的问题,本文提出一种基于相邻脉冲统计特性的WBI识别方法;然后,在此基础上给出一种新的参数化SAR宽带干扰抑制方法,该方法首先把宽带干扰建模为多项式相位信号(polynomial phase signal,PPS),进而利用高阶模糊函数(high-order ambiguity function,HAF)以及相应的解模糊的方法来精确估计PPS的相关参数,从而将WBI信号转化为窄带干扰(narrowband interference,NBI)信号,然后利用现有的NBI信号抑制方法得到去除干扰后的回波信号;最后,计算机仿真结果和实测数据处理结果验证了本文提出方法的有效性。
Wideband interference(WBI),as one of the common forms of interference in synthetic aperture radar(SAR),significantly reduces the quality of SAR images and is always difficult to tackle.For the problem that the WBI is difficult to identify,a WBI recognition method based on the statistical feature of adjacent pulses is presented firstly.Based on that,a novel parameterized WBI suppression method for SAR imaging is proposed.First,WBI signal is modelled as a polynomial phase signal(PPS),and then the high-order ambiguity function(HAF)as well as the corresponding aliasing resolved method are adopted to estimate the coefficients of PPS.According to obtained coefficients,the WBI signals can be transformed into narrowband interference(NBI)signal,and then the existing NBI suppression method can be utilized to remove interference of echo signal.Finally,the computer simulation results and the measured data processing results show the effectiveness of the proposed method.
Wideband interference(WBI),as one of the common forms of interference in synthetic aperture radar(SAR),significantly reduces the quality of SAR images and is always difficult to tackle.For the problem that the WBI is difficult to identify,a WBI recognition method based on the statistical feature of adjacent pulses is presented firstly.Based on that,a novel parameterized WBI suppression method for SAR imaging is proposed.First,WBI signal is modelled as a polynomial phase signal(PPS),and then the high-order ambiguity function(HAF)as well as the corresponding aliasing resolved method are adopted to estimate the coefficients of PPS.According to obtained coefficients,the WBI signals can be transformed into narrowband interference(NBI)signal,and then the existing NBI suppression method can be utilized to remove interference of echo signal.Finally,the computer simulation results and the measured data processing results show the effectiveness of the proposed method.
引文
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[2]WANG H.A comparative analysis of adaptive beamforming algorithms for satellite multiple-beam antennas[J].Acta Electronica Sinica,2001,29(3):358-360.
[3]TAO M,ZHOU F,ZHANG Z.Wideband interference mitigation in high-resolution airborne synthetic aperture radar data[J].IEEE Trans.on Geoscience and Remote Sensing,2016,54(1):74-87.
[4]张双喜,张磊,刘艳阳,等.基于STFT和WT的SAR干扰抑制算法[J].电子学报,2011,39(7):1581-1588.ZHANG S X,ZHANG L,LIU Y Y,et al.Interference suppression algorithm for SAR based on short-time Fourier transform and Wavelet transform[J].Acta Electronica Sinica,2011,39(7):1581-1588.
[5]粟嘉,陶海红,宋大伟,等.基于WD和时频滑窗掩膜的SAR干扰抑制算法[J].电子学报,2015,43(12):2345-2351.SU J,TAO H H,SONG D W,et al.Interference suppression algorithm for SAR based on WD and sliding window masking technique in time-frequency domain[J].Acta Electronica Sinica,2015,43(12):2345-2351.
[6]BARBAROSSA S,SCAGLIONE A,GIANNAKIS G B.Product high-order ambiguity function for multicomponent polynomialphase signal modeling[J].IEEE Trans.on Signal Processing,1998,46(3):691-708.
[7]PELEG S,FRIEDLANDER B.The discrete polynomial-phase transform[J].IEEE Trans.on Signal Processing,1995,43(8):1901-1914.
[8]ZHOU G T,WANG Y.Exploring lag diversity in the high-order ambiguity function for polynomial phase signals[C]∥Proc.of the IEEE Signal Processing Workshop on the Higher-Order Statistics,1997:103-106.
[9]DJUKANOVI S,DJUROVI I.Aliasing detection and resolving in the estimation of polynomial-phase signal parameters[J].Signal Processing,2012,92(1):235-239.
[10]ANGEBY J.Aliasing of polynomial-phase signal parameters[J].IEEE Trans.on Signal Processing,2000,48(5):1488-1491.
[11]PELEG S,PORAT B.Estimation and classification of polynomial-phase signals[J].IEEE Trans.on Information Theory,1991,37(2):422-430.
[12]DJUKANOVI S,POPOVI V.A parametric method for multicomponent interference suppression in noise radars[J].IEEE Trans.on Aerospace and Electronic Systems,2012,48(3):2730-2738.
[13]DJUKANOVI S,DAKOVIC M,THAYAPARAN T,et al.Method for non-stationary jammer suppression in noise radar systems[J].IET Signal Processing,2010,4(3):305-313.
[14]LIU H,LI D.RFI suppression based on sparse frequency estimation for SAR imaging[J].IEEE Geoscience and Remote Sensing Letters,2016,13(1):63-67.
[15]ZHOU F,TAO M.Research on methods for narrow-band interference suppression in synthetic aperture radar data[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2015,8(7):3476-3485.
[16]LI D,LIU H Q,YANG L S.Efficient time-varying interference suppression method for synthetic aperture radar imaging based on time-frequency reconstruction and mask technique[J].IET Radar,Sonar&Navigation,2015,9(7):827-834.
[17]XIN M D,ZHENG B.Motion parameter estimation based SAR imaging[J].Acta Electronica Sinica,2001,29(12):1824-1828.