一种基于高效FrFT的LFM信号检测与参数估计快速算法
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摘要
针对传统方法对线性调频(LFM)信号检测与参数估计运算量大的问题,该文提出一种基于高效Fr FT的快速算法。首先,分析了高效Fr FT原理,指出高效Fr FT存在旋转角度的选取、易受初始频率影响以及抗噪性能差等问题。针对以上问题,该文利用修正的功率谱平滑滤波方法对高效Fr FT进行改进。理论分析表明,该文提出的改进算法仅用3次旋转角度即可实现较低信噪比下LFM信号的检测和参数估计。与传统的Fr FT相比,在保证参数估计精度不变的情况下,运算复杂度大大降低,更符合工程上实时处理的要求。仿真结果验证了该算法的有效性。
A fast algorithm based on the effective Fr FT is proposed to realize the detection and parameter estimation of Linear Frequency Modulation(LFM) signal, since the traditional algorithms have a great computational burden. The effective Fr FT is first analyzed, and pointed out to have problems in choosing the rotation angles, being easily affected by initial frequency, and poor anti-noise performance. Faced with the above problems, a modified power spectrum smooth filtering method is used to improve the effective Fr FT algorithm. The theoretical analysis indicates that the proposed method based on effective Fr FT can realize the detection and parameter estimation of LFM signal in low SNR condition with only three rotation angles. Furthermore, the computational cost is greatly reduced under the guarantee of the same parameter estimation accuracy compared to traditional Fr FT. The simulation results verify the effectiveness of the proposed algorithm.
A fast algorithm based on the effective Fr FT is proposed to realize the detection and parameter estimation of Linear Frequency Modulation(LFM) signal, since the traditional algorithms have a great computational burden. The effective Fr FT is first analyzed, and pointed out to have problems in choosing the rotation angles, being easily affected by initial frequency, and poor anti-noise performance. Faced with the above problems, a modified power spectrum smooth filtering method is used to improve the effective Fr FT algorithm. The theoretical analysis indicates that the proposed method based on effective Fr FT can realize the detection and parameter estimation of LFM signal in low SNR condition with only three rotation angles. Furthermore, the computational cost is greatly reduced under the guarantee of the same parameter estimation accuracy compared to traditional Fr FT. The simulation results verify the effectiveness of the proposed algorithm.
引文
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[14]张雯雯,刘黎平.一种新的相位编码信号识别方法[J].哈尔滨工程大学学报,2009,30(10):1204-1208.doi:10.3969/j.issn.1006-7043.2009.10.023.ZHANG Wenwen and LIU Liping.A new recognition method for phase-shift keying signals[J].Journal of Harbin Engineering University,2009,30(10):1204-1208.doi:10.3969/j.issn.1006-7043.2009.10.023.
[2]CZARNECKI K and MOSZYNSLI M.A novel method of local chirp-rate estimation of LFM chirp signals in the time-frequency domain[C].International Conference on Telecommunications and Signal Processing,Italy,Rome,2013:704-708.doi:10.1109/TSP.2013.6614028.
[3]李秀坤,吴玉双.多分量线性调频信号的Wigner-Ville分布交叉项去除[J].电子学报,2017,45(2):315-320.doi:10.3969/j.issn.0372-2112.2017.02.008.LI Xiukun and WU Yushuang.Cross-term removal of Wigner-Ville distribution for multi-component LFM signals[J].Acta Electronica Sinica,2017,45(2):315-320.doi:10.3969/j.issn.0372-2112.2017.02.008.
[4]BOASHASH B and OUELHA S.An improved design of high-resolution quadratic time-frequency distribution for the analysis of nonstationary multicomponent signal using directional compact kernels[J].IEEE Transactions on Signal Processing,2017,65(10):2701-2713.doi:10.1109/TSP.2017.2669899.
[5]WOOD J C and BARRY D T.Radon transformation of time-frequency distributions for analysis of multicomponent signals[J].IEEE Transactions on Signal Processing,1994,42(11):3166-3177.doi:10.1109/78.330375.
[6]BARBAROSSA S.Analysis of multicomponent LFM signals by a combined Wigner-Hough transform[J].IEEETransactions on Signal Processing,1995,43(6):1511-1515.doi:10.1109/78.388866.
[7]刘颖,陈殿仁,陈磊,等.基于周期Choi-Williams Hough变换的线性调频连续波信号参数估计算法[J].电子信息学报,2015,37(5):1136-1140.doi:10.11999/JEIT140876.LIU Ying,CHEN Dianren,CHEN Lei et al.Parameter estimation algorithm of linear frequency modulated continuous wave signals based on period Choi-Williams Hough transform[J].Journal of Electronics&Information Technology,2015,37(5):1136-1140.doi:10.11999/JEIT140876.
[8]WANG M,CHAN A K,and CHUI C K.Linear frequencymodulated signal detection using Radon-ambiguity transform[J].IEEE Transactions on Signal Processing,1998,43(6):571-586.doi:10.1109/78.661326.
[9]齐林,陶然,周思永,等.基于分数阶Fourier变换的多分量LFM信号的检测和参数估计[J].中国科学E辑,2003,33(8):750-759.doi:10.3321/j.issn:1006-9275.2003.08.008.QI Lin,TAO Ran,ZHOU Siyong,et al.Detection and parameter estimation of multicomponent LFM signal based on the fractional Fourier transform[J].Science in China(Series E),2003,33(8):750-759.doi:10.3321/j.issn:1006-9275.2003.08.008.
[10]陈艳丽,郭良浩,宫在晓.简明分数阶傅里叶变换及其对线性调频信号的检测和参数估计[J].声学学报,2015,40(6):761-771.doi:10.15949/j.cnki.0371-0025.2015.06.001.CHEN Yanli,GUO Lianghao,and GONG Zaixiao.The concise fractional Fourier transform and its application in detection and parameter estimation of the linear frequencymodulated signal[J].Acta Acustica,2015,40(6):761-771.doi:10.15949/j.cnki.0371-0025.2015.06.001.
[11]ZHANG Xuepan,LIAO Guisheng,ZHU Shengqi,et al.Efficient compressed sensing method for moving targets imaging by exploiting the geometry information of the defocused results[J].IEEE Geoscience and Remote Sensing Letters,2015,12(3):517-521.doi:10.1109/LGRS.2014.2349035.
[12]ALMEIDA L B.The fractional Fourier transform and timefrequency representations[J].IEEE Transactions on Signal Processing,1994,42(11):3084-3091.doi:10.1109/78.330368.
[13]赵兴浩,邓兵,陶然.分数阶傅里叶变换数值计算中的量纲归一化[J].北京理工大学学报,2005,25(4):360-364.doi:10.3969/j.issn.1001-0645.2005.04.019.ZHAO Xinghao,DENG Bing,and TAO Ran.Dimensional normalization in the digital computation of the fractional Fourier transform[J].Transactions of Beijing Institute of Technology,2005,25(4):360-364.doi:10.3969/j.issn.1001-0645.2005.04.019.
[14]张雯雯,刘黎平.一种新的相位编码信号识别方法[J].哈尔滨工程大学学报,2009,30(10):1204-1208.doi:10.3969/j.issn.1006-7043.2009.10.023.ZHANG Wenwen and LIU Liping.A new recognition method for phase-shift keying signals[J].Journal of Harbin Engineering University,2009,30(10):1204-1208.doi:10.3969/j.issn.1006-7043.2009.10.023.