基于经验小波变换的目标加速度估计算法

陈浩; 郭军海; 齐巍

doi:10.13700/j.bh.1001-5965.2014.0036

基于经验小波变换的目标加速度估计算法

doi: 10.13700/j.bh.1001-5965.2014.0036

北京跟踪与通信技术研究所, 北京 100094

基金项目: 国家自然科学基金资助项目(61101070);总装备部预先研究资助项目

详细信息

作者简介:
陈浩(1989-),男,湖北黄冈人,硕士生,chinnyhaochen@126.com

通讯作者:
郭军海(1968-),男,湖北宜昌人,研究员,gjchy@aliyun.com,主要研究方向为外弹道测量数据处理方法研究、雷达信号处理.

中图分类号: V557.3;TN911.7
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- 被引次数: 0
出版历程
- 收稿日期: 2014-01-15
- 网络出版日期: 2015-01-20

Estimation of target's acceleration based on empirical wavelet transform

CHEN Hao,
GUO Junhai^,,

Beijing Institute of Tracking and Telecommunication Technology, Beijing 100094, China

摘要

摘要: 加速度会使目标回波信号的频谱展宽甚至偏移,使传统脉冲雷达测速方法不能准确估计信号的多普勒频率.为了克服目标的加速度对脉冲雷达测速的影响,提出了一种基于经验小波变换(EWT)的径向加速度估计算法.对回波信号进行EWT变换和能量型频率主成分提取方法得到回波信号瞬时频率,并利用抗差最小二乘拟合得到相位高阶系数,进而估计目标径向加速度.利用估计的加速度对信号频谱进行补偿就能准确估计信号的多普勒频率.仿真表明EWT方法是一种高精度快速算法,且估计误差最接近待估参数的C-R下界.实测高速飞行器脉冲雷达I/Q数据验证表明,EWT算法估计的加速度精度优于0.4 m/s².该算法可应用于脉冲雷达实时加速度估计.
- 径向加速度 /
- 非平稳信号 /
- 经验小波变换 /
- 瞬时频率 /
- 频率提取
Abstract: Target's accelerations lead to spectrum shift and broadening of target's echo signal, resulting in the inaccuracy estimation of target's Doppler frequency with traditional pulse radar velocity measurement method. To overcome the effect of acceleration on pulse radar velocity measurement, an empirical wavelet transform (EWT) based radial acceleration estimation method was proposed. The instantaneous frequency of the echo signal can be extracted through EWT and energy-oriented principal frequency components extraction method. The high order coefficients of the phase were obtained through robust least square fitting on the instantaneous frequency, which correspond to the radial velocity and radial acceleration respectively. After compensating the echo signal with estimated accelerations, the Doppler frequency of echo signal can be accurately estimated. Simulations show that the EWT method is a fast algorithm with high estimation accuracy, and the estimation error is close to Cramer-Rao lower bound. Applying EWT method on measured pulse radar data of high speed vehicle, the estimated acceleration error is smaller than 0.4 m/s². EWT method is applicable in real time pulse radar acceleration estimation.
- radial acceleration /
- non-stationary signal /
- empirical wavelet transform /
- instantaneous frequency /
- frequency extraction

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参考文献(17)

[1]	袁斌,陈曾平,徐世友,等.基于距离单元筛选快速最小熵的含旋转部件目标相位补偿方法[J].电子与信息学报,2013,35(5):1128-1134.Yuan B,Chen Z P,Xu S Y,et al.Phase compensation for targets with rotating parts based on range bins selection in fast minimum entropy[J].Journal of Electronics & Information Technology,2013,35(5):1128-1134(in Chinese).
[2]	夏猛,杨小牛.基于三次相位补偿的运动目标参数估计[J].电子科技大学学报,2013,42(4):559-564.Xia M,Yang X N.Parameter estimation for moving target based on three-phase compensation[J].Journal of University of Electronic Science and Technology of China,2013,42(4):559-564(in Chinese).
[3]	Cao S,Bing P,Lu J,et al.Seismic data time-frequency analysis by the improved Hilbert-Huang transform[J].Oil Geophysical Prospecting,2013,48(2):246-254.
[4]	Wang Z Z,Liu F,Huang Y,et al.Digitized periodic wigner-hough transform and its performance analysis[J].Telecommunications Engineering,2012,52(9):1452-1458.
[5]	欧国建,陈玲珑,何俞璟.一种多分量LFM信号参数估计的快速仿真算法[J].重庆邮电大学学报:自然科学版,2013,25(4):459-463.Ou G J,Chen L L,He Y J.A simulation fast algorithm for parameters estimationof the multicomponent LFM signals[J].Journal of Chongqing University of Posts and Telecommunications,2013,25(4):459-463(in Chinese).
[6]	Yu Y.Detection and parameter estimation of linear frequency modulated signals based on radon transform[J].Journal of Modern Defence Technology,2013,41(1):136-141.
[7]	Zhu Y W,Zhao Y J,Jia W G.Fast parameter estimation method for LFM signal based on ambiguity function slice and FrFT[J].Journal of Information Engineering University,2012,13(2):218-223.
[8]	Mohindru P,Khanna R K R,Bhatia S S.Analysis of chirp signal with fractional Fourier transform[J].Majlesi Journal of Multimedia Processing,2013,2(1):314-322.
[9]	Dinç E,Duarte F B,Machado J A T,et al.Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture[J].Signal,Image and Video Processing,2013,21(10):1-7.
[10]	Huang N E.The empirical modedecomposition and the Hilbert spectrum for nonlinear andnon-stationary time series analysis[J].Proceedings of Royal Society of London,1998,A4(54):903-995.
[11]	Flandrin P,Rilling G,Goncalves P.Empirical mode decomposition as a filter bank[J].Signal Processing Letters,IEEE,2004,11(2):112-114.
[12]	崔华.一种新的线性调频信号的瞬时频率估计方法[J].计算机应用研究,2008,25(8):2532-2533.Cui H.New method for instantaneous frequency estimations of LFM signals[J].Application Research of Computers,2008,25(8):2532-2533(in Chinese).
[13]	王燕,邹男,付进,等.基于局部瞬时能量密度级的瞬态信号检测方法[J].电子与信息学报,2013,35(7):1720-1724.Wang Y,Zou N,Fu J,et al.Transient signal detection method based on partial instantaneous energy density level[J].Journal of Electronics & Information Technology,2013,35(7):1720-1724(in Chinese).
[14]	Wu Z H,Huang N E.Ensemble empirical mode decomposition:a noise assisted data analysis method[J].Advances in Adaptive Data Analysis,2009,1(1):1-41.
[15]	Gilles J.Empirical wavelet transform[J].IEEE Transactions in Signal Processing,2013,61(16):3999-4010.
[16]	Steven M K.Fundamentals of statistical signal processing, Volume I:estimation theory[M].Beijing:Publishing House of Electronics Industry,2006:25-39.
[17]	成礼智.小波的理论与应用[M].北京:科学出版社,2009:75-88.Cheng L Z.Theories and applications of wavelet[M].Beijing:Science Press,2009:75-88(in Chinese)