基于莱温伯格-马夸特的TDOA测向算法研究
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摘要
为降低到达时差测量噪声对测向精度的干扰,避免算法结果不收敛现象,提出一种基于莱温伯格-马夸特的测向算法。用线性最小二乘(LLS)算法求出的闭式解作为该算法的初始方位估计,通过迭代运算求得辐射源的方位,从而实现对声源方位的高精度估计。实验结果表明,相对LLS算法、Taylor算法,该算法能够达到克拉姆-拉奥下界,在保证结果收敛的同时提高测向精度,且具有鲁棒性。
A direction finding algorithm based on Levenberg-Marquardt( LM) is proposed to reduce the interference of Time Difference of Arrival( TDOA) measurement noise on lateral accuracy and avoid the phenomenon that algorithm results are not convergent. The closed-form solution obtained by the Linear Least Squares( LLS) algorithm is used as the initial bearing estimation of the algorithm,and the azimuth of the radiator is obtained by iterative operation,so as to achieve a high accuracy estimation of the acoustic source azimuth. Experimental results show that,compared with LLS algorithm and Taylor algorithm,this algorithm can reach the Cramer-Rao Lower Bound( CRLB),improve the direction finding accuracy and robustness while ensuring the convergence of the results.
A direction finding algorithm based on Levenberg-Marquardt( LM) is proposed to reduce the interference of Time Difference of Arrival( TDOA) measurement noise on lateral accuracy and avoid the phenomenon that algorithm results are not convergent. The closed-form solution obtained by the Linear Least Squares( LLS) algorithm is used as the initial bearing estimation of the algorithm,and the azimuth of the radiator is obtained by iterative operation,so as to achieve a high accuracy estimation of the acoustic source azimuth. Experimental results show that,compared with LLS algorithm and Taylor algorithm,this algorithm can reach the Cramer-Rao Lower Bound( CRLB),improve the direction finding accuracy and robustness while ensuring the convergence of the results.
引文
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[2]孙仲康,郭福成,冯道旺.单站无源定位跟踪技术[M].北京:国防工业出版社,2008.
[3]VAKULYA G,SIMON G.Fast adaptive acoustic localization for sensor networks[J].IEEE Transactions on Instrumentation and Measurement,2011,60(5):1820-1829.
[4]BERDUGO B,DORON M A,ROSENHOUSE J,et al.On direction finding of an emitting source from time delays[J].Journal of the Acoustical Society of America,2007,105(6):3355-3363.
[5]MENNITT D J.Multiarray passive acoustic localization and tracking[EB/OL].[2017-08-10].http://pdfs.semanticscholar.org/1a0c/fc522921348a3f7f3d01e3b62209ee17fbd4.pdf.
[6]CUI X X,YU K G,LU S S.Direction finding for transient acoustic source based on biased TDOA measurement[J].IEEE Transactions on Instrumentation and Measurement,2016,65(3):2442-2453.
[7]CUI X X,YU K G,LU S S.Evolutionary TDOA-based direction finding methods with 3-D acoustic array[J].IEEE Transactions on Instrumentation and Measurement,2015,64(6):2347-2359.
[8]FOY W H.Position-location solutions by Talor-series estimation[J].IEEE Transactions on Aerospace and Electronic Sytems,1976,12(2):187-194.
[9]张令文,谈振辉.基于泰勒级数展开的蜂窝TDOA定位新算法[J].通信学报,2007,28(6):7-11.
[10]方姝,倪育德,刘逸,等.基于最小二乘与Taylor级数展开的新型混合定位方法[J].计算机工程,2015,41(6):316-321.
[11]张光澄,王文娟,韩红蕾.非线性最优化计算方法[M].北京:高等教育出版社,2006.
[12]YU K,SHARP I,GUO Y J.地面无线定位技术[M].崔逊学,汪涛,译.北京:电子工业出版社,2012.
[13]MARQUARDT D.Algorithm for least-squares estimation of nonlinear parameters[J].SIAM Journal on Applied Mathematics,1963,11:431-441.
[14]CHAN Y,HO K.A simple and efficient estimator for hyperbolic location[J].IEEE Transactions on Signal Processing,1994,42(8):1905-1915.
[15]POISEL R A.电子战目标定位方法[M].王沙飞,田中成,译.北京:电子工业出版社,2008.
[16]NIELSEN R O.Estimation of azimuth and elevation angles for a plane wave sine wave with a 3-D array[J].IEEE Transactions on Signal Processing,1994,42(11):3274-3276.