高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于马尔科夫键蒙特卡洛抽样的最大似然时差-频差联合估计算法

赵拥军 赵勇胜 赵闯

赵拥军, 赵勇胜, 赵闯. 基于马尔科夫键蒙特卡洛抽样的最大似然时差-频差联合估计算法[J]. 电子与信息学报, 2016, 38(11): 2745-2752. doi: 10.11999/JEIT160050
引用本文: 赵拥军, 赵勇胜, 赵闯. 基于马尔科夫键蒙特卡洛抽样的最大似然时差-频差联合估计算法[J]. 电子与信息学报, 2016, 38(11): 2745-2752. doi: 10.11999/JEIT160050
ZHAO Yongjun, ZHAO Yongsheng, ZHAO Chuang. Maximum Likelihood TDOA-FDOA Estimator Using Markov Chain Monte Carlo Sampling[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2745-2752. doi: 10.11999/JEIT160050
Citation: ZHAO Yongjun, ZHAO Yongsheng, ZHAO Chuang. Maximum Likelihood TDOA-FDOA Estimator Using Markov Chain Monte Carlo Sampling[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2745-2752. doi: 10.11999/JEIT160050

基于马尔科夫键蒙特卡洛抽样的最大似然时差-频差联合估计算法

doi: 10.11999/JEIT160050
基金项目: 

国家自然科学基金(61401469, 41301481, 61501513),国家高技术研究发展计划(2012AA7031015)

Maximum Likelihood TDOA-FDOA Estimator Using Markov Chain Monte Carlo Sampling

Funds: 

The National Natural Science Foundation of China (61401469, 41301481, 61501513), The National High Technology Research and Development Program of China (2012AA7031015)

  • 摘要: 该文针对无源定位中参考信号真实值未知的时差-频差联合估计问题,构建了一种新的时差-频差最大似然估计模型,并采用马尔科夫链蒙特卡洛(MCMC)方法求解似然函数的全局极大值,得到时差-频差联合估计。算法通过生成时差-频差样本,并统计样本均值得到估计值,克服了传统互模糊函数(CAF)算法只能得到时域和频域采样间隔整数倍估计值的问题,且不存在期望最大化(EM)等迭代算法的初值依赖和收敛问题。推导了时差-频差联合估计的克拉美罗界,并通过仿真实验表明,算法在不同信噪比条件下的估计精度优于CAF算法和EM算法,且计算复杂度较低。
  • HIGGINS T, WEBSTER T, and MOKOLE E L. Passive multistatic radar experiment using WiMAX signals of opportunity. Part 1: Signal processing[J]. IET Radar, Sonar Navigation, 2016, 10(2): 238-247. doi: 10.1049/iet-rsn. 2015.0020.
    LI Ruiyang and HO K. Efficient closed-form estimators for multistatic sonar localization[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(1): 600-614. doi: 10.1109/TAES.2014.140482.
    ZEMMARI R, BROETJE M, BATTISTELLO G, et al. GSM passive coherent location system: Performance prediction and measurement evaluation[J]. IET Radar, Sonar Navigation, 2014, 8(2): 94-105. doi: 10.1049/iet-rsn.2013.0206.
    DECARLI N, GUIDI F, and DARDARI D. A novel joint RFID and radar sensor network for passive localization: Design and performance bounds[J]. IEEE Journal of Selected Topics in Signal Processing, 2014, 8(1): 80-95. doi: 10.1109 /JSTSP.2013.2287174.
    曲付勇, 孟祥伟. 基于约束总体最小二乘方法的到达时差到达频差无源定位算法[J]. 电子与信息学报, 2014, 36(5): 1075-1081. doi: 10.3724/SP.J.1146.2013.01019.
    QU Fuyong and MENG Xiangwei. Source localization using TDOA and FDOA measurements based on constrained total least squares algorithm[J]. Journal of Electronics Information Technology, 2014, 36(5): 1075-1081. doi: 10.3724 /SP.J.1146.2013.01019.
    STEIN S. Algorithms for ambiguity function processing[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1981, 29(3): 588-599. doi: 10.1109/TASSP. 1981.1163621.
    TOLIMIERI R and WINOGRAD S. Computing the ambiguity surface[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985, 33(5): 1239-1245. doi: 10.1109/ TASSP.1985.1164688.
    AUSLANDER L and TOLIMIERI R. Computing decimated finite cross-ambiguity functions[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988, 36(3): 359-364. doi: 10.1109/29.1532.
    OZDEMIR A K and ARIKAN O. Fast computation of the ambiguity function and the Wigner distribution on arbitrary line segments[J]. IEEE Transactions on Signal Processing, 2001, 49(2): 381-393. doi: 10.1109/78.902121.
    TAO R, ZHANG W Q, and CHEN E Q. Two-stage method for joint time delay and Doppler shift estimation[J]. IET Radar, Sonar Navigation, 2008, 2(1): 71-77. doi: 10.1049 /iet-rsn:20060014.
    SHIN D C and NIKIAS C L. Complex ambiguity functions using nonstationary higher order cumulant estimates[J]. IEEE Transactions on Signal Processing, 1995, 43(11): 2649-2664. doi: 10.1109/78.482115.
    NIU X, CHING P C, and CHAN Y T. Wavelet based approach for joint time delay and Doppler stretch measurements[J]. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(3): 1111-1119. doi: 10.1109/7. 784079.
    BELANGER S P. Multipath TDOA and FDOA estimation using the EM algorithm[C]. IEEE International Conference on Acoustics, Speech, and Signal Processing, Minneapolis, USA, 1993: 168-171. doi: 10.1109/ICASSP.1993.319621.
    GILAVERT C, MOUSSAOUI S, and IDIER J. Efficient Gaussian sampling for solving large-scale inverse problems using MCMC[J]. IEEE Transactions on Signal Processing, 2015, 63(1): 70-80. doi: 10.1109/TSP.2014.2367457.
    BATES B C and CAMPBEL E P. A Markov chain Monte Carlo scheme for parameter estimation and inference in conceptual rainfall-runoff modeling[J]. Water Resources Research, 2001, 37(4): 937-947. doi: 10.1029/2000WR900363.
    林彦, 王秀坛, 彭应宁, 等. 基于MCMC的线性调频信号最大似然参数估计[J]. 清华大学学报(自然科学版), 2004, 44(4): 511-514. doi: 10.3321/j.issn:1000-0054.2004.04.020.
    LIN Yan, WANG Xiutan, PENG Yingning, et al. Maximum likelihood parameter estimation of chirp signals based on MCMC[J]. Journal of Tsinghua University(Science and Technology), 2004, 44(4): 511-514. doi: 10.3321/j.issn:1000- 0054.2004.04.020.
    NG W, REILLY J P, KIRUBARAJAN T, et al. Wideband array signal processing using MCMC methods[J]. IEEE Transactions on Signal Processing, 2005, 53(2): 411-426. doi: 10.1109/TSP.2004.838934.
    李晶, 赵拥军, 李冬海. 基于马尔科夫链蒙特卡罗的时延估计算法[J]. 物理学报, 2014, 63(13): 67-73. doi: 10.7498/aps.63. 130701.
    LI Jing, ZHAO Yongjun, and LI Donghai. Time delay estimation using Markov chain Monte Carlo method[J]. Acta Physica Sinica, 2014, 63(13): 67-73. doi: 10.7498/aps.63. 130701.
    PINCUS M. A closed form solution of certain programming problems[J]. Operations Research, 1968, 16(3): 690-694. doi: 10.1287/opre.16.3.690.
  • 加载中
计量
  • 文章访问数:  1389
  • HTML全文浏览量:  106
  • PDF下载量:  434
  • 被引次数: 0
出版历程
  • 收稿日期:  2016-01-13
  • 修回日期:  2016-06-08
  • 刊出日期:  2016-11-19

目录

    /

    返回文章
    返回