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

带有信息反馈的最优异步递推航迹融合算法

文成林 葛泉波 刘双剑

文成林, 葛泉波, 刘双剑. 带有信息反馈的最优异步递推航迹融合算法[J]. 电子与信息学报, 2009, 31(9): 2123-2131. doi: 10.3724/SP.J.1146.2008.00857
引用本文: 文成林, 葛泉波, 刘双剑. 带有信息反馈的最优异步递推航迹融合算法[J]. 电子与信息学报, 2009, 31(9): 2123-2131. doi: 10.3724/SP.J.1146.2008.00857
Wen Cheng-lin, Ge Quan-bo, Liu Shuang-jian. Optimal Asynchronous Recursive Track Fusion with Global Feedback[J]. Journal of Electronics & Information Technology, 2009, 31(9): 2123-2131. doi: 10.3724/SP.J.1146.2008.00857
Citation: Wen Cheng-lin, Ge Quan-bo, Liu Shuang-jian. Optimal Asynchronous Recursive Track Fusion with Global Feedback[J]. Journal of Electronics & Information Technology, 2009, 31(9): 2123-2131. doi: 10.3724/SP.J.1146.2008.00857

带有信息反馈的最优异步递推航迹融合算法

doi: 10.3724/SP.J.1146.2008.00857

Optimal Asynchronous Recursive Track Fusion with Global Feedback

  • 摘要: 现有的异步航迹融合算法大都采用无全局信息反馈的设计框架,并且忽略各异步传感器局部预测航迹误差间的相关性,加之考虑上述相关性的最优整体航迹融合算法的实时性难以被保证,从而导致局部传感器估计精度低、稳定性差、全局估计的最优性丧失和差的应用性等不足。为此,本文在引入全局信息反馈的基础上,同时考虑各局部预测航迹误差相关性,在融合估计误差协方差矩阵迹最小意义下,建立一种带有全局反馈机制的最优异步递推航迹融合算法。文中不仅对各种算法的次优或最优原理及性能进行了详细的分析与讨论,理论证明和仿真结果也表明了该文算法的有效性和优越性。
  • Shao Kai, Zhang Hong-Wei, Liang Yan, Zhang Zhi-zhong,and Luo Jiang-tao. Data fusion in wireless sensor network: Asurvey[J]. Journal of Chongqing University of Posts andTelecommunications (Nature Science), 2006, 18(1): 53-59.[2]文成林, 周东华. 多尺度估计理论及应用[M]. 北京 : 清华大学出版社, 2002 : 221-233.Wen Cheng-lin and Zhou Dong-hua. Multiscale EstimateTheory and Application[M]. Beijing : Tsinghua UniversityPress, 2002: 221-233.[3]韩崇昭, 朱洪艳, 段战胜等. 多源信息融合[M]. 北京: 清华大学出版社, 2006: 338-361.Han Chong-zhao, Zhu Hong-yan, and Duan Zhan-sheng.Multi-source Information Fusion [M]. Beijing : TsinghuaUniversity Press, 2006: 338-361.[4]Yan Li-ping, Liu Bao-sheng, and Zhou Dong-hua. Themodeling and estimation of asynchronous multiratemultisensor dynamic systems [J]. Aerospace Science andTechnology, 2006(10): 63-71.[5]Alouani A T and Rice T R. On Optimal asynchronous trackfusion[C]. 1st IEEE Australian Symposium on Data Fusion,Adelaide, SA, Australia, 1996 : 147-152.[6]徐毓, 金以慧. 多传感器异步关联航迹的融合[J]. 系统工程与电子技术, 2003, 25(11): 1318-1320.Xu Yu and Jin Yi-hui. Asynchronous suboptimal fusion ofcorrelated target tracks from multisensors[J]. SystemsEngineering and Electronics of China, 2003, 25(11):1318-1320.[7]郭徽东, 章新华, 宋元, 陆强强. 多传感器异步数据融合算法[J].电子与信息学报.2006, 28(9):1546-1549浏览[8]文成林, 葛泉波. 异步多传感器系统的分步式预测融合[J]. 中南大学学报, 2005, 32(专辑1): 652-653.Wen Cheng-lin and Ge Quan-bo. Step by Step predictionfusion based on asynchronous multisensor system[J]. J. Cent.South Univ. of China (Science and Technology), 2005,32(Special 1): 652-653.[9]刘双剑, 倪红霞, 葛泉波, 文成林. 基于传感器网络的异步最优预测航迹融合算法[J]. 中南大学学报, 2007, 38(增刊1):798-803.Liu Shuang-jian, Ni Hong-xia, Ge Quan-bo, and WenCheng-lin. Asynchronous optimal predict fusion of targettracks for sensor networks [J]. J.Cent. South Univ. of China(Science and Technology), 2007, 38(Suppl.1): 798-803.[10]Alouani A T, Gray J E, and Mccabe D H. Theory ofdistributed estimation using multiple asynchronous sensors[J].IEEE Transactions on Aerospace and Electronic Systems.2005, 41(2):717-722[11]Jin Hong, Qiu Hong-Zhuan, and Zhang Hong-Yue. Fusionalgorithm of correlated local estimates for federated filter[C].In: Proceedings of the 3rd Asian Control Conference,Shanghai, 2000: 1428-1433.[12]Bar-Shalom Y.[J].Li X R, and Kirubarajan T. Estimation withApplication to Tracking and Navigation [M]. New York: JohnWiley Sons.2001,:-
  • 加载中
计量
  • 文章访问数:  3494
  • HTML全文浏览量:  114
  • PDF下载量:  626
  • 被引次数: 0
出版历程
  • 收稿日期:  2008-07-07
  • 修回日期:  2009-05-18
  • 刊出日期:  2009-09-19

目录

    /

    返回文章
    返回