Advanced Search
Volume 33 Issue 4
May  2011
Turn off MathJax
Article Contents
Wang Xiao-ye, Wang Zheng-ou. An Improved K-Nearest Neighbor Algorithm[J]. Journal of Electronics & Information Technology, 2005, 27(3): 487-491.
Citation: Xu Zhen-Hua, Huang Jian-Guo, Zhang Qun-Fei. New Method for Distributed and Quantitative Estimation Fusion of Multi-sensor Based on EM Algorithm[J]. Journal of Electronics & Information Technology, 2011, 33(4): 977-981. doi: 10.3724/SP.J.1146.2010.00599

New Method for Distributed and Quantitative Estimation Fusion of Multi-sensor Based on EM Algorithm

doi: 10.3724/SP.J.1146.2010.00599
  • Received Date: 2010-06-08
  • Rev Recd Date: 2011-01-03
  • Publish Date: 2011-04-19
  • For multi-sensor distributed and quantitative estimation fusion problem of underwater target detection, a model of distributed and quantitative estimation fusion is established. The channel noise and its statistical property which is not fully known to fusion center is considered, The superiority of Expectation Maximization (EM) algorithm completely is used in parameter estimation problem when the observation data is missing. A new algorithm of distributed and quantitative estimation fusion is proposed based on EM algorithm. In this method, the unknown parameters of underwater acoustic channel noise and the quantization probability of local quantizer are modeled as the binary Gaussian mixture model parameters. Then, the invariance of the maximum likelihood estimation is used to get the result of the estimation fusion. Simulation results show that the estimation performance of the new algorithm is comparable to the methods which need ideal channel condition when the number of local sensors samples is larger than 5000 and the signal to noise ratio is higher than 6 dB. This new algorithm provides a theoretical basis for realizing the distributed and quantitative estimation fusion system of underwater target detection.
  • 王志胜, 姜斌, 甄子洋. 融合估计与融合控制[M]. 北京:科学出版社, 2009: 36-38.[3]Fang Jun and Li Hong-bin. Distributed estimation of Gauss- Markov random fields with one-bit quantized data[J].IEEE Signal Processing Letters.2010, 17(5):449-452[4]Chen Hao and Varshney P K. Performance limit for distributed estimation systems with identical one-bit quantizers[J].IEEE Transactions on Signal Processing.2010, 58(1):466-471[5]Ribeiro A and Giannakis G. Bandwidth-constrained distributed estimation for wireless sensor networkspart II: unknown probability density function [J].IEEE Transactions on Signal Processing.2006, 54(7):2784-2796[7]Ramanan S and Walsh J M. Distributed estimation of channel gains in wireless sensor networks[J].IEEE Transactions on Signal Processing.2010, 58(6):3097-3107[8]Senol H and Tepedelenlioglu C. Performance of distributed estimation over unknown parallel fading channels [J].IEEE Transactions on Signal Processing.2008, 56(12):6057-6068[9]Arindam k. das mehran mesbahiDistributed linear parameter estimation over wireless sensor networks[J].. IEEE Transactions on Aerospace and Electronic Systems.2009, 45(4):1293-1305[10]Cattivelli F S and Sayed A H. Diffusion LMS strategies for distributed estimation[J].IEEE Transactions on Signal Processing.2010, 58(3):1035-1048[11]Song En-bin, Zhu Yun-min, Zhou Jie, and You Zhi-sheng. Minimum variance in biased estimation with singular fisher information matrix[J].IEEE Transactions on Signal Processing.2009, 57(1):376-381[12]Ribeiro A and Giannakis G B. Bandwidth-constrained distributed estimation for wireless sensor networkspart I: Gaussian case [J].IEEE Transactions on Signal Processing.2006, 54(3):1131-1143[13]Fang Jun and Li Hong-bin. Distributed adaptive quantization for wireless sensor networks: from Delta modulation to maximum likelihood[J].IEEE Transactions on Signal Processing.2008, 56(10):5246-5257[14]Aysal T C and Barner K E. Constrained decentralized estimation over noisy channels for sensor networks [J].IEEE Transactions on Signal Processing.2008, 56(4):1398-1410
  • Cited by

    Periodical cited type(6)

    1. 李晓花,苏骏,李秀秀. 强干扰环境单观测站水下纯方位多目标跟踪. 计算机工程与应用. 2021(17): 253-259 .
    2. 田政,姜林君,程显超,韩旭. 传感器测量衰减下的水下目标纯方位跟踪算法. 海洋测绘. 2020(05): 53-57 .
    3. 黄璐. 一种智能的尘埃监测及告警系统. 数字技术与应用. 2015(11): 78-79+81 .
    4. 闫永胜,王海燕,申晓红. 小规模传感器网络远程目标探测系统的建模与性能分析. 电子与信息学报. 2014(07): 1625-1630 . 本站查看
    5. 周方,张小凤. EM-ACO算法及其在多重超声回波参数估计中的应用. 陕西师范大学学报(自然科学版). 2013(06): 27-32 .
    6. 赵泉华,李玉,何晓军,宋伟东. 基于Voronoi几何划分和EM/MPM算法的多视SAR图像分割. 遥感学报. 2013(04): 841-854 .

    Other cited types(8)

  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (3498) PDF downloads(1002) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return