Sensors' optimal dimensionality compression matrix in estimation fusion

被引：45
|
作者：
Song, EB [1 ]
Zhu, YM [1 ]
Zhou, E [1 ]
机构：
[1] Sichuan Univ, Dept Math, Chengdu 610064, Peoples R China
来源：
AUTOMATICA | 2005年 / 41卷 / 12期
基金：
高等学校博士学科点专项科研基金; 中国国家自然科学基金;
关键词：
multisensor estimation fusion; linear compression; minimum variance estimation;
D O I：
10.1016/j.automatica.2005.07.011
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
When there exists the limitation of communication bandwidth between sensors and a fusion center, one needs to optimally pre-compress sensor outputs-sensor observations or estimates before sensors' transmission to obtain a constrained optimal estimation at the fusion center in terms of the linear minimum error variance criterion. This paper will give an analytic solution of the optimal linear dimensionality compression matrix for the single sensor case and analyze the existence of the optimal linear dimensionality compression matrix for the multisensor case, as well as how to implement a Gauss-Seidel algorithm to search for an optimal solution to linear dimensionality compression matrix. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2131 / 2139
页数：9
相关论文
共 50 条
  • [1] Optimal dimensionality reduction of sensor data in multisensor estimation fusion
    Zhu, YM
    Song, EB
    Zhou, J
    You, ZS
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2005, 53 (05) : 1631 - 1639
  • [2] Optimal sensor data linear compression in multisensor estimation fusion
    Zhu, YM
    Song, EB
    Zhou, J
    You, ZS
    42ND IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-6, PROCEEDINGS, 2003, : 5807 - 5812
  • [3] Optimal linear estimation fusion - Part VI: Sensor data compression
    Zhang, KS
    Li, XR
    Zhang, P
    Li, HF
    FUSION 2003: PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE OF INFORMATION FUSION, VOLS 1 AND 2, 2003, : 221 - 228
  • [4] Closed-Form Solution for Optimal Compression Matrix Design in Distributed Estimation
    Zhang, Linxia
    Niu, Dunbiao
    Song, Enbin
    Shi, Qingjiang
    IEEE ACCESS, 2019, 7 : 5045 - 5056
  • [5] Distributed Dimensionality Reduction Fusion Estimation: An H∞ Approach
    Chen, Bo
    2020 IEEE 16TH INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION (ICCA), 2020, : 266 - 271
  • [6] Fusion estimation under binary sensors
    Zhang, Yuchen
    Chen, Bo
    Yu, Li
    AUTOMATICA, 2020, 115
  • [7] Fusion Estimation for Two Sensors with Nonuniform Estimation Rates
    Zhang, Wen-An
    Liu, Steven
    Chen, Michael Z. Q.
    Yu, Li
    2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2012, : 4083 - 4088
  • [8] Image compression with matrix detail estimation
    Urbano-Sanchez, E
    Perez-Meana, H
    Nakano-Miyatake, M
    MSMW'04: FIFTH INTERNATIONAL KHARKOV SYMPOSIUM ON PHYSICS AND ENGINEERING OF MICROWAVES, MILLIMETER, AND SUBMILLIMETER WAVES, SYMPOSIUM PROCEEDINGS, VOLS 1 AND 2, 2004, : 925 - 927
  • [9] IMM fusion estimation with multiple asynchronous sensors
    Hu, Yanyan
    He, Xiao
    Zhang, Lan
    Sun, Changyin
    SIGNAL PROCESSING, 2014, 102 : 46 - 57
  • [10] Dimensionality reduction, compression and quantization for distributed estimation with wireless sensor networks
    Schizas, Ioannis D.
    Ribeiro, Alejandro
    Giannakis, Georgios B.
    WIRELESS COMMUNICATIONS, 2007, 143 : 259 - +
12345