Earticle

초록

영어

A multi-target localization algorithm based on compressed sensing was proposed in this paper. The issue of multi-target localization was transformed into compressed sensing. The algorithm greatly reduced the amount of wireless network’s communication data by transferring most of the computing work to the central server. This method made full uses of the priori information of the signal and the support set. It combined Kalman filter with Bayesian compressed sensing to improve the localization accuracy and noise immunity. Simulation results showed that the proposed method has good noise immunity, robustness and localization accuracy compared with traditional localization methods.

목차

Abstract
 1. Introduction
 2. Localization Model based on Compressed Sensing
  2.1. Compressed Sensing
  2.2. Modeling by Compressed Sensing
  2.3. Multi-target CS Localization Algorithm
 3.The Simulation Results Analysis
  3.1. Localization Results of MCL Algorithm
  3.2. Reconstruction Error Comparison of KNN, BP, KFCS and MCL
 4. Summary
 References

키워드

저자

• Nan Xue [ College of Electrical & Electronic Engineering, Harbin University of Science and Technology, China ]
• Yan Hu [ College of Electrical & Electronic Engineering, Harbin University of Science and Technology, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605