Skip to main navigation Skip to search Skip to main content

Data Processing and Fusion Working Mechanism Scheme of MIMU Sensor Network

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aiming at the engineering environment that requires a wide range of laying, long working hours, high accuracy and reliability, a sensor network framework model was proposed, which can effectively acquire the collected information and meet the real-time data transmission function. At the same time, a data processing and fusion scheme was proposed to remove trend and gross error terms from the static collected data. The trend test and ADF test data are used to meet the stability requirements. Then a multi-redundancy data fusion mechanism is applied for data fusion of preprocessed data. Finally, via the Allan variance method, the random noise characteristics of the gyro was analyzed, and the data quality and fusion effect are evaluated. Experimental results show that the designed sensor network can effectively collect real-time information, and the data processing and fusion working mechanism can effectively reduce noise and improve data quality.

Original languageEnglish
Title of host publicationProceedings of the 39th Chinese Control Conference, CCC 2020
EditorsJun Fu, Jian Sun
PublisherIEEE Computer Society
Pages3092-3097
Number of pages6
ISBN (Electronic)9789881563903
DOIs
StatePublished - Jul 2020
Externally publishedYes
Event39th Chinese Control Conference, CCC 2020 - Shenyang, China
Duration: 27 Jul 202029 Jul 2020

Publication series

NameChinese Control Conference, CCC
Volume2020-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference39th Chinese Control Conference, CCC 2020
Country/TerritoryChina
CityShenyang
Period27/07/2029/07/20

Keywords

  • Data fusion
  • Data processing
  • Sensor networks

Fingerprint

Dive into the research topics of 'Data Processing and Fusion Working Mechanism Scheme of MIMU Sensor Network'. Together they form a unique fingerprint.

Cite this