Missile-borne radar data filtering algorithm based on the "current" statistical model

  • Huifeng Li*
  • , Chao Li
  • *Corresponding author for this work

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

Abstract

An Extended Kalman Filter (EKF) based on the "current" statistical model is developed for detection of highly maneuvering target using missile-borne Pulse Doppler radar. The online recursive filtering algorithm was also developed to estimate the four dimensional variable: relative distance, velocity, azimuth and elevation angles. Identifying the mean acceleration of maneuvering targets real-timely while estimating the state could improve the tracking performance. Simulation results show that the "current" statistical model based on EKF filtering algorithm is adaptive to high target maneuvering.

Original languageEnglish
Title of host publicationMaterials Science and Information Technology, MSIT2011
Pages6965-6973
Number of pages9
DOIs
StatePublished - 2012
Event2011 International Conference on Material Science and Information Technology, MSIT2011 - Singapore, Singapore
Duration: 16 Sep 201118 Sep 2011

Publication series

NameAdvanced Materials Research
Volume433-440
ISSN (Print)1022-6680

Conference

Conference2011 International Conference on Material Science and Information Technology, MSIT2011
Country/TerritorySingapore
CitySingapore
Period16/09/1118/09/11

Keywords

  • "current"statistical model
  • EKF
  • Highly maneuvering
  • Missile-borne PD radar

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