A nonlinear tracking algorithm with range-rate measurements based on unbiased measurement conversion

Lianmeng Jiao, Quan Pan, Yan Liang, Feng Yang

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

19 Scopus citations

Abstract

The three-dimensional CMKF-U with only position measurements is extended to solve the nonlinear tracking problem with range-rate measurements in this paper. A pseudo measurement is constructed by the product of range and rangerate measurements to reduce the high nonlinearity of the rangerate measurements with respect to the target state; then the mean and covariance of the converted measurement errors are derived by the measurement conditioned method, showing better consistency than the transitional nested conditioning method; finally, the sequential filter was used to process the converted position and range-rate measurements sequentially to reduce the approximation error in the second-order EKF. Monte Carlo simulations show that the performance of the new tracking algorithm is better than the traditional one based on CMKF-D.

Original languageEnglish
Title of host publication15th International Conference on Information Fusion, FUSION 2012
Pages1400-1405
Number of pages6
StatePublished - 2012
Event15th International Conference on Information Fusion, FUSION 2012 - Singapore, Singapore
Duration: 7 Sep 201212 Sep 2012

Publication series

Name15th International Conference on Information Fusion, FUSION 2012

Conference

Conference15th International Conference on Information Fusion, FUSION 2012
Country/TerritorySingapore
CitySingapore
Period7/09/1212/09/12

Keywords

  • measurements
  • nonlinear
  • range-rate
  • RCMKF-U
  • tracking
  • unbiased measurement conversion

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