On reliability measures for kinematic surveys

M. Jia, B. Montgomery, Xiaoli Ding

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)


Kalman filter models are usually used to process and analyze the data from kinematic (dynamic) surveys. The reliability of a kinematic survey system is an important factor to consider when designing the survey. This paper looks into the various reliability measures for Kalman filter based kinematic survey models when errors within the current epoch only are considered, including the redundancy numbers and measures derived based on the concept of minimum detectable errors. The properties of these measures are discussed. The relationships between the different definitions of the measures are also examined. The theoretical equivalence of the reliability measures derived based on the predicted residuals and those on filtered residuals is proved. Examples are given to illustrate the applications of the reliability measures.
Original languageEnglish
Pages (from-to)37-44
Number of pages8
Issue number1
Publication statusPublished - 1 Dec 1998

ASJC Scopus subject areas

  • Geography, Planning and Development


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