Unbiased FIR Filtering for Time-Stamped Discretely Delayed and Missing Data

Karen J. Uribe-Murcia, Yuriy S. Shmaliy, Choon Ki Ahn, Shunyi Zhao

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


The unbiased finite impulse response (UFIR) filtering approach is developed for discrete-time state-space models with time-stamped discretely delayed and missing data. The model with k-step-lags in observations is transformed to have no latency and expanded on a finite horizon of N most recent data points. It is shown that the optimal horizon for the UFIR filter is practically k-invariant, unlike the tuning factor of the H&inf; filter. Higher robustness of the UFIR filter against the Kalman and H&inf; filters is justified theoretically in uncertain environments with discretely delayed and missing data. Experimental verification is provided based on GPS-based tracking of a moving vehicle to demonstrate a good agreement with the theory.

Original languageEnglish
Article number8815824
Pages (from-to)2155-2162
Number of pages8
JournalIEEE Transactions on Automatic Control
Issue number5
Publication statusPublished - 2020 May


  • Delayed data
  • H&inf; filter
  • Kalman filter (KF)
  • robustness
  • unbiased finite impulse response (FIR) filter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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