Abstract
This letter develops the Kalman and unbiased finite impulse response filtering algorithms for linear discrete-time state-space models with Gauss-Markov colored process noise (CPN) employing state differencing. The approach avoids problems caused by matrix augmentation, but requires solving a nonsymmetric algebraic Riccati equation to specify the system matrix modified for CPN. Higher accuracy of the algorithms proposed is demonstrated by simulation. A comparative analysis of filtering estimates is provided based on navigation data of walking humans.
Original language | English |
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Article number | 8638977 |
Pages (from-to) | 548-551 |
Number of pages | 4 |
Journal | IEEE Signal Processing Letters |
Volume | 26 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2019 Apr |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Kalman filter
- State-space
- colored process noise
- state differencing
- unbiased FIR filter
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Applied Mathematics