In finite impulse response (FIR) filtering using finite recent measurements, horizon size (window length) is an important parameter that influences estimation performance. In this paper, to improve the estimation performance of a nonlinear FIR filter, we propose an alternative nonlinear FIR filter called horizon group shift (HGS) FIR filter and adopt a novel method to manage horizon size. The HGS-FIR filter adjusts horizon size based on the likelihood of observation and achieves a significant performance improvement. We verified that the HGS-FIR filter exhibits excellent performance, exceeding that of existing nonlinear filters, including the extended Kalman filter, unscented Kalman filter, and particle filter.
|Number of pages||13|
|Journal||Measurement: Journal of the International Measurement Confederation|
|Publication status||Published - 2014 Nov|
Bibliographical noteFunding Information:
This work (NRF-2013R1A1A2008698) was supported by General Research Program through NRF grant funded by the Ministry of Education. This work was also financially supported in part by the Ministry of Trade, Industry & Energy (MOTIE) , Korea Institute for Advancement of Technology (KIAT) and Honam Institute for Regional Program Evaluation through the Leading Industry Development for Economic Region.
- Finite impulse response filter
- Horizon group shift
- Nonlinear filter
- State estimation
ASJC Scopus subject areas
- Electrical and Electronic Engineering