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| Content Provider | IET Digital Library |
|---|---|
| Author | Cho, Seong Yun |
| Abstract | Infinite impulse response (IIR) filter generally used in estimation, positioning, etc. has problems in that, when there is a modeling error even if the system is completely observable, the estimates may converge to incorrect values or the varying values cannot be estimated quickly. The finite impulse response (FIR) filter, which has been investigated as a method to solve this problem, has faster estimation performance than the IIR filter in the presence of modelling error, but there is a limit to the convergence characteristic of the state variables. In this paper, a non-linear FIR smoothing (NFS) filter is proposed to overcome the limitation of the state variable convergence characteristic of the FIR filter. The proposed NFS filter adds the smoothing concept to the modified receding horizon Kalman FIR filter. In order to verify the performance of the NFS filter, this filter is applied to a delay-tolerant integrated navigation system using magnetic compass (MC) of which error is difficult to be modelled accurately. If an un-modeled jump or ramp error occurs in the MC measurement, it shows that the NFS filter can estimate the measurement error more accurately than the FIR filter as well as the IIR filter through a simulation. |
| Starting Page | 882 |
| Ending Page | 888 |
| Page Count | 7 |
| ISSN | 17518784 |
| Volume Number | 12 |
| e-ISSN | 17518792 |
| Issue Number | Issue 8, Aug (2018) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-rsn/12/8 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2017.0551 |
| Journal | IET Radar, Sonar & Navigation |
| Publisher Date | 2018-04-19 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Delay-tolerant Dead Reckoning DR/GPS Integrated Navigation Filtering Method in Signal Processing Finite Impulse Response Filter FIR Filter Global Positioning System Global Positioning System Integrated Navigation System IIR Filter Infinite Impulse Response Filter Kalman Filter Modified Receding Horizon Kalman FIR Filter NFS Filter Nonlinear FIR Smoothing Filter Satellite Communication System State Variable Convergence Characteristic |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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