Förfiltrering av singnaler med kalmanfilter
(1969) In MSc ThesesDepartment of Automatic Control
- Abstract
- In this paper we discuss the problem of finding a suitable filter used as prefilter at digital Kalman filtering. The process is described by a stochastic state model. Two different filters are analyzed: a low-pass filter and a mean value filter. Especially we examine optimal choices of the parameters of the filters i.e. optimal integration area in the mean value filter and optimal time constant in the low-pass filter. In the analysis of the mean value filter it is supposed that the integration area h doesn't exceed the length of the sampling interval T. The analysis is carried out in a more general way and the results are applied to special dynamical systems: 1. A system of first order which can be described by a constant + noise. 2. A... (More)
- In this paper we discuss the problem of finding a suitable filter used as prefilter at digital Kalman filtering. The process is described by a stochastic state model. Two different filters are analyzed: a low-pass filter and a mean value filter. Especially we examine optimal choices of the parameters of the filters i.e. optimal integration area in the mean value filter and optimal time constant in the low-pass filter. In the analysis of the mean value filter it is supposed that the integration area h doesn't exceed the length of the sampling interval T. The analysis is carried out in a more general way and the results are applied to special dynamical systems: 1. A system of first order which can be described by a constant + noise. 2. A system of second order which is oscillating and disturbed by noise. We find in these cases optimal choices of h and a (a denotes the time constant in the low-pass filter). In some cases it seems optimal to take h > T. This appears especially when the sampling interval is short. At long sampling intervals, on the other hand, we often get a considerable improvement by choosing h < T in comparison with the case h = T. In the studied cases the low-pass filter has proved to be the best. However, we get only a slight decrease in the information function when we choose a mean value filter with a suitable integration time. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8850809
- author
- Bengtsson, Gunnar
- supervisor
- organization
- year
- 1969
- type
- H3 - Professional qualifications (4 Years - )
- subject
- publication/series
- MSc Theses
- report number
- TFRT-5058
- ISSN
- 0346-5500
- language
- Swedish
- id
- 8850809
- date added to LUP
- 2016-03-29 16:53:12
- date last changed
- 2016-03-29 16:53:12
@misc{8850809,
abstract = {{In this paper we discuss the problem of finding a suitable filter used as prefilter at digital Kalman filtering. The process is described by a stochastic state model. Two different filters are analyzed: a low-pass filter and a mean value filter. Especially we examine optimal choices of the parameters of the filters i.e. optimal integration area in the mean value filter and optimal time constant in the low-pass filter. In the analysis of the mean value filter it is supposed that the integration area h doesn't exceed the length of the sampling interval T. The analysis is carried out in a more general way and the results are applied to special dynamical systems: 1. A system of first order which can be described by a constant + noise. 2. A system of second order which is oscillating and disturbed by noise. We find in these cases optimal choices of h and a (a denotes the time constant in the low-pass filter). In some cases it seems optimal to take h > T. This appears especially when the sampling interval is short. At long sampling intervals, on the other hand, we often get a considerable improvement by choosing h < T in comparison with the case h = T. In the studied cases the low-pass filter has proved to be the best. However, we get only a slight decrease in the information function when we choose a mean value filter with a suitable integration time.}},
author = {{Bengtsson, Gunnar}},
issn = {{0346-5500}},
language = {{swe}},
note = {{Student Paper}},
series = {{MSc Theses}},
title = {{Förfiltrering av singnaler med kalmanfilter}},
year = {{1969}},
}