State Estimation and Error Analysis of a Single State Dynamic System with Sensor Data Using Kalman Filter
Keywords:
Estimator, kalman error analysis, kalman filter, kalman optimization, measurement noise covariance, state estimation, process noise covariance.Abstract
Kalman Filter is used in system estimation
applications today like state estimation, load flow analysis,
harmonic estimation, digital signal processing, sensor
integration, Navigational Systems, etc. In using a Kalman Filter
the user has to give the parameters relating the estimates of
process and measurement noise along with system state
modeling. The values of process and measurement noise
covariance are usually not available beforehand and have to be
estimated, usually by hit or trial method. This involves heavy
computation, as two variables have to be estimated for optimal
filtering independently. For multi-state systems this value
further increases the computation time. This paper presents the
application of Kalman Filter to a simple one state problem. This
paper, through using simulations, finds relationships between
the two different parameters Q (Process Noise Covariance) and
R (Measurement Noise Covariance). This results in reduction of
computation time. The proposed scheme’s low complexity and
robustness makes it practical for real implementations.
Downloads
Downloads
Published
Issue
Section
License
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
