Implementation of Kalman Filter with Python Language
2012
In this paper, we investigate the implementation of a Python code for a Kalman Filter using the Numpy package. A Kalman Filtering is carried out in two steps: Prediction and Update. Each step is investigated and coded as a function with matrix input and output. These different functions are explained and an example of a Kalman Filter application for the localization of mobile in wireless networks is given.
Keywords:
- Kalman filter
- Fast Kalman filter
- Invariant extended Kalman filter
- Alpha beta filter
- Python (programming language)
- Computer science
- Machine learning
- NumPy
- Theoretical computer science
- Simultaneous localization and mapping
- Extended Kalman filter
- Artificial intelligence
- Algorithm
- Real-time computing
- Distributed computing
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
4
References
7
Citations
NaN
KQI