Robust Incremental Kalman Filter for the System under Poor Observation Conditions
- Resource Type
- Conference
- Authors
- Zhang, Bo; Ma, Guangpeng; Sun, Xiaojun
- Source
- 2020 Chinese Automation Congress (CAC) Automation Congress (CAC), 2020 Chinese. :5490-5493 Nov, 2020
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Kalman filters
Filtering algorithms
Mathematical model
Filtering
Upper bound
Measurement uncertainty
Noise measurement
systems under poor observation condition
incremental filtering
robustness
- Language
- ISSN
- 2688-0938
When the measurement equation or noise variance of the system is uncertain, the performance of the filter will deteriorate and even cause the divergence of the filter. The introduction of incremental equation is an effective method to eliminate the unknown measurement error. In this paper, a robust incremental Kalman filter based on incremental equations is proposed for linear discrete systems with unknown measurement errors and unknown noise variances, and its robustness is analyzed. Simulation results show the effectiveness and feasibility of the proposed algorithm.