Process / pipelineOptimal state estimation
Kalman Filter for Signal Tracking
The Kalman filter is a recursive algorithm that optimally estimates the state of a linear dynamic system from noisy measurements, minimizing mean-square error. Introduced by Rudolf Kalman in 1960, it revolutionized control theory, navigation, and signal processing by enabling real-time optimal estimation for time-varying systems. The Kalman filter became indispensable for spacecraft tracking, GPS navigation, and countless modern applications.
Open in MethodMindSoonVideoSoon
Read the full method
Members only
Sign inSign in with a free account to read this section.
Sources
- Kalman, R. E. (1960). A New Approach to Linear Filtering and Prediction Problems. Journal of Basic Engineering, 82(1), 35–45. DOI: 10.1115/1.3662552 ↗
- Grewal, M. S., & Andrews, A. P. (2015). Kalman Filtering: Theory and Practice with MATLAB (4th ed.). Wiley-IEEE Press. link ↗