Kalman Filter Source Code Package

This package provides complete source code for Kalman filter implementation, shared for community use and learning. The Kalman filter is an optimal recursive algorithm for state estimation, widely employed in control systems and navigation applications. It operates by combining prior knowledge with real-time measurements through recursive updates of state estimates and covariance matrices to enhance estimation accuracy. The implementation includes core algorithmic components such as: - State prediction and update equations - Covariance matrix propagation - Measurement innovation calculations - Optimal Kalman gain computation Understanding Kalman filter algorithms is crucial for developing robust control and navigation systems. This source code package offers a practical implementation framework, facilitating both educational purposes and real-world applications. The code is structured to demonstrate key functions including initialization, prediction steps, and correction phases with clear variable naming and commenting. Available for download and sharing, this resource supports engineers and researchers in implementing Kalman filters for various estimation problems while providing insights into algorithm optimization and performance tuning aspects.