KalmanVisualizer

An interactive graphical representation of kalman computations

Kalman Filter Explanation:

The Kalman Filter is a recursive algorithm used to estimate the state of a linear dynamical system from a series of noisy measurements.

The Filter implemented in this project is a simple one-dimensional filter and can be broken down into the following equations:

1. Prediction Step:

   • Predicted State Estimate:

     

   • Predicted Estimate Covariance:

     

   Where Q is the process variance

2. Update Step (Compute Kalman Gain):

   • Kalman Gain:

     

   • Updated State Estimate:

     

   • Updated Covariance Estimate:

     

   Where R is the measurement variance