A Kalman filter elegantly solves this by acting as an optimal sensor fusion algorithm. It balances what your knowledge of physics says should happen against what your imperfect instruments say is happening. It calculates a weighted average between your prediction and your measurement based on which one is more trustworthy at that exact millisecond. The 4 Essential Concepts of Phil Kim’s Approach
He explains why the equations work using simple physical examples (like tracking a moving car or estimating a battery's state of charge) before diving into code. A Kalman filter elegantly solves this by acting
Calculates the expected new position or velocity based on the last known state. The 4 Essential Concepts of Phil Kim’s Approach
% Define the system matrices A = [1 1; 0 1]; B = [0.5; 1]; H = [1 0]; Q = [0.001 0; 0 0.001]; R = 0.1; B = [0.5