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KALMAN FILTER + SENSOR FUSION
Kalman Filter Sensor Fusion Lab
Run a visual Kalman filter sensor-fusion lab with noisy measurements, filtered trajectory, innovation residuals, covariance diagnostics, estimate CSV, measurement CSV, Markdown notes and JSON receipt.
Reviewed 2026-06-28
MathPrediction/correctionTrajectory SVGResidual chartEstimate CSVMeasurement CSVJSON receipt
FORMULA CONTRACT
A useful estimator shows both the path and the correction math.
The lab uses x_k = F x_(k-1), P_k = F P F^T + Q and K = P H^T (H P H^T + R)^-1. It reports measurement RMSE, filter RMSE, innovation residuals and covariance radius so the filter can be tuned.