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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

Math
Prediction/correctionTrajectory SVGResidual chartEstimate CSVMeasurement CSVJSON receipt

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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.

Read the editor guide for Kalman sensor fusion