PPolySim OS
Controls & Robotics Pack · Multi-Solver

State Estimator

Sensor fusion. This multi-solver chains 1 solvers into a single guided workflow — run each step in order and carry the result forward.

Workflow steps
  1. kalman-filter
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1

Kalman Filter

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Kalman FilterLive

Controls

Presets

The Kalman filter fuses a motion model with noisy measurements to track a hidden state optimally. Each step it predicts, then corrects using the Kalman gain — trusting the measurement more when the model is uncertain, and vice versa. It smooths the jittery sensor (gray) into a clean estimate (cyan) that hugs the truth. The math behind GPS, radar, and spacecraft navigation.

▶ Run in Python

Data Inspector

Measurement RMSE0.0
Kalman RMSE0.0
Noise reductionNaN%

Governing equation

Reading this result: Measurement noise dwarfs process noise, so the Kalman gain stays small — the filter leans on its motion model and smooths the jitter hard.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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More in the Controls & Robotics pack

Frequently asked questions

What is the State Estimator multi-solver?
State Estimator is a guided workflow that chains 1 individual PolySim solvers into one end-to-end analysis, piping each result into the next step.
Is it free to use?
Yes. Every step runs entirely in your browser using real numerics — no install, no account, no cloud cost. Custom or private solver packs are available as a paid service.