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Releases: Ali-Marandi/kalman-sensor-js
Releases · Ali-Marandi/kalman-sensor-js
Release list
Kalman Sensor Studio v4.1 - Universal Edition
Enhanced Signal Processing
New in v4.1
- Transfer Entropy Analysis: Shannon entropy, mutual information, directional TE for sensor coupling detection
- Adaptive Fuzzy Kalman Filter: Fuzzy innovation-based Q/R adaptation with 3 fuzzy rules, dynamic sigma scaling
Features
- Zero new dependencies (pure JavaScript)
- 4 new IPC handlers and UI panels
Kalman Sensor Studio v4.0.0
Kalman Sensor Studio v4.0.0
What is New
- Complete rewrite as Electron desktop app
- Pure JS Kalman filter: Scalar (1-State) + Constant Velocity (2-State)
- RTS Smoother for backward-pass smoothing
- Signal Generator with 7 types (sine, cosine, square, sawtooth, step, ramp, constant)
- Grid search auto-tuner with RMSE optimization
- Interactive Q/R sliders with real-time updates
- Uncertainty visualization with plus/minus 1-sigma bands
- Innovation sequence analysis
- CSV import/export via native dialogs
- Professional cyan-themed dark UI
- Zero runtime dependencies
Tech Stack
- Electron 28 (desktop shell)
- Pure JavaScript (zero npm dependencies for core)
- Chart.js 4.4.7 (visualization)
- electron-builder (Windows .exe packaging)
Build on Windows
npm install
npm startFor portable .exe:
npm run build-portableKalman Sensor Studio 1.0.0
Kalman Sensor Studio 1.0.0
First desktop release: a portable Windows application for real-time Kalman filtering, tuning and analysis of noisy sensor streams.
Download
Kalman-Sensor-Studio-win32-x64.zip -> unzip -> run Kalman Sensor Studio.exe. Portable, no installer, no runtime dependencies.
Highlights
- Live streaming workspace: sine / ramp / step / random-walk sources, adjustable noise, 5-120 Hz sample rate, outlier injection
- Two filter models: scalar constant-state and 2-state constant-velocity with full covariance propagation
- Interactive log-scale tuning of process noise
qand measurement noiser - Auto-tune: grid search minimising one-step-ahead prediction RMS error
- Optional RTS (Rauch-Tung-Striebel) offline smoother
- +/-1 sigma confidence band and a dedicated innovation (residual) chart
- Live metrics: RMSE vs ground truth (raw vs filtered), noise reduction, Kalman gain, covariance, sample count
- CSV/TSV import to replay real sensor logs; export filtered session to CSV and chart to PNG
- Keyboard shortcuts and native menus (Space, Ctrl+O, Ctrl+S, Ctrl+T, Ctrl+R)
Library
kalman.js now exports ScalarKalman, ConstantVelocityKalman, rtsSmooth, autoTune and metrics, still dependency-free. All tests pass with npm test.
MIT licensed.