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WIDS RSSI Localization & CRLB Uncertainty (2D)

Interactive 2D WIDS simulator: drag a rogue Wi-Fi transmitter across a monitored floor plan while five sensors measure RSSI, invert the log-distance path-loss model, multilaterate its position with a Gauss-Newton refinement, and draw the Cramer-Rao uncertainty ellipse for the estimate.

Cybersecurity2DAdvanced60 FPS📱 Mobile-adapted⇄ 3D version

A rogue or "evil-twin" access point is one of the most common wireless attack surfaces. This 2D simulator visualizes the defensive countermeasure — a distributed Wireless Intrusion Detection System (WIDS) — from directly overhead. Five fixed sensors measure the rogue transmitter's RSSI, invert the log-distance path-loss model into per-sensor distance estimates, and multilaterate a position fix through a linear solve followed by nonlinear Gauss-Newton refinement. Unlike a single point estimate, this version also propagates the sensors' measurement noise into a Cramer-Rao lower bound on the estimator's own covariance, drawn as a 95% confidence ellipse. Drag the rogue transmitter around the floor plan or re-scatter the sensors to see how both fading noise and pure sensor geometry (GDOP) independently degrade localization confidence.

⚙ Under the hood

2D top-down WIDS simulator: drag a rogue Wi-Fi transmitter across a monitored floor plan while five sensors measure RSSI, invert the log-distance path-loss model, multilaterate its position with a linear solve refined by Gauss-Newton, and draw the Cramer-Rao (CRLB) 95% uncertainty ellipse around the estimate to expose geometric dilution of precision (GDOP).

wireless securityWIDSRSSItrilaterationrogue APwifiCRLBGDOPGauss-Newton

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install