AccuNav
High-Precision Localization System.
“Achieved sub-meter positional accuracy by integrating PPK correction streams with real-time mapping.”
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Pioneering Sub-Meter PPK Satellite Localization
Standard commercial GPS sensors suffer from atmospheric distortion and multi-path reflection errors (drift of 3 to 10 meters). In this innovation project, we engineered a configuration and visualization platform integrating SUPARCO's PakRehber PPK (Post-Processed Kinematic) correction data to achieve true sub-meter spatial accuracy on standard mobile devices.
Project at a Glance
A high-precision geolocation and configuration management system leveraging SUPARCO's PakRehber PPK service to achieve sub-meter positional accuracy.
Geospatial Localization & Satellite PPK Corrections
Field Surveyors, Agriculture & Engineering
Q2 - Q3
Sub-meter positional precision achieved without requiring costly specialized differential GPS hardware.
The Problem
Engineering-grade surveying, precision farming, and infrastructure inspection require accuracy within 50 centimeters. Specialized RTK hardware costs upwards of $10,000 per unit, while standard smartphone GPS drifts up to 10 meters, rendering consumer devices useless for professional surveying.
Commercial smartphone GPS lacks ionospheric and orbital error correction.
Dedicated RTK rovers are prohibitively expensive and require bulky ground base stations.
Field workers lack intuitive mobile visualization tools to calibrate coordinates in real-time.
Manual post-processing of raw RINEX satellite data is slow and error-prone.
Goals
Technical Goals
- Ingest SUPARCO PakRehber satellite correction telemetry streams in near-real-time.
- Compute PPK differential corrections to reduce positional variance below 0.8 meters.
- Responsive Flutter mobile client displaying live position overlays on satellite maps.
- Offline-first coordinate caching with automatic sync upon cellular reconnection.
Business Goals
- Democratize high-precision geospatial surveying at a fraction of hardware costs.
- Accelerate field data collection workflows for civil engineering and agriculture.
- Demonstrate domestic satellite navigation capability for enterprise operations.
My Role
Lead Geospatial Engineer
Core Responsibilities
- Engineered the Node.js backend parsing PPK correction data streams.
- Built the cross-platform Flutter application for Android and iOS.
- Integrated Mapbox vector tiles with dynamic high-precision coordinate overlays.
- Calibrated coordinate conversion mathematics (WGS84 to local datum projections).
Primary Focus Areas
Solution
AccuNav bridges consumer mobile sensors with national satellite correction base stations. The mobile app logs raw GNSS pseudorange measurements, pairs them with SUPARCO PakRehber base station correction streams, and computes corrected sub-meter coordinates in real-time.
PPK Correction Engine
Applies differential carrier-phase calculations to eliminate satellite clock and atmospheric delay errors.
Fluid Flutter Mapping UI
Custom vector rendering of waypoints, survey boundaries, and precision confidence circles.
Offline Sync Engine
Ensures surveyors working in remote rural zones can record high-precision points with zero cellular signal.
Architecture & Data Flow
Real-time pipeline bridging raw mobile GNSS logs, PakRehber base station telemetry, Node.js processing, and Flutter map visualizer.
Raw GNSS Logging
Android GNSS API / FlutterMobile app records raw satellite pseudoranges and carrier phase data.
Correction Stream Ingestion
Node.js / WebSocketsNode.js server streams PakRehber reference station ephemeris and correction data.
Kinematic Differential Calculation
PostGIS / C++ Math RoutinesAlgorithm applies differential corrections, resolving integer ambiguities and computing sub-meter coordinates.
Real-Time Map Visualization
Flutter / Mapbox SDKCorrected coordinates rendered on Mapbox with visual precision confidence ellipses.
Core Features
Sub-Meter Positional Precision
<0.8m accuracyReduces standard mobile GPS drift from 5-10 meters down to 0.6-0.8 meters through PPK corrections.
Real-Time Precision Confidence Ellipse
Visual error marginVisual indicator on the map showing current spatial error margins based on active satellite geometry.
Offline Survey Waypoint Logging
Offline-first capabilityCapture survey markers, polygon boundaries, and field notes without needing an active internet connection.
CAD & GIS Export Integration
Instant GIS exportExport survey projects directly to Shapefile, GeoJSON, and AutoCAD DXF formats.
Engineering Decisions
Flutter for Mobile Client vs Native Android/iOS
Why: Flutter enabled 100% shared mathematical coordinate transformation logic and identical Mapbox rendering across both operating systems.
Challenges
Satellite Signal Multipath: Urban buildings and trees causing signal reflection and erratic coordinate jumps.
Implemented Kalman filtering algorithms to smooth trajectory paths and reject high-residual satellite observations.
Smooth, reliable waypoint plotting even in challenging terrain.
Implementation Timeline
Correction Stream Decoding
- PakRehber stream parser
- Raw GNSS Android logging harness
- Coordinate conversion logic
Mobile Interface & Mapbox Tiles
- Flutter UI scaffolding
- Mapbox vector layer integration
- Offline SQLite storage
Calibration & Accuracy Verification
- Field test against calibrated survey benchmark points
- Kalman filter tuning
- GIS export engine
Results & Metrics
Consistent sub-meter precision verified across field survey test trials.
Compared to purchasing dedicated commercial RTK surveying receivers.
Zero data loss during extensive remote rural field operations.
Screenshots
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Live High-Precision Map View & Satellite Telemetry
Map showing active satellite constellations and confidence precision radius.
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Survey Boundary Plotting & GeoJSON Export
Interactive polygon marker plotting for agricultural parcel boundary surveys.
Demo Video
AccuNav Field Test Walkthrough: 2-minute video demonstrating real-time coordinate correction in an agricultural field trial.
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Demonstration Highlights:
Lessons Learned
Accessing raw pseudorange GNSS measurements on consumer mobile devices requires handling device-specific clock drift variations.
Kalman filtering is mandatory to suppress multipath noise when operating near physical obstructions.
Tech Stack
Mobile Client
Backend & Telemetry
Geospatial & Satellite
Business Impact
Proved that consumer smartphones paired with regional correction satellite feeds can perform engineering-grade surveying tasks.