1. GPS Data Collection: During a drone flight, the UAV is equipped with a Global Navigation Satellite System (GNSS), which includes GPS receivers to capture positioning data. The GPS receivers record the drone's coordinates and other relevant information during the entire flight. 2. In-Flight Kinematics: The drone's flight dynamics, including its position, orientation, and velocity, are continuously recorded by the onboard sensors. 3. Post-Processing: After the drone completes its mission, the collected GNSS data and in-flight kinematics data are downloaded to a computer for post-processing. Specialized software is used to precisely synchronize the GPS data with the in-flight kinematics data. 4. Base Station Corrections: PPK often involves the use of a ground-based reference station with known coordinates as a base station. The corrections from the base station are applied to the drone's GNSS data, compensating for errors introduced by factors such as atmospheric conditions and satellite signal delays. 5. Centimeter-Level Accuracy: By post-processing the data and incorporating corrections, PPK achieves significantly higher accuracy compared to real-time kinematics (RTK) methods. The resulting drone survey data can reach centimeter-level accuracy in terms of spatial positioning. 6. Reduced Reliance on Real-Time Corrections: Unlike Real-Time Kinematics (RTK), which requires continuous communication with a base station during the flight, PPK eliminates the need for real-time corrections. This allows for more flexibility in flight planning and remote location mapping. 7. Applications: PPK is widely used in applications such as photogrammetry, surveying, mapping, and precision agriculture. It enhances the accuracy and reliability of geospatial data collected by drones, making it invaluable for industries that demand high-precision mapping. In summary, the PPK method is a powerful technique that enhances the accuracy of drone mapping by carefully post-processing GNSS data, correcting for errors, and achieving centimeter-level precision in the final geospatial outputs. Image: heliguy.com