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Appendix B. Typical examples
We test a series of IGS static stations in 2020. Then we compare the static PPP-AR results with IGS SINEX solutions. The figures listed below (Figure B-1) record the difference between our solutions and IGS SINEX solutions in east/north/up directions, respectively. The X axis, which denotes day of year, ranges from 1 to 366. The Y axis denotes different stations. The color map, which ranges from blue to red, represents the difference value in the unit of centimeter.
Figure B-1 Difference between PRIDE PPP-AR Ⅲ solution and IGS SINEX solution of various stations.
PRIDE PPP-AR Ⅲ can still process super-high-rate data, up to 50 Hz. Then we test HLFY station (1300 kilometers away from epicenter), to presenting the 2011 earthquake of the Pacific coast of Tōhoku occurred in Japan at 05:46:24 (UTC) on March 11, 2011 with a magnitude of MW 9.0. As shown in Figure B-2, the evident horizontal vibration is reach about 10 centimeters.
Figure B-2 Time series of super-high-rate kinematic solutions (cm) in east, north, and up components at station HLFY on March 11, 2011
In an aerial photogrammetry experiment, high-dynamic PPP has been realized. The observation period is on November 27, 2017 and lasting about 5 hours. The sampling rate is 0.5 seconds. The trajectory of the aircraft is shown in Figure B-3. And we use relative positioning solutions of WayPoint software (a commercial positioning software) as the reference solutions, whose maximum baseline length is up to 170 kilometers. As shown in Figure B-4, In the airborne experiment with less shielding, the positioning accuracy is basically the same with that of commercial software. Besides, fixed ambiguity can also significantly improve the positioning accuracy in high-dynamic data solutions.
Figure B-3 Trajectory of the aircraft in high-dynamic aerial photogrammetry experiment
![image95](https://private-user-images.githubusercontent.com/67955813/411952141-8195b07d-29aa-42af-a638-dc216f1c5fa6.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.QA9r1KhO6ua4N_n_76ANDwJL9P_OmcgvXhq5geM6gw0)
Figure B-4 Location differences between PRIDE PPP-AR and WayPoint software
- Introduction
- Fundamentals
- Program structure and algorithm
- Technical Aspects
- PRIDE PPP‐AR for GUI