1. PPP Workshop: Reaching Full Potential
Single-Station Ionosphere Modelling for Precise Point Positioning Paul Collins, Reza Ghoddousi-Fard, Simon Banville François Lahaye Geodetic Survey Division, Natural Resources Canada, Ottawa, Ontario, Canada
PPP Workshop: Reaching Full Potential
June 12-14, 2013, Ottawa, Canada

2. Introduction
A clearer understanding of the role of the ionosphere in high-precision GNSS permits:
rapid PPP-AR (under some circumstances),
those ‘circumstances’ look suspiciously like RTK…
One goal of this presentation is to retain:
a distinction between PPP & RTK techniques.
Motivation:
What was the point of GPS in the first place?
Why the desire for dense reference networks?

3. PPP/RTK Review Two kinds of RTK: Differentiator between RTK and PPP:
Observation Space Representation (OSR-RTK)
State Space Representation (SSR-RTK)
Preferably not PPP-RTK, because…
Differentiator between RTK and PPP:
Network Size:
RTK: local/regional.
PPP: (wide-area)/global.
Network Dependence:
RTK User: No network, no solution.
PPP User: What network?

4. Ionosphere/Ambiguity Relationship
Ionosphere-free model
code s = 10cm; phase s = 1mm
L1 iono bias = 2cm/0.12TECU
Ionosphere-fixed model

5. Four-observable PPP model
Original three-observable decoupled clock model:
Split widelane-phase/narrowlane-code observable:
Result: phase ionosphere.
Biased by datum ambiguities and hardware delays.

6. Slant ionosphere estimates
float sigma
fixed sigma

7. Applying the Constraints
Ionospheric Slant delays contain:
Integer-biased satellite phase equipment delay.
Common to all stations.
Integer-biased station phase equipment delay.
Unique to all stations, can change on solution reset.
Use single-differences to eliminate station bias:
Add as pseudo-observations: ,

8. PPP-ICAR Methodology LAMBDA float solution fixed solutions AR LAMBDA
float/fixed solutions
constrained solutions
ion AV AR

9. PPP-ICAR Testing Local stations around Ottawa.
JO2P (30sec); NRC1 (1sec).
Two receivers driven on the Rideau Canal (frozen).
0015, 0019 (1sec).
frozen surface should be ‘level’. S1
S2a
S2c
S2b
JO2P
NRC1
0015
0019
8.5km

10. Solution 1 JO2P → NRC1 (2D-Horiz.)
67% ~1cm
95% ~2cm

11. Solution 1 JO2P → NRC1 (3D)
67% ~3cm
95% ~7cm

12. Solution 2: Height Estimates
PPP(SMD) HGT = ± 0.10
PPP(ICAR) HGT = ± 0.05
RTK(NRC1) HGT = ± 0.02

13. Solution 2: JO2P→0019→NRC1→0015 Ion Ion NRC1 JO2P 0019 (kinematic)
NRC1 (stationary)
Ion
0015 (kinematic)
Ion

14. RTK Network
Master
User
Ref.

15. PPP Local ‘Network’
User
“Ref.”

16. PPP Local Augmentation

17. Point Positioning Scalability
STD
PPP
PPP−AR
PPP− ICAR
Broadcast Orbits & Clocks
pseudoranges
Precise Orbits & Clocks
carrier phases
Decoupled Clock Model
equipment delays
Ionosphere Constraints
ambiguity constraints

18. Conclusions Key Points:
Know the Ionosphere, Know the Ambiguities.
Constrain ambiguity resolution, not the observation model.
Using external ionosphere constraints for AR pushes PPP as close to RTK as possible, without being RTK.
An RTK solution is still (a little) better!
In principle,
Permits a generalised local augmentation concept:
Peer-to-Peer in nature,
no centralised solution or coordination required;
state space representation of information.
Regular PPP-AR solution possible at all times and all locations.

19. Future Work
Analyse Ionosphere Spatial Gradients

20. Acknowledgements Pierre Héroux and Christian Prévost Thank You
Rideau Canal dataset
Thank You