presentation - sensor network approach to gps rtk
DESCRIPTION
Sensor Network Approach to GPS RTKTRANSCRIPT
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Sensor Network Approach to GPS RTK
New Navigator Seminar
20th June 2007
Nicholas Zinas
Supervisors: Prof. Paul Cross
Dr Marek Ziebart
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OverviewI) The concept of Network RTK
- Network Correction Computation
- Network Correction Interpolation
- Network Correction Transmission
II) UCL RTK Software & Results
- Concept of the RTK software
- Models and Algorithms
- Results
III) Current & Future Work
- Theoretical Development
- Research Experiment
- Future Work
Overview
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GPS Positioning
GPS Positioning
Absolute Positioning Relative/Differential Positioning
One Reference
StationMultiple Reference StationsPseudoRanges
Carrier Phases
&Pseudoranges
Stand Alone Precise Point Positioning
Static
Fast Static
OTF Kinematic
Stop & Go
PseudoRangesCarrier Phases &
Pseudoranges
Network
RTK
WADGPSLADGPS
CORS
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Network RTK Benefits
1. Less Reference stations needed Low infrastructure Cost
2. Improved Error Modeling increased availability and reliability
3. Increased Reference Station – Rover distance separation
4. Single Receiver cm positioning lower costs
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Network RTK
Network RTK
Network Correction
ComputationCorrection Interpolation Transmission of Corrections
Linear
Combination
Model
FKP VRS
Fix Network
Ambiguities
Computation
of Network
Corrections
State
Space
Observation
Space
Network RTK
Network Correction
ComputationCorrection Interpolation Transmission of Corrections
Linear
Interpolation
Algorithm
Low Order
Surface
Model
Fix Network
Ambiguities Grid Based
Parameteris
ation
Broadcast
(One way
Communication)
Bilinear
Communication
1 1 1 1 1 1( )i i i i i i
AB AB AB AB AB AB
fN dT dI
c
1 1 1 1i i i i
AB AB AB AB
fV N
c
1i
A ROVER A ROVER A ROVERV a X b Y
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Models
Troposphere ESA Zenith Delay model, Global Mapping Function (GMF - Boehm et al, 2006)
Ionosphere Klobuchar Broadcast Model (double differencing, ionospheric free linear
combination)
GPS Antenna Model: IGS Antex file corrections (APC &PCV)
Geoid Model : Implementation of EGM96
RTK Software (2)
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Algorithms
Point Positioning
SP3 (BRDC) orbit files implementation
LAMBDA method for Ambiguity Resolution
Reference Station Ambiguity Resolution: spanning tree algorithm, closed loop approach
Single Epoch Carrier Phase Positioning
Carrier phase and pseudorange (L1,L2,L1+L2 fixed solutions)
Multiple Epoch Carrier Phase Positioning:Helmert Blocking: Ambiguities Global Parameters, Rover position Local
(L1+L2 fixed solutions)
RTK Software (3)
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Algorithms (3)
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Baseline 18km (Models:None)
-0.100000
-0.080000
-0.060000
-0.040000
-0.020000
0.000000
0.020000
0.040000
0.060000
00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00
Time
De
via
tio
n f
rom
SK
I-P
RO
co
ord
ina
tes
ΔLat
ΔLong
ΔHeight
Results
Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 2 consecutive epochs
Baseline : Barking – London (OS Stations)
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Results (2)
Baseline: 18 km (Models: Ionosphere,Troposphere,Antenna)
-0.080000
-0.060000
-0.040000
-0.020000
0.000000
0.020000
0.040000
0.060000
00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00
Time
Dev
iati
on
fro
m S
KI-
PR
O c
oo
rdin
ates
ΔLat
ΔLong
ΔHeight
Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 2 consecutive epochs
Baseline : Barking – London (OS Stations)
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Results (3)
Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 4 consecutive epochs
Baseline : Barking – London (OS Stations)
Baseline 18km (Models: Ionosphere,Troposphere,Antenna)
-0.080000
-0.060000
-0.040000
-0.020000
0.000000
0.020000
0.040000
0.060000
0.080000
00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00
Time
De
via
tio
n f
rom
SK
I-P
RO
Co
ord
ina
tes
ΔLat
ΔLong
ΔHeight
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Results (4)
Number of Satellites used in Multiple Epoch Carrier Phase Positioning
0
2
4
6
8
10
12
00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00
Time
Nu
mb
er o
f Sat
ellit
es
Satellites
Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 4 consecutive epochs
Baseline : Barking – London (OS Stations)
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Single Epoch Carrier Phase Positioning (L1+L2) (carrier phase & pseudorange)
Baseline : Barking – London (OS Stations)
Results (5)
Baseline 18km (Models: Ionosphere,Troposphere,Antenna)
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00
T i me
Devia
tion from
SK
I-P
RO
com
pute
d C
oordin
ate
s
DLat
DLong
DHeight
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Results (6)
ΔLatitude
1σ 2σ
ΔLongitude
1σ 2σ
ΔHeight
1σ 2σ
Ambiguity Success
Rate
Single Epoch
Carrier Phase
Positioning0.0091
0.0182
0.0037
0.0074
0.0162
0.0323
91%
Maximum 4
Consecutive
Epochs
(All Models)
0.0086
0.0173
0.0038
0.0076
0.0159
0.0318
57 %
Maximum 2
Consecutive
Epochs
(All Models)
0.0083
0.0167
0.0036
0.0072
0.0151
0.0302
43%
Maximum 2
Consecutive
Epochs
(No Models)
0.0102
0.0204
0.0046
0.0092
0.0186
0.0372
13%
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Research Experiment (1)
CORS : 3
- 1 ZMAX Net (JGC)
- 1 Trimble NetR5 (Geot)
- 1 Trimble 4000SSI
(Dionysus Satellite Observatory)
GPS Receivers : 14
- 12 Trimble R8/5800
- 2 Trimble 5700Reference Station Networks
a) JGC-DION-S1
b) JGC-DION-GEOT
c) GEOT-DION-S1
d) JGC-DION-GEOT-S1
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Dionysus Satellite Observatory
Dionysus – dion: 159.713m
Dionysus – JGC: 11604.133m
Dionysus – S1 : 22001.990m
Dionysus – Geot : 9771.100m
Research Experiment (2)
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Dionysus Satellite Observatory
Research Experiment (3)
Dionysus – R12 : 789.034m
Dionysus – R11 : 20331.590m
Dionysus – R6 : 13676.251m
Dionysus – R8 : 13125.525Dionysus – R9 : 10801.607
Dionysus – R7 : 9295.421m
Dionysus – R4 : 8459.406m
Dionysus – R1 : 8309.600m
Dionysus – R2 : 7594.345m
Dionysus – R10 : 7327.178
Dionysus – R3 : 5530.964m
Dionysus – R5 : 5108.805m
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Research Questions
How many users needed in order to see improvement in the computation of the
Rover position?
Does the geometry of the rovers affect the solution?
What is the Ambiguity Success Rate we can achieve in Single Epoch Carrier
Phase Positioning?
How can we take advantage of the redundancy in the equations in terms of
modelling various error sources?
Since we know the ambiguities between the users can we use this system to
determine the atmospheric influence on GPS signals in a regional level?
What is the magnitude of the improvement, if any?
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Implementation of the concept in the UCL-RTK software
Test the results against GIPSY computed rover positions
Compare the position time series of R12 against single baseline RTK
positioning
Generate VRS stations for each of the rovers and compare against VRS positioning
Aim is to develop a robust centralized Network RTK positioning approach where all the appropriate steps will be carried out at a central processing facility, transmitting to the user just its final position.
Future Work