Presentation - Sensor Network Approach to GPS RTK

Page 1

Sensor Network Approach to GPS RTK New Navigator Seminar th 20 June 2007

Nicholas Zinas Supervisors: Prof. Paul Cross Dr Marek Ziebart


Overview

Overview I) 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


GPS Positioning

GPS Positioning

Absolute Positioning

PseudoRanges

Carrier Phases &Pseudoranges

Relative/Differential Positioning

One Reference Station

Static Fast Static Stand Alone

OTF Kinematic Stop & Go

Multiple Reference Stations

PseudoRanges

Carrier Phases & Pseudoranges

Precise Point Positioning CORS LADGPS

WADGPS Network RTK


Network RTK Benefits

1. 2. 3. 4.

Less Reference stations needed Low infrastructure Cost Improved Error Modeling increased availability and reliability Increased Reference Station – Rover distance separation Single Receiver cm positioning lower costs


Network RTK

Network RTK

Network Correction Computation

Fix Fix Network Network Ambiguities Ambiguities

Computation of Network Corrections

State Space

N

1i AB

Transmission of Corrections

Correction Interpolation

Observation Space

Linear Interpolation Algorithm

1i A ROVER

V

f 1i 1i 1i 1i 1i   AB  (  AB  dTAB  dI AB   AB ) c f 1i 1i 1i 1i VAB   AB   AB  N AB c

Linear Combination Model

Low Order Surface Model

Grid Based Parameteris ation

Broadcast (One way Communication)

Bilinear Communication

FKP

VRS

 aX A ROVER  bYA ROVER



RTK Software (2)

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 (3)

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)



Algorithms (3)


Results Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 2 consecutive epochs Baseline : Barking – London (OS Stations) Baseline 18km (Models:None) 0.060000

Deviation from SKI-PRO coordinates

0.040000

0.020000

ΔLat 0.000000 00:00:00

04:48:00

09:36:00

14:24:00

19:12:00

00:00:00

04:48:00

ΔLong

-0.020000

-0.040000

ΔHeight

-0.060000

-0.080000

-0.100000

Time


Results (2) Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 2 consecutive epochs Baseline : Barking – London (OS Stations) Baseline: 18 km (Models: Ionosphere,Troposphere,Antenna)

Deviation from SKI-PRO coordinates

0.060000

0.040000

ΔLat

0.020000

0.000000 00:00:00

04:48:00

09:36:00

14:24:00

19:12:00

00:00:00

ΔLong 04:48:00

-0.020000

ΔHeight -0.040000

-0.060000

-0.080000

Time


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

Deviation from SKI-PRO Coordinates

0.060000 0.040000

ΔLat

0.020000 0.000000 00:00:00

04:48:00

09:36:00

14:24:00

19:12:00

00:00:00

ΔLong 04:48:00

-0.020000 -0.040000

ΔHeight

-0.060000 -0.080000 Time


Results (4) Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 4 consecutive epochs Baseline : Barking – London (OS Stations) Number of Satellites used in Multiple Epoch Carrier Phase Positioning 12

Number of Satellites

10

8

6

Satellites

4

2

0 00:00:00

04:48:00

09:36:00

14:24:00 Time

19:12:00

00:00:00

04:48:00


Results (5) Single Epoch Carrier Phase Positioning (L1+L2) (carrier phase & pseudorange) Baseline : Barking – London (OS Stations)

Baseline 18km (Models: Ionosphere,Troposphere,Antenna)

Deviation from SKI-PRO computed Coordinates

0.06 0.04 0.02 0 00:00:00 -0.02

DLat 04:48:00

09:36:00

14:24:00

19:12:00

00:00:00

04:48:00

DLong DHeight

-0.04 -0.06 -0.08 T i me


Results (6)

ΔLatitude

1σ Single Epoch Carrier Phase 0.0091 Positioning Maximum 4 Consecutive Epochs (All Models) Maximum 2 Consecutive Epochs (All Models) Maximum 2 Consecutive Epochs (No Models)

ΔLongitude

ΔHeight

2σ 1σ

0.0037 0.0182

0.0086

0.0162 0.0074

0.0038 0.0173

0.0083

0.0159

0.0036

0.0102

57 % 0.0318

0.0151 0.0072

0.0046 0.0204

91% 0.0323

0.0076

0.0167

Ambiguity Success Rate 2σ

43% 0.0302

0.0186 0.0092

13% 0.0372




Research Experiment (1)

CORS : 3 - 1 ZMAX Net (JGC) - 1 Trimble NetR5 (Geot) - 1 Trimble 4000SSI (Dionysus Satellite Observatory)

GPS Receivers : 14 Reference Station Networks a) JGC-DION-S1 b) JGC-DION-GEOT c) GEOT-DION-S1 d) JGC-DION-GEOT-S1

- 12 Trimble R8/5800 - 2 Trimble 5700


Research Experiment (2)

Dionysus – dion: 159.713m

Dionysus – JGC: 11604.133m

Dionysus Satellite Observatory

Dionysus – Geot : 9771.100m

Dionysus – S1 : 22001.990m


Research Experiment (3)

Dionysus – R12 : 789.034m Dionysus – R11 : 20331.590m Dionysus – R6 : 13676.251m Dionysus – R8 : 13125.525 Dionysus – 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

Dionysus Satellite Observatory


Research Questions

How many users needed in order to see improvement in the computation of the Rover position?

What is the magnitude of the improvement, if any? 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?


Future Work

 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.


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