Assessment of a New Rover Enhanced

Network Based RTK GNSS Data Processing

Strategy

Nicholas Zinas

Ph.D. Researcher

Department of Civil, Environmental and Geomatic Engineering

UCL, UK

ION GNSS 2009, Savannah-Georgia

Overview

• A very short Introduction to Network RTK

• Sensor Networks and Multiple Rover Concepts

• The Multiple Rover Positioning Algorithm

• Sample Test Network

• Results

• Conclusions and Recommendations

2

Evolution of GPS Networks

3

2. Single Baseline RTK positioning using the Pseudoranges

(DGPS)

1. Active GPS reference Stations

3. Single Baseline RTK positioning using the Carrier Phase

and Pseudorange observables (OTF RTK)

4. RTK clusters broadcasting corrections from the closest

reference station

RTK Clusters Vs RTK Networks

• Early RTK Networks appear around 2003.

RTK Clusters RTK Networks

Vs

RTK Corrections provided

based on one reference

station

RTK Corrections provided

based on most or all

reference stations

One Way Communication

Links

One Way Or Two Way

Communication Links

Processing at User site Processing either at the

user site or at a CPF4

Network RTK Processes

1. Resolution of the the Ambiguities between the Reference

Stations

2. Generation of Corrections

3. Transmission of Corrections

• Errors = Carrier Phase Range Observations – Geometric Range

• Errors = As derived from Linear Combinations

• Errors = Estimated as Unknown Parameters

•FKP, VRS, MAC…5

Transmission of Corrections

6

FKP - Reference stations estimate errors and broadcast

correction parameters to users

VRS - Estimates network errors and interpolates to

approximate position of rover

MAC – Broadcasts raw observations from Master

Station and correction differences from the Auxiliary

Stations

Although the Network Assists the Users

Users do not assist the network.

7

Sensor Networks & Multiple Rover

Algorithms (1)

A wireless sensor network (WSN) is a wireless network

consisting of spatially distributed autonomous devices using

sensors to cooperatively monitor physical or environmental

conditions ,…., at different locations [Kay et al, 2004].

A Real Time GNSS Network consists

of spatially distributed sensors of

GNSS signals.

Users of the network Additional Sensors

8

Sensor Networks & Multiple Rover

Algorithms (2)

Lachapelle (1993), introduces a quadruple receiver

configuration approach to reliably resolve ambiguities on the fly

using the integer ambiguities closure constraints.

Luo (2003), presents a method to realise the relative precise

positioning of multiple moving platforms (MultiKin)

Alves (2004), proposes a tightly coupled approach where the

precise rover positions are estimated with network ambiguities

Luo (1999), shows that the time to fix can be reduced by 50%

in the case of three moving platforms.

9

The Rover Enhanced Network Based

GNSS RTK Algorithm*

…requires a centralized

network architecture with two

way communication means

established and that all

available data is collected at

the Central Processing Facility

(CPF).

*Algorithm implemented in the UCL GNSS software suite10

Step 1: Multiple Epoch Reference Station

Ambiguity Resolution

Helmert-Wolf

Method

ambiguities resolved?no yes

Collect

Next

epochBack

substitutionLAMBDA

Global

ParametersDD Ambiguities

Local

ParametersRelative Zenith

Ionospheric

Estimates

Float

estimates

Collect data for a number

of epochs

11

Step 2: Filtering & Interpolation of the

Ionospheric Estimates

The moving window is defined by the number of epochs

(n) needed for ambiguity resolution

An Exponential Moving Average is applied on the moving

window time series

A Distance Weighted Linear Interpolation is then

performed (Gao et al 1997)*12

A) Reference

Station

System &

User System

C) Increase

redundancy using

information from all

Ref Stations

Step 3: Multiple Rover Positioning: Method (1/2)

B CA

B) Selection of:

Rover ‘Shortest Walk’

Primary Rover

Primary Ref Station

A

1

13

Unknown Parameters

Rover position vectors

Between Rover ‘Shortest Walk’

Primary Rover to Primary Ref Station

Single Epoch Weighted

Least Squares Estimator

Step 3: Multiple Rover Positioning: Method (2/2)

N

N

14

South California Integrated GNSS Test Sub

Network (1/2)

15

South California Integrated GNSS Test Sub

Network (2/2)December 2007

Starting:00.00 UTC

Period: 2hrs 8 mins

3 Reference

Stations

4 Rovers

Distances between the

Reference Stations

Ambiguities for the

shortest RS baselines

resolved after 41 mins. 16

106km 72km

69km

Double Difference Residuals

0102030405060708090

-0.1

-0.05

0

0.05

172860 174710 176560 178410 180260

E L

E V

A T

I O

N

(de

gre

es)

DD

re

sid

ual

s (m

ete

rs)

G P S T I M E (sec)

L1 L2

PRN 21

PRN 18

0102030405060708090

-0.1

-0.05

0

0.05

172860 174710 176560 178410 180260

E L

E V

A T

I O

N

(de

gre

es)

DD

re

sid

ual

s (m

ete

rs)

GPS T I M E (sec)

L1 L2

PRN 21

PRN 18

(1σ) (rms)

L1 = 1.2cm 1.35cm

L2 = 2.2cm 2.39cm

(1σ ) (rms)

L1 = 1. 7cm 1.48cm

L2 = 2.7cm 2.49cm

106km

72km

17

Relative Zenith Ionospheric Estimates

-0.1

-0.05

0

0.05

0.1

172860 174710 176560 178410 180260met

ers

G P S T I M E (sec)

-0.1

-0.05

0

0.05

0.1

172860 174710 176560 178410 180260met

ers

G P S T I M E (sec)

106km

72km (rms)

L1 = 1.81cm

(rms)

L1 = 2.92cm

18

Multiple Rover Positioning (1)

Rover Baselines

Primary Rover – Primary RS

Multiple Rover

Approach

Vs

• Single Baseline

Solution (SBS)

• Single Rover Network

Solution (SNS)

RTK processing simulated by

Single Epoch Positioning

19

31km

13km

19km

25km

Multiple Rover Positioning (2)

Station SBS SNS Multiple

Rover

BGIS

RHCL

OXYC

WRHS

94.1%

85.6%

75.8%

87.5%

99.3%

99.3%

96.0%

79.5%

99.3%

99.3%

99.3%

97.4%

Ambiguity success rates for each rover applying the

relative zenith ionospheric estimates

20

Multiple Rover Positioning (3)

-0.05

-0.03

-0.01

0.01

0.03

0.05

-0.04 -0.02 0 0.02 0.04

No

rth

ings

(m)

Eastings (m) -0.05

-0.03

-0.01

0.01

0.03

0.05

-0.04 -0.02 0 0.02 0.04

No

rth

ings

(m)

Eastings (m)-0.05

-0.03

-0.01

0.01

0.03

0.05

-0.04 -0.02 0 0.02 0.04N

ort

hin

g s

(m)

Eastings (m)

RHCL

(MultiRov)

OXYC

(MultiRov)

WRHS

(MultiRov)

21

Conclusions & Recommendations (1/2)

Multiple Rover Approach Improved Ambiguity

Success Rates

Greater impact for rovers

operating outside the

network

Geometry of Solution

affects the precision

22

Performs better than

both SBS and SNS

solutions

Conclusions & Recommendations (2/2)

23

Multiple Rover Approach Beneficial for Operators

that want to expand their

sphere of influence

May prove advantageous

for coastal or near shore

surveys

Improved atmospheric

modeling

Single Frequency users

could also benefit

Thank you !

Questions?

24