International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B6. Istanbul 2004 
  
project is currently in Phase 2, in which the main effort is to 
refine the models incorporated in the Phase 1 release, to ensure 
high fidelity modelling. 
The FURLONG Simulation Facility: The British National 
Space Centre funded Future Real-time Location and Navigation 
study (FURLONG) was concerned with simulating the signals 
of future satellite positioning systems (the proposed European 
Galileo system and the Modernised GPS) in order to assess the 
precision and reliability of future real time positioning services. 
It based this work on research and practical modelling efforts 
undertaken by three United Kingdom based organisations that 
are at the forefront of this application domain; namely the 
[ESSG, SciSys Ltd, and the UK’s Centre for Ecology and 
Hydrology. 
  
During the study the IESSG Navigation System Simulator (see 
Section 2.3 below) has been further developed to include 
Galileo signals and those of the modernised GPS. In addition a 
detailed environmental model has been developed which 
simulates both difficult and challenging environments, 
including such factors as terrain and building signal obscuration 
and multi-path. There was also a need to advance the 
development of new processing algorithms and tools to process 
these new GNSS observables in a dynamic, and often difficult, 
simulated environment. 
A further key development within FURLONG was the 
communication emulator which includes GSM networks (2G), 
GPRS networks (2.5G), and UMTS networks (3G). In the case 
of the 3G emulation, care was taken to adjust the operational 
parameters to allow for T-UMTS operation, S-UMTS operation 
and combined S/T-UMTS operation. In every case the aim was 
to emulate the performance of the communications system as 
perceived by an ordinary user with bandwidth (both nominal 
and degraded due to adverse location), propagation delays, 
hand-over glitches, dropouts and data congestion all modelled. 
2.2 Simulation in Teaching 
Gaining experience of methods, techniques, and practical 
applications can play a major role in the learning process. 
Analysing these experiences often leads to significant 
understanding of all aspects of a subject from fundamental 
principles through to advanced applications. To provide 
significant amounts of such experience in a one-week intensive 
teaching block, which is the module staff contact time on our 
Masters level courses, is not practicable. Likewise it is not 
feasible to provide everyone with equipment, often expensive, 
and the practical scenarios to enable them to undertake tasks 
outside of the one-week teaching blocks. For a number of 
years, therefore, we have been exploring how best to create, 
develop and utilise a range of simulators and emulators for 
computer-based learning. The main technologies to be 
simulated have been GPS and IMUs as described in the 
following sections. 
102 
The GPS Computer Aided Learning (CAL) Facility: Our 
involvement in the development of simulations for teaching is 
not just a recent event. During the mid-90’s the IESSG 
developed a series of Computer Aided Learning (CAL) Tools 
related to various aspects of surveying. At the time, the drivers 
were much as they are today eg an improved student learning 
environment, greater control of learning, the development of an 
exciting and interesting environment and alternative methods of 
learning. Positive feedback from both undergraduate and 
postgraduate students was received over a period of years with 
clear messages emphasising how the CAL packages improved 
teaching, complemented lectures, increased awareness before 
practicals and allowed a more efficient use of resources. 
IMU Simulation Facility: The IESSG has internally developed 
a MathCAD based IMU simulator which is used very 
successfully within a number of our teaching and research 
activities. One particularly popular exercise involves the 
Master's level students designing a navigation solution for use 
by an autonomous robot on the moon. 
ibd 
  
  
  
  
  
  
| BE) Mathcad Explorer:D:\Chris\Teaching\Integrated Systems\Lab\INS-Error-moon-v&b.mcd 
Pie Edt View Insert Format Math Symboles Help s ë : 
G Woo (8 86 
n etii -i 
NPLV INS Error Analysis 
€ 
= 
m» 
71791 hi. 3 
ined Erro Pos 
EA=019%9 ADaçe(t} = 1- cos( e t)) 7e 
fy 2s 
sy 09 LD ill) = emi Sint) e 
-Rä, ES 
AD uitis —{wt- sintot}} “a 
dys = 0:10 AD alt= -R 2 cos(A)ö y, 
-R&-cos(Aj à v 
5, 001 AD ppt) = M (et- sincetyl en 
© 
$5200 AD zit} = -R 8 g:{1- cos(@1)) sep 
v 
«1 > 
Press F1 for help. iE à Auto | MM: Pagel 
  
  
Figure 1 — INS Simulation Teaching Tool Screen Shot 
The intuitive mix of education, assistance and calculations 
within the package (see Figures 1 and 2) enables the students to 
explore a range of performance characteristics including 
acceleration error, azimuth gyro drift, levelling gyro drift and 
velocity error, never forgetting critical issues such as the 
Schuler Period on the Moon's surface and the impact of the 
Lunar environment (“Moon rate”) on the Azimuth 
Misalignment and Azimuth Gyro Drift terms! 
Int 
  
On 
a ( 
an 
pr 
be 
M 
inc 
(In 
en 
co 
an 
tra 
co 
co 
an 
ane 
TC 
an 
tec 
pe 
fu 
al: 
int 
sei 
th 
the 
an