ASSESSMENT OF THE EGNOS SIGNAL AVAILABILITY FOR LAND MOBILE USER
Pavel Kovář, František Vejražka, Libor Seidl, Pavel Puričer
Czech Technical University in Prague, Department of Radio Engineering, Faculty of Electrical Engineering
Technicka 2, 166 27 Praha 6, Czech Republic
phone +420 224 352 246
fax +420 224 355 829
e-mail [email protected]
Abstract
Keywords: EGNOS, mobile user, Markov model
The EGNOS system is a satellite based augmentation system (SBAS), which has been developed for improvement of the
existing GNSS systems in order to be applicable in safety critical applications. The availability of the EGNOS system for
land mobile user is limited by the shadowing of the satellite signals by various obstacles, terrain, buildings, vegetation etc.
The EGNOS land mobile channel is analyzed in this project. The shadowing of the EGNOS signal is modelled by two-state
Markov model in which a time variable is equal to covered distance. The aim of this contribution is to discuss topics
concerning the experimental part of the project. The measurements were prepared for various typical environments in the
Czech Republic like Prague city, urban and suburban areas, countryside, etc. The experiments were planned to make possible
statistical processing and generalisation of their results. The experimental equipment for research of satellite signal
shadowing process, a new version of the Experimental GNSS receiver, has been developed. For rapid EGNOS signal
detection the fully parallel EGNOS software correlator has been developed and implemented into the receiver.
Introduction
The EGNOS (European Geostationary Navigation Overlay System) [1] is the first step on the way to European
satellite navigation system. It belongs under satellite based augmentation systems (SBAS) that offer improvement of
present GNSS systems. In the family of SBAS we can find besides EGNOS also US WAAS that is fully compatible
with EGNOS. In Asian region there were developed Japanese MSAS and Indian GAGAN that would help to cover
entire world by SBAS signal in the future.
Main purpose of the EGNOS is to improve performance and integrity of present systems, US system GPSNAVSTAR and Russian system GLONASS, in order to enable use of these two systems for safety critical
applications. Primary purpose of EGNOS, which has been developed for, is to support position determination and
navigation of civilian aircrafts.
EGNOS operation principle is based on distribution of wide area differential corrections of GPS and GLONASS
systems. Differential corrections carry information about measurement errors for individual satellites, information
about precision of position determination, and information about integrity of the satellite signal. The broadcasted
information is provided by the network of ground stations that execute monitoring the navigation signals.
The signal is disseminated by four geostationary satellites (GEO). The structure of EGNOS signal is similar to
signal of GPS L1 C/A, i.e. ranging signal that enables distance measurement in addition to differential corrections
dissemination. EGNOS satellites then extend the current navigational satellites constellation for several satellites
which results in increase of precision of position determination due to PDOP decrease.
The system should be in the status of full operational capability since 2004. The full operational status is preceded by
test in the frame of ESTB (EGNOS System Test-Bed). Since the current plans of EGNOS use cover land applications,
it is crucial to investigate its availability to land mobile user.
1. Mobile satellite channel modelling
Mobile channel models of satellite systems are based on general channel models. The satellite mobile channels differ
from terrestrial mobile channels in the fact that the direct signal path for mobile channels is blocked only in the close
surrounding of the receiver antenna. The fluctuation of signal strength caused by the medium-term fading is then not
characterized by log-normal distribution known from terrestrial channels but rather by its discrete states (open, closed).
Fig. 1 shows block scheme of the model of mobile satellite channel with frequency flat fading [2]. The channel is
characterised by its two states: open (unblocking), closed (blocking). The state open means that direct path signal is
not blocked. In this state, the flat fading is modelled by the Ricean random process. The parameter c expresses ratio
of direct path signal power to power of diffracted and reflected signals.
The flat fading in the channel state closed is modelled by the multiplicative random process with log-normal
distribution with parameters  and  . The mechanism of the opening and closing of direct path is usually modelled
by Markov chain for the discrete time model and Markov process for the continuous time, respectively.
Fig. 1. Model of a frequency-flat fading satellite channel
Mobile satellite channel at the frequency 1.5 GHz can be considered as a frequency flat fading channel for narrow
bandwidth only. In case that bandwidth is wider than 30 MHz the delay of the reflected signals has to be taken into
account. This leads to significant increase of model complexity [3].
2. Probability of EGNOS message reception
The analytical solution of the EGNOS signal reception issues for the mobile user is presented here. The two-state
Markov model of the channel that was described in previous text is used. The solution is represented by messages
reception statistics.
Let
Ai be
a successful reception of i-th message and the beginning of the transmission of i-th message is
( T1v  T2v  ...  TN v ). Length of broadcasting of the message is
TZ v  m . The messages can not be overlapping
each other in time.
Assuming the steady state of the random process, i.e. probability of the states 0 and 1 is
probability of reception of one message
Pr  A1 
Ti v
0
and
1 ,
the
can be then expressed as
 Pr  persistence in state 1 during TZ v state 1 in time T1v  . 
Pr  A1   
 
 Pr  state 1 in time T v 
1


 TZ v
  1e
Probability of reception of at least one message from N messages can be expressed by probability of union of
random sets
Ai


N 
 N 
N 
 N 
Pr  Ai   Pr  A1   Ai    Pr  A1   Pr  Ai   Pr  A1   Ai   
 i 1 
 i 2  
 i 2 
 i 2  


N

i 2
The term
.
Ai  Y  Pr  A1   Pr Y   Pr  A1  Y   Pr  A1   Pr Y   Pr  A1  Pr Y A1 
 N 1

Pr Y   Pr  Ai 1 
 i 1

can be computed recursively with use of previous terms. Two sets case can
be solved by
Pr  A1  A2    1e  TZ v   1e  TZ v   1e  TZ v p11  T2  T1  TZ  v  e  TZ v 

  1e  TZ v 2  p11  T2  T1  TZ  v  e  TZ v
The conditional probability

Pr Y A1  can be computed by the terms
 N 1

Pr Y A1   Pr  Ai 1 X T1v  TZ v   1 
 i 1


 N 2
 
Pr
A
X
T
v

T
v

1

Pr



2
1
Z
 Ai  2 X T1v  TZ v   1  
 i 1
 

direct computation
recursive




N 2


  Pr 
Ai  2 X T2 v  TZ v   1 Pr A2 X T1v  TZ v   1 


 i 1



direct computation
recursive






The described term contains parts that can be computed recursively. The remaining parts, for example conditional
probability of type

Pr  A
 , can be computed with respect to assumptions above according to
X T v  T v   1  p T v  T v  T v   e

for j  i .
 T  T  T  v  e
Pr A2 X T1v  TZ v   1
 p11
 TZ v
j
i
Z
11
j
i
Z
 TZ v
j
i
Z
3. EGNOS fast detection algorithm
First step to successful reception of the EGNOS message is correct and fast detection of the EGNOS signal. The
advantage of the EGNOS is its use of geostationary satellites for signal transmission. Thus the signal is not affected by
the Doppler offset of the carrier frequency caused by the movement of the satellite. The frequency offset of the
received signal is then caused by user receiver movement and inaccuracy of the receiver clock source. The sources of
errors and the related frequency offsets are summarised in the following table.
Sources of Errors
Max. Frequency Offset [Hz]
Satellite movement
0
User movement (max. radial velocity 72 km/h)
100
Inaccuracy of the receiver clocks 10-7
150
Total
250
Table 1. Contributions to the frequency error
The results in the table show that maximal frequency offset in the discussed case will be 250 Hz, which is one
half of the frequency step during searching state. The detection of the presence of the EGNOS signal for designed
receiver can be done by the search of the maximum of the correlation function for one frequency only, which is equal
to L1. The task is thus simplified to a search in signal delay  .
The other method that will speed up the algorithm of the search of the correlation function maximum is use of
parallel computation of correlation function. The receiver in that case has to be able to compute during time interval
TC
value of correlation function for all of investigated delays
.
The signal processing algorithm of EGNOS signal detection implemented in the experimental GNSS receiver
can be according the block scheme at Fig. 2 separated into four consecutive parts:
1.
Transformation of the intermediate frequency signal to the baseband and signal decimation
2.
Parallel computation of cross correlation function of received signal and its replica
3.
Noncoherent integration
4.
Search of the correlation function maximum and signal presence detection
sr
IF
R
sr
Transformation to the
baseband
Parallel
correlator
2
Noncoherent
integration
Signal
detection
output
Fig. 2. Block scheme of signal processing algorithm
The whole signal processing algorithm was developed and tested in Matlab Simulink environment with use of
Xilinx DSP Blockset add-on and Xilinx System Generator [4]. The described combination was used because of
planned implementation into the experimental GNSS receiver based on FPGA device Xilinx Virtex-II, described
bellow. The implementation is shown on the Fig. 3. Block GPS_EGNOS_parallel_correlator transforms
signal to the baseband and computes cross correlation of the received signal and replica. Block
Noncoherent_integrator executes noncoherent integration. The last block Peak_detector executes search
of the maximum of correlation function and evaluates signal presence. The implementation scheme is for testing
purposes also equipped by block of logical analyzer ChipScope, which is connected to the output of parallel
correlator and noncoherent integrator.
Fig. 3. Matlab Simulink model of signal processing algorithm
4. Experimental measurements
This chapter describes realization and results of experimental measurements of shadowing process of EGNOS
satellites for land mobile user. The experimental GNSS receiver based on Software Defined Radio concept was used
for experimental measurements. The equipment was installed in the car with carriage. The measurements were realized
during common traffic operations in typical environments:
•
city of Prague
•
industrial town
•
village
•
highway
•
main and secondary roads in the country
The measured data were processed by mathematical software and compared to theoretical results.
4.1. Experimental GNSS receiver
High performance analogue to digital and digital to analogue converters together with high computational power of
programmable devices and digital signal processors (DSP) enable to convert analogue RF signal to its digital form and
process this signal as a sets of binary data. The realization of basic blocks and even whole signal processing stages in
present systems, for example radio receivers and radio transmitters for communications or navigation, is then
transferred to digital domain. It includes signal filtering, modulation/demodulation, synchronization, etc. The border of
converting analogue signal to digital moves to the higher frequencies (e.g. intermediated frequencies 70 and 140
MHz). At this level, the signal with bandwidth of tens of MHz can be now processed with sufficient dynamic range
thanks to high performance of digital devices.
As all operations with signal are done by digital programmable circuits or devices, the signal processing is
determined by a implemented software algorithms or devices software configurations. The concept of radio receiver,
whose main parts of signal processing chain are realized digitally by programmable digital circuits, is usually called
Software Defined Radio (SDR) or simply Software Radio.
The SDR concept of embedded processor in FPGA device was chosen for design and development of experimental
GNSS receiver at the Czech Technical University in Prague. The main aim of the design was to provide flexible and
versatile platform for implementation, testing, and verification of GNSS signal processing algorithms. The receiver
should serve also as a highly configurable device for GNSS signal measurements and tests. To achieve these
requirements the modular concept of the receiver was chosen.
Generally, the receiver consists of two main parts: RF unit and DSP unit. In the first version, the RF unit consisted of
two channels, providing down converted analogue signal to DSP unit connected to High Power Computer (HPC)
(Fig. 4). The DSP part was based on Xilinx FPGA Virtex-II device platform realized as a PCI interface card installed
in HPC represented by PC workstation running under MS Windows 2000 operating system [5].
GNSS antenna
Radio Frequency Unit
DSP Unit
LNA
DSP Xilinx
Channel 1
Synthesizer
A/D
FPGA
Virtex II
Channel 2
LNA
PCI Bridge
High Power
Computer
Fig. 4. Experimental GNSS software receiver architecture – first version
The initial test and experiments with first version receiver have shown that chosen concept is appropriate for planned
purposes, however with several restrictions. The main issues related to the first version of GNSS receiver were
represented by following problems:



The Windows 2000 proved not to be reliable operation system for such application, where frequent
software handling is required. The interrupt dropouts were sometime observed.
Communication with DSP via PCI bus, that is block oriented, caused some problems. The direct access to
the correlator registers would be more convenient.
The first version of the experimental GNSS receiver is incompact; that complicates for example mobile
experiments realization.
These problems lead to design of advanced version of the receiver. The main change was done in DSP unit design
that is now represented by FPGA device Virtex-II Pro with two embedded IBM PowerPC PPC–405 cores (Fig. 5).
That platform enables single chip integration of all digital processing parts, i.e. correlators and computer for tracking
and navigation task resolving. For achieving higher reliability of the whole system, the true real time multitasking
operating system is chosen instead of Windows 2000.
GNSS antenna
Radio Frequency Unit
DSP and Processor Unit
LNA
Channel 1
Synthesizer
FPGA Xilinx
Virtex II Pro
Channel 2
LNA
Channel 3
AD
PowerPC PowerPC
core
core
LNA
Fig. 5. Experimental GNSS software receiver architecture – advanced version
Moreover, the number of RF channels was increased to four due to modernization of the GNSS systems, where the
new GNSS signals on the new frequencies will be available. The receiver should process these signals simultaneously.
The RF channels are unified to keep the simplicity and compactness of the receiver. Each channel is equipped with
SAW intermediated frequency (IF) filter of unified bandwidth 24 MHz. The intermediate frequency is increased on
140 MHz. It insures higher suppression of undesirable signals on the mirror frequency. The resolution of the analogue
to digital converters will be 8 bits. The sample frequency is designed 80 MHz. Such frequency can be easily derived
from 10 MHz normal by frequency multiplication.
4.2. Installation of measuring equipment
The measuring equipment has to measure and record presence of EGNOS signal and travelled distance. Because of
complicated direct installation to the car the sensor of travelled distance was mounted to the carriage towed behind the
car. The construction of the sensor is based on combination of permanent magnets and magnetic contacts similar to
sensors used for bicycle computers. The wheel of carriage was equipped by three permanent magnets (Fig. 6). The
magnetic contact of sensor is based on miniature dry-reed relay in DIL14 package, mounted on the base of carriage.
Fig. 6. Sensor of the travelled distance – wheel with magnets and relay mounting
The measured signals are pre-processed in 8051 series microcontroller, which processes pulses from distance sensor
and information about presence of EGNOS signal from experimental GNSS receiver. Processed data are then stored in
notebook. The experimental receiver and notebook were installed in the cabin of the car (Fig. 7)
EGNOS signal was received by the common consumer GPS L1 antenna with magnetic mounting on the roof of the
car.
Fig. 7. Experimental GNSS receiver and notebook for data storage
4.3. EGNOS satellite selection
The mobile experiments were carried out in January to March of 2005. EGNOS was operating during time of
experiments in its testing phase ESTB. EGNOS signal was regularly transmitted by Inmarsat IOR (PRN 131) satellite.
Another signal from Inmarsat AOR-E (PRN 120) satellite was available in the unscheduled intervals besides IOR
satellite signal.
The Inmarsat IOR satellite is located above the Indian Ocean in the position 64º East and the elevation of the satellite
in the Czech Republic is around 15º [6]. In the full operational phase will the system transmit EGNOS signals from the
satellites listed in the Table 2. The elevation angle of new satellites will be more than 30º, which will result in better
availability of EGNOS signal for land mobile user. The regular broadcast from these new satellites was not available in
time of experiment, that's why the Inmarsat IOR (PRN 131) satellite was used for experimental measurements. Several
measurements were done for AOR-E satellite too.
SATELLITE
POSITION
ELEVATION IN CR
PRN
Inmarsat III (AOR-E)
15,5W
26º
120
ESA Artemis
21,5E
32º
124
Inmarsat III F5
25E
32º
126
Inmarsat IOR
64,5ºE
15º
131
Table 2. Constellation of EGNOS Satellites
4.4. Measurements results
Figures 8, 9, and 10 show measured processes of EGNOS satellite shadowing in typical environments (village, main
and secondary roads – Fig. 8a, industrial town – Fig. 9a, city of Prague – Fig. 10a). The computed estimates of
distribution of time of blocking and unblocking states of satellite signal path based on measured shadowing process are
shown at Fig. 8b, Fig. 9b, and Fig. 10b. The pictures show comparison of the described distribution with exponential
distribution density function, which relies to theoretical distribution of persistence of Markov process in each of the
states. The graphs show that estimate of distribution of open or closed state is in correspondence with theoretical
distribution except for part close to zero distance.
block
unblock
0
1000
2000
3000
4000
Distance [m]
5000
6000
7000
(a)
(b)
Fig. 8. The EGNOS satellite shadowing (a), Distribution of blocking and unblocking states (b)
– village, main and secondary roads
block
unblock
0
500
1000
1500
2000
Distance [m]
2500
3000
3500
(a)
(b)
Fig. 9. The EGNOS satellite shadowing (a), Distribution of blocking and unblocking states (b)
– industrial town
block
unblock
0
1000
2000
3000
4000
5000
6000
Distance [m]
(a)
7000
8000
9000
10000
(b)
Fig. 10. The EGNOS satellite shadowing (a), Distribution of blocking and unblocking states (b)
– city of Prague
The next step of measured data analysis is an evaluation of message reception statistics. The probabilities of message
reception were obtained from the simulation based on measured shadowing processes. The statistics obtained from real
measurements were compared with probability statistics computed from mathematical model.
(a)
(b)
Fig. 11. The probability of reception of at least one message from N for real data (a) and mathematical model (b)
– village, main and secondary roads
(a)
(b)
Fig. 12. The probability of reception of at least one message from N for real data (a) and mathematical model (b)
– industrial town
(a)
(b)
Fig. 13. The probability of reception of at least one message from N for real data (a) and mathematical model (b)
– city of Prague
The probability of reception of at least one message from N in relation to a number of messages N and user radial
velocity v is shown on Fig. 11, Fig. 12, and Fig. 13 for each of environments used above. The probabilities are
depicted both for computation based on measured real data (a) and for computation based on mathematical model (b).
Conclusions
The availability of the EGNOS signal for a land mobile user was evaluated. The channel model based on two-state
Markov process was used for computation of probability of the EGNOS message reception. The algorithm of fast
signal detection based on parallel computation of correlation function was developed in Matlab Simulink and
implemented into experimental GNSS software receiver. The experimental receiver was used for sets of
measurements, covering typical environments in the Czech Republic: City of Prague, industrial town, country town or
village, highway, and main and secondary road in the countryside. The results obtained from the real data have shown
good relationship with theoretical models. However, it is very complex task to deduce more general conclusions about
satellite visibility in various environments because the border between them can not be sharply defined and each of
environments itself varies from location to location. The measurements results are related to the used EGNOS satellite.
Since the used Inmarsat IOR satellite is visible under relatively small elevation of 15º in the Czech Republic, the
results with satellites planned for full operational capability will bring better signal availability and thus the higher
probability of successful message reception. Since the crucial task is to ensure regular actualization of corrections and
integrity information in the user receiver, it is not necessary to receive every transmitted message. It is only necessary
to ensure that the age of this information will not exceed some clearly defined value. We are then interested not only in
simple probability of message reception but also in the probability of reception of at least one message from two, three,
etc. The message reception statistics based on real measured data was evaluated in the paper.
References
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http://www.esa.int/esaNA/egnos.html (Ref. 28th March 2005).
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3. Mayr, H.; Moeneclaey, M.; Fechtel, S. A.: Digital Communication Receivers, Synchronization, Channel
Estimation And Signal Processing, John Wiley & Sons 1997. ISBN 0-471-50275-8
4. Xilinx System Generator for DSP version 2,2. Reference manual. Xilinx 2003
5. Vejražka, F.; Kovář, P.; Seidl, L.; Kačmařík, P.: Experimental Software Receiver of Signal of Satellite
Navigation Systems. In Proceedings of 11th IAIN World Congress. German Institute of Navigation, Berlin 2003
(CD ROM)
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