Satellite availability in a railway mountainous environment :
Can we use satellite positioning for safety applications ?
1
1
Juliette Marais , Amaury Flancquart , Sébastien Lefebvre
1
1
French National Institute for Transport and Safety Research
Abstract
The arrival of GALILEO will provide to railways a localisation solution, civil, European, interoperable with
the existing GPS. The use of both systems and the characteristics of GALILEO open the way to new
applications, and particularly to safety related applications.
However the reception of satellite signals depends on the environment around the antenna and can
degrade the typical performance of such systems. The PREDISSAT tool based on video records permit to
evaluate the satellite states of reception along a line. The study realised along a mountainous line in the
south of France illustrates the tool and typical results obtained.
Introduction
With the development of GALILEO, satellite positioning systems are considered for new safe railways
applications. However, the condition for their use is the guarantee of safety. Today GPS, does not offer
enough reliability and safety for railways requirements. Tomorrow, GALILEO will offer a supplementary
and independent constellation for localisation. The two constellations will be interoperable and better
performances can be expected. In parallel, based on the existing GPS, alternative solutions have been
designed, in European projects, based on redundancy of signal uses or multi-sensors systems… The
safety of these solutions remains a critical challenge !
One of the main drawbacks for satellite use remain signal reception difficulties due to high masking
obstacles. Because of its mountainous surroundings, the railway line between Nice and Digne, operated
by CONNEX in the south of France, has been an interesting test site in the LOCOPROL project context.
Satellite positioning relies on propagation time measurement from 4 satellites at least. Obstacles can
obstruct signal reception so that the train cannot position itself. Furthermore, masks around the antenna
cause propagation delays when satellite signal reflects on obstacles that increase the positioning errors.
This is also true for the EGNOS satellites. EGNOS is a satellite-based augmentation system for GPS. Its
use is a step towards integrity but the reception of EGNOS satellites is very disturbed by obstacles
because EGNOS satellites are geostationary. Due to their positions, their elevation above the horizon is
very low in Europe and they will be more sensitive to masking effects.
In this paper, we will present a study of the reception conditions of these satellites and, in particular, the
tool developed to achieve this.
First part of the paper will summarize needs and solutions that GNSS (Global Navigation Satellite
System) can propose for railways. The second part will introduce the tool. The originality of our study
deals with the use of a representation of the real environment to simulate what GALILEO will add to
existing systems. Our method is based on a video record and satellite position simulations. The fish-eye
360 degrees view of the environment above the train determines automatically the masking obstacles
such as trees, mountains or buildings. As developed in part 3 in the case of a mountainous environment,
the number of visible satellites along the line and the quality of their reception is then extracted from this
analysis, so that we are able to quantify the reliability of such a positioning solution along the line. As
tunnels, critical areas will have to be equipped with a balise or the train will have to use another sensor to
compensate the lack of signal. We will conclude with a study of how these results will help to a safety
analysis and open for safety critical applications.
1. GALILEO for railways ?
1.1. Needs
In the European Commission White Paper on Transport, one of the priorities is given to the revitalization
of the railways. The rail sector must improve its competitiveness and attractivity. This concerns various
activities such as track occupancy, safety, productivity and customer satisfaction in different sectors such
as fleet management, passenger information or train control [1].
GNSS use can be part of the solution in this objective. GNSS benefits will result from increased
performance of rail transport and multimodality, reduction of trackside equipments and more economic
solutions, unique solutions all over the world, independent from countries and equipments. Nowadays,
most of the railway localisation sensors are balises on track that require maintenance and that differ
function of the country. For a high frequency position computation, a large number of sensors have to be
deployed. Furthermore, trains have to be equipped with every balise readers to cross frontiers and be
able to continue to position itself… In order to reduce these costs, tendency is to embed systems.
GNSS is also particularly appropriate in many countries where there is today no trackside equipments.
Along low density traffic lines, a full set of signalling equipment is uneconomic and could be replaced by
embedded GNSS solutions.
Fleet management systems will benefit of a continuous localisation information to organise rolling stock,
improve maintenance, enable dangerous good tracking and surveillance… Moreover, the knowledge of
the train position and its environment will allow the driver to optimise his speed in order to save energy.
Of course, cost reduction or maintenance facility is not acceptable if GNSS solution does not offer
guarantees, required safety or accuracy. Next paragraphs will focus on GPS and GALILEO.
1.2. GPS solution
GPS can today answer to some of the railways requirements. Its accuracy and availability are able to fulfil
the needs for some applications. Freight wagons tracking is currently trialed in different countries (France,
Germany, Belgium…). SNCF uses a GPS-based system for fleet monitoring of the TGV.
GPS answers to their requirements because :
-
it is not safety related
-
accuracy is not critical,
-
availability is not critical, neither continuity…
But GPS does not offer integrity and safety applications remains inaccessible.
1.3. GALILEO enhancements
With the aim of freeing itself from the American monopoly, Europe has decided to create its own
navigation satellite constellation, GALILEO. The reasons are both political and economic: it is important
for Europe not to be dependent on systems and technologies that have been developed elsewhere for
applications which are vital for tomorrow’s society. Furthermore, Europe cannot remain excluded from a
technology which is destined to be one of the principal sectors of industry. The GALILEO system will be a
civil system; it is planned for 2008 and will provide several levels of service.
GPS and GALILEO systems will be interoperable. A receiver able to use both constellations will therefore
benefit from greater coverage and therefore better availability. Moreover, GALILEO will send an integrity
message to the user that will be able to use the satellite information with much more confidence than the
GPS one. This message is already broadcast by the EGNOS (European Geostationary Navigation
Overlay Service) satellites. Three geostationary satellites have been launched. These satellite are
devoted to GPS solution enhancements over Europe. EGNOS broadcasts pseudo-range corrections and
their accuracy. EGNOS corrects ionospheric and tropospheric delays, orbital and clock errors…
EGNOS is fully operational since 2005. In the results presented in this paper, one paragraph will deal with
their availability.
These innovations will help to develop new satellite-based services such as driving optimization, moving
blocks, tolling of access on infrastructure, tracking of wagons transporting dangerous goods… GALILEO
is foreseen to become an instrument for safety-related train control functions within the European Train
Control System ETCS/ERTMS.
2. PREDISSAT : How to evaluate satellite availability
2.1. Principle
Satellite positioning involves computations based on measurements of the propagation time of each
signal received from the visible satellites which provide pseudo-distance values between each of the
satellites considered and the receiver. The results are contaminated with errors. Some of these are
known and corrected directly by the receiver using models: these are the errors caused by the passage
through the atmosphere. Others are caused by radio-electric shadows around the receiver and in
principle cannot be corrected because there is no model that can be applied to all environments: these
errors are generated by multipath propagation.
The best reception of a satellite signal is obtained in the case of direct visibility. The signal does not
undergo attenuation and delay due to multipath. This is referred to as line-of-sight (LOS) reception. When
the signals from satellites are shadowed, the satellites are either blocked (a situation known as non-lineof-sight (NLOS)), or received by multipath and thus likely to generate an error in the position calculation.
We shall refer to this as a reflected satellite signal. These three states must be identified in order to
predict availability.
The objective of our tool is to identify, at any point along the route and at any instant t, the state of
reception (visible, reflected, blocked) of each of the satellites that is available around the vehicle’s
reception antenna.
In order to know how many satellites are available for the purposes of the positioning calculation, we have
developed a tool to forecast the availability of a constellation of satellites along a known route. This tool is
known as PREDISSAT (Predictive Software for Satellite Availability in the Field of Transport) [2].
The tool determines the number of satellites that are available as a function of the position of a vehicle on
its journey and the obstacles which surround it. The method involves filming the environment of the
antenna, using vehicle-borne cameras during a single passage along the route. Semi-automatic image
processing allows the properties of the optical obstructions along the route to be determined in three
dimensions. These obstacles are then associated with simulated satellite data. As GNSS satellites are
moving, simulations are performed taking into account different times of departure in order to propose a
representative view of the line availability.
2.2. First applications (LOCOPROL)
The PREDISSAT tool has been applied in the 5th Framework Program LOCOPROL. The LOCOPROL
project intends to develop a new cost-effective satellite based fail-safe and innovative train protection,
control and command system, specifically to be used on railways for low traffic density.
As the addition of multiple sensors does not fit to the objective of a low cost system, the LOCOPROL
navigation system has been defined with the aim of minimal equipment on-board and minimal cost.
Starting from the notion that the trajectory of the train is known, the algorithm has been reduced to a one
dimensional problem. Independent pairs of assumed time synchronized satellites and technique referred
to TDOA (Time Difference Of Arrival) method have conducted to propose a solution with a worse
accuracy but a high integrity [3].
In this project, PREDISSAT has been used as an evaluator of availability. Figure 1 shows a typical result
obtained along the Belgian test track with the total number of satellites received from which the number of
received directly. The directly visible satellites can be used with confidence but the reflected one with
careful.
9
Number of received satellites
8
7
6
5
4
3
2
1
14:32:36
14:32:31
14:32:27
14:32:22
14:32:18
14:32:13
14:32:09
14:32:04
14:32:00
14:31:55
14:31:50
14:31:46
14:31:41
14:31:35
14:31:15
14:30:50
14:30:45
14:30:41
0
Time
Figure 1. Function of time, number of satellites received (blue curve) and from which directly received
(green curve).
Intensive simulations exploring different departure times for the vehicle have shown availability statistics
along the line or minimum expected visibility and so on.
2.3. Evolutions
During the French tests, PREDISSAT has been used in a railway mountainous environment. The original
configuration of the tool, based on two cameras back to back observing each one side of the track has
shown its inadequacy in such an environment. Indeed, a mono-camera stereovision process was applied
on the record in order to detect the begin and the end of each obstacle. Along a track running close to the
mountain surface, these begins and ends cannot be seen into the camera lenses. Thus, we have used an
other sensor based on a fish-eye lens as some of the telecommunication studies found in the literature
[4]. A view of the record is seen in figure 2.
Figure 2. Fish-eye view of the antenna surroundings.
The first algorithm used to process two lines extracted from B&W matrix images, and pixels were
characterized by their grey level. The new record has then required very different processing techniques.
The following processing technique consists in :
1. Characterizing the distortion of the fish-eye lens,
2. Placing each satellite into the image corresponding to the train path,
3. Defining a neighbourhood of 9*9 pixels around each satellite position,
4. Segmenting the sky based on three criteria :
- a colour indicator : blue level in a colorimetric RGB referential
- luminance and saturation levels in the HLS (Hue, Luminance, Saturation) referential
5. Automatically detecting the satellite visibility state based on three different states : the
satellite is visible if the image zone characterises sky. The state is uncertain when the
characteristics of the studied window does not permit a reliable diagnostic, as behind
trees as explained in the following. Otherwise the satellite is considered as masked..
This algorithm has shown its utility but one can cite the following difficulties :
Most of the previous image processing developments concern known and closed environment. In this
case, the conditions are defined as optimal as possible as done for indoor surveillance for example. For
example, the light can be modified if necessary. Here, the vocation of the video cameras is to record the
sky along long path. That means that light conditions can change. However the camera configuration has
to fit during the whole train run. In the same way, the processing algorithms have to deal with various
types of objects (trees, mountains, buildings, catenaries…) and detection rules have to be global. This
challenge is part of the research areas today in several projects [5].
Using a fish-eye lens on a camera pointing vertically on the top of the train makes the sun always directly
on the sensor. Thus, records are sometimes difficult to process due to saturation of the image that makes
the video lose every colour information. To minimize those problems, first solution is composed of
equipping the lens of a dome. Second is the use of automatic gain control (ACG) that allows the sensor to
adapt itself very quickly to the light changes. Future solution will be oriented towards the use of
logarithmic cameras.
Another difficulty deals with obstacles that present a very high luminance that are detected as they were
sky.
In our mountainous environment, most of the line is bordered by trees. Their density varies function of the
season and their propagation characteristics are complicated. This explain why the satellites detected
behind trees are considered as “uncertain” before the use of specific propagation studies [6,7].
No other propagation rules are applied in this version of the tool contrary to the first one based on the two
matrix cameras [1].
Finally, some differences between PREDISSAT results and measurements are observed. Some can be
explained by the fact that the tool acts like a discrete tool considering the images one by one as
independent data. Indeed the actual version of the tool does not take into account any receiver
characteristics (time to first fix, acquisition time, latency…). This will be a research axis in our future work
as well as the definition of a variable sky indicator based on a sample in the centre of the image and able
to evolve during the train run.
3. Along a real railway mountainous environment
Measurements have been performed along the CFTA railway line between Nice and Digne in the south of
France. The train first goes out of the city and progressively runs along the mountains. The line is
bordered by trees or hills. Thus, satellite reception can be difficult at least from one half of the global view
as seen in figure 3. The tree processing is sensitive because of the season effect ; the compromise
between considering them as obstructing obstacles or not is difficult to find. A future enhancement of the
tool will be the recognition of such texture in order to integer propagation rules directly related to this
particular case.
Figure 3. Mountainous visibility.
Following the image processing briefly described in the previous paragraph, typical results are presented
in the next paragraphs.
3.1. Number of GPS satellites received
One image is recorded every 2 meters along the line. As described in the previous paragraphs, satellite
positions are simulated for every point of image acquisition. Each simulated satellite is then positioned in
the corresponding image as illustrated figure 4. Green satellites are detected in the sky. Their state is
“directly visible”. Their use assures a degree of guarantee about the reception quality and the pseudorange extraction. Red satellites are placed behind obstacles. In the case of tree, the density of the foliage
is high enough so that the tree is considered as “masking”. Orange numbers show uncertainty cases.
These satellites are behind trees and simulation do not allow to know if they will be obstructed or received
after attenuation. In practical, the comparison of the carrier-to-noise ratio of the signal received could be a
good indicator because multipath and reflections affect it.
Figure 4. Satellites represented in the image.
Their name is coloured function of their state of reception.
Next result shows the variations of the number of satellites received directly along 20 km. Figure 5 shows,
in blue, the number of directly received satellites. Zeros correspond to tunnels.
Number of satellites received
7
6
5
4
3
2
1
0
20000
22000
24000
26000
28000
30000
32000
Meters from departure
34000
36000
38000
40000
Figure 5. Number of satellites received along the line function of the train position
Due to the uncertainty condition and the non use of the propagation phenomena (that could make a
satellite received after reflection but without direct ray), the number of satellites considered can be
reduced in comparison with an experimental one. However, the number simulated above assures that this
number of satellites are well-received satellites.
This will be important for example in the computation of the GDOP, representative value of the geometric
contribution of observation errors to the GPS positioning accuracy. The GDOP validity is under the
assumption of equal pseudo-range measurement error variance in each channel which is the case with
direct signals. GDOP is then a good indicator of the accuracy of the solution [8]. This criterion is no more
reliable in masking environments because of the random variations of geometric pseudo-ranges. Critical
areas will be the places where less than 4 satellites can be received.
3.2. EGNOS availability
Since mid-2005, EGNOS satellites allow the receiver to use supplementary satellites to compute
positions and especially to benefit from an integrity message that guarantee the reliability of satellite
messages. Three EGNOS satellites are available. As they are geostationary satellites, their reception can
be difficult in masking environment because of their low elevation angle (31° for AOR-E, 36° for
ARTEMIS). However, they are of huge utility in a context of safety application. The service offers an alert
in a period of less than 6 seconds in case of satellite failure. This is not proposed by GPS alone today.
Thus, we have simulated the EGNOS availability along the same portion of line. EGNOS broadcasts also
the ionospheric corrections to apply for better accuracy. In order to use optimally the information, the
EGNOS continuity of reception is of particular interest.
Indeed, to obtain a full set of corrections, the antenna receives the ionospheric map over a period of a few
minutes and then get a full set of corrections for SBAS operation. Figure 6 presents the cumulative
distribution function representing the period of continuous reception of the ARTEMIS satellite from
PREDISSAT simulation (blue curve) compared to experimental measurements (red curve).
Because of the very quickly changes of the environment around the antenna, EGNOS state of reception
vary very quickly also. Simulation results are pessimistic compared to experimental ones. They show that
60% of the reception durations are shorter than 10 seconds. 40% are shorter than 5 seconds and do not
allow the receiver to benefit from integrity data. But some long areas of reception are observed. The
longest one has a duration of 275 seconds, which allows the receiver to benefit of some corrections for
accuracy gain. Periods without direct reception of the EGNOS satellites are shorter. The longest is equal
to 49 seconds. Function of the receiver specifications, the impact of very short service interruptions will
have a minimal impact on the service quality.
100
Sim.
CDF (%)
80
Exp.
60
40
20
0
0
50
100
150
200
Continuity duration (s)
250
300
Figure 6. Cumulative distribution function representing the ARTEMIS continuity of reception along the
40 km of track : Simulation (blue) and experimental results (red).
Comparison of simulation and experimental results allows us to assess the performance of the fish-eye
version of PREDISSAT. In the future, we could use the video only as a valid source of information for
such an analysis.
Several levels of service are distributed by EGNOS satellites : GPS signal broadcasting for the use of the
satellite as a supplementary GPS one, propagation corrections for a better accuracy, and integrity. The
availability of these services varies function of their message length. The continuity of the reception will
then constraint the message availability. Results presented here show that long durations of reception are
difficult to obtain, especially in a very masking environment such this mountainous one. In such a case,
long message (360 s) required for ranging signal has a small probability to be received and used. The
chances to benefit from them are that the train stops long enough in a free of obstacle environment… The
integrity message (Use/Don’t Use), that validates the use or not of each of the available satellite, has
more chance to be used as its cycle is only 5 seconds long. However, its validity period is very short.
Finally, corrections will require that the messages would be received totally. This could last till 300
seconds and we observe that such a long period happened very rarely along the line.
Conclusions
GNSS offers new localisation solutions for railways. GPS constellation will be completed with GALILEO.
The use of both systems and the enhancements that GALILEO will add are of great interest for safety
applications. Some of them can be studied already with EGNOS satellites. As satellite reception can be
obstructed by obstacles along a track, we have developed a tool able to analyse the availability.
First experiments of the tool had already shown the utility of such a tool. The new enhancements
presented in this paper enlarge its possibility, especially for new environments. Some important
perspectives are today studied such as :
- The image processing new algorithms will allow us to define precisely the type of the obstacles
(tree, building…). Combined to adapted propagation rules, the integration of such information
promises very interesting enhancements of the tool.
- Considering the quick evolution of technologies, the idea of a real time use will probably become
realistic in a few years.
- Definition of a visibility criterion ; The process presented in this paper is time-dependent. Next
step will be to define a percentage of visible sky in order to put a confidence level into the GNSS
position, independent of the time of the run. Its role will be to aid a multi-sensor navigation system
to weight the use of the different sensors function of their reliability probability.
The beginnings of PREDISSAT were focused on availability in terms of number of satellites received.
Studies implying EGNOS open the way to safety analysis in real environment because of their
supplementary information they broadcast compared to GPS.
For the moment, the tool is not realised “in safety” and its results have to be used carefully. PREDISSAT
could be in the future a tool for GALILEO certification for railways that would take into account the reality
of railway environments.
In the mountainous environment considered in this paper, EGNOS cannot be fully used. The low
elevation angle of the geostationary satellites make them difficult to receive along long enough period.
Thus, their plain capability cannot profit to the receiver. However, some of the information are available
intermittently and provide an enhancement compared to the existing GPS. Furthermore, some hybridising
systems could be engaged on such lines such as the deployment of a SISNeT (Signal in Space through
the Internet) architecture that would broadcast signal through non-GEO means (e.g. FM or GSM
broadcasting) and make EGNOS and GALILEO a step towards new applications [9].
Acknowledgements
The authors acknowledge people from CONNEX and CFTA railways for their cooperation during the
measurements and from CNES for their helpful information about EGNOS.
References
[1] “GALILEO. Applications for rail. Roadmap for implementation“, Prepared by the UIC Working Group
'GALILEO Applications for rail - 5 October 2005
[2] J. Marais, A. Flancquart, M. Berbineau. “Prediction of GNSS availability in railway environments“,
World Congress on Railway Research, Edinburgh, (2003).
[3] J. Marais, M. Berbineau, O. Frimat, J.-P. Franckart, “A new satellite-based fail-safe train control and
command for low density railway lines”, Technological Innovation for Land Transportation (TILT 2003),
Lille, Déc. (2003).
[4] C. Amaya, T. Nguyen, “Performance evaluation of a LEO system in urban/suburban environments in
Ottawa, Canada”, IEEE Vehicular Technology Conference, Los Angeles, Sept. (2004).
[5] P. Lasserre, R. Murrieta Cid, M. Briot, “Le modèle nominative de Régions :segmentation couleur et
identification de régions par analyse de couleur et de texture”, GRETSI 1997, Grenoble, Sept. (1997).
[6] J. Goldhirsh, W. J. Vogel “Roadside Tree Attenuation Measurements at UHF for Land Mobile Satellite
Systems“, IEEE Trans. On Antennas and Prop., Vol. AP-35, n°5, May (1987).
[7] A. Steingaß, A. Lehner, “Land Mobile Satellite Navigation – Characteristics of the Multipath Channel”,
ION GPS/GNSS 2003, Portland, USA, (2003).
[8] P. Misra, P. Enge, “Global Positioning System. Signals, Measurements, and Performance”, GangaJamuna Press, (2001).
[9] F. Torán-Martí, J. Ventura-Traveset, “The ESA SISNeT Project: Current Status and Future Plans”,
GNSS 2004, Rotterdam, March, (2004).