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OCR for page 105
Monitoring and Assessment of
GNSS Open Services
JIAO WENHAI
Beijing Institute of Tracking and Telecommunication Technology
DING QUN
Xi’an Research Institute of Navigation
LI JIAN-WEN
Zhengzhou Institute of Surveying and Mapping
LU XIAOCHUN
National Time Service Center
FENG LAIPING
Xi’an Research Institute of Surveying and Mapping
Interoperability of GNSS Open Services has already been a significant ten -
dency in developing all satellite navigation systems, and its performance will
directly affect the security and reliability of its usages. Therefore, monitoring
and assessment of GNSS Open Services have become a focus of attention for all
providers and users of GNSS. This paper begins to illuminate the elements and
methods for monitoring and assessing GNSS Open Services. Then according
to the requirements, the architecture of an international GNSS Monitoring and
Assessment System (iGMAS) is designed to achieve the 4-overlap and 1-overlap
coverage and sophisticated analysis, respectively. Here, this iGMAS is based
on omnidirectional antennas, multi-beam antennas, and a high-gain paraboloid
antenna. In the meantime, the configuration scheme of worldwide monitoring
stations is provided. Finally, some related works that have been done to monitor
and assess the BeiDou Open Service are introduced that can be used to verify the
feasibility of this proposed system.
105
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106 GLOBAL NAVIGATION SATELLITE SYSTEMS
INTRODUCTION
Stepping into the 21st century, because of the successful launches of the
BeiDou and the Galileo satellites, the GNSS is changing from the bipolar com -
petition situation between GPS and GLONASS to a new situation of competition
and cooperation among four systems. Obviously, the compatibility and interoper-
ability of navigation signals have already been the main features during the period
of GNSS development. Against this background, open signals, with the function
of interoperability, are expected to bring GNSS services of higher quality and
better performance to GNSS users, especially in such places as urban canyons
and mountainous areas where visual airspace of satellite is limited. Open signals
can bring a significant increase in the number of visible navigation satellites,
improving the reliability and availability of navigation and positioning services
(Yang, 2010). So far, the main existing and being designed signals of GNSS Open
Services are as shown in Table 1.
At present, the four satellite navigation systems have issued or are planning
to issue their own specifications on open service performance. However, because
of the diversity in their respective conditions and knowledge, there may be large
differences in those specifications, either in form or in performance. As a result,
users will get confused when they are using and it will be inconvenient for them
to use. In addition, there are no performance specifications on GNSS open ser-
vice signals. To ensure the safety of the usage and achieve the ultimate goal of
interoperability of GNSS Open Services signals, it is essential for us to research
the monitoring and assessment of GNSS Open Services.
Monitoring and assessment of GNSS Open Services could provide third-party
information on performance for a single system and reliable decision-support
TABLE 1 Signals of GNSS Open Services
Global Navigation Center Frequency Modulation Interoperable
Satellite Systems Frequency (MHz) Mode or Not
GPS L1 C/A 1575.42 BPSK(1)
L1C 1575.42 MBOC(6,1,1/11) Yes
L2C 1227.6 BPSK(1)
L5C 1176.45 QPSK Yes
GLONASS L1OF/L1OCM 1598.06~1604.40 BPSK
L2OF/L1OCM 1242.94~1248.63 BPSK
L3 OC 1202.025/1207.14 BPSK
BeiDou B1-C 1575.42 MBOC(6,1,1/11) Yes
B2a 1191.795 AltBOC(15,10) Yes
B2b
GALILEO E5a 1191.795 AltBOC(15,10) Yes
E5b
E1 1575.42 MBOC(6,1,1/11) Yes
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MONITORING AND ASSESSMENT OF GNSS OPEN SERVICES
information for users when they are using its service, to minimize possible
adverse effects and to improve quality of service. On the other hand, based on
compatibility and interoperability, the GNSS system can bring not only a great
leap in improved performance and quality of navigation service, but also large
degradation due to signal interference problems between systems. Carrying on the
monitoring and assessment of GNSS Open Services can help to deal with these
problems. It can enhance the reliability of open service on one hand, and, on
the other hand, from the standpoint of system monitoring and assessment on the
comprehensive properties of multi-system open services, could improve compat -
ibility and interoperability performance between each system, providing decision-
support information for maintenance and management of the multi-system.
Since 1997, Stanford University has been under contract to support the U.S.
GPS Joint Program Office by regularly monitoring the L-band transmissions of all
newly launched and currently operational GPS satellites. The goal of this program
is to verify that all deployed satellites are consistently and reliably performing
according to the specifications. Stanford University has been measuring the signal
power, code delay, frequency content, and bandwidth to verify the proper opera -
tion of satellite constellations. Currently, Stanford University is upgrading the RF
and data-collection systems at a 47 m- (150 ft-) diameter steerable antenna (“The
Dish”) that has been used to collect these measurements. Meanwhile, it can also
monitor and analyze other countries’ satellite navigation systems.
In September 2005, the Institute of Communications and Navigation of the
German Aerospace Center (DLR) established an independent monitoring station
for analyzing GNSS signals. The core of this facility is a 30-m deep space antenna
located at DLR ground station at Weilheim, Germany. The integrated measure-
ment system fulfills the highest quality standards to obtain high-accuracy mea -
surements from raw data of GNSS signals to perform precise analyses. After the
commissioning phase of SVN49, relative data were collected in order to provide
a basis for analyzing the signal anomaly. After the SVN49 signal anomaly was
first noticed by this monitoring station, they started a detailed investigation of this
issue using the high-gain antenna.
Stanford and the DLR have already formed the cooperation mechanism for
joint monitoring and assessment of GPS and Galileo signals.
ELEMENTS AND METHODS FOR MONITORING
AND ASSESSING GNSS OPEN SERVICES
The work of monitoring and assessing of GNSS Open Services can be divided
into the following layers: constellation state layer, spatial signals layer, navigation
information layer, and service performance layer. Before choosing and determin -
ing the elements and methods of assessment, we should, in the sight of different
users’ requirements, take into comprehensive consideration organic connections
between different layers, as well as characteristics of independent elements. So
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the independence of open services for a single system cannot be neglected in
front of multi-systems. Those finally determined elements and methods should
be open, extensible, and compatible. So when a new system and its open signals
appear, this monitoring system can analyze them as well. In addition, the function
and role of third-party monitoring cannot be fulfilled unless real-time monitor-
ing and real-time release are emphasized when monitoring and assessing GNSS
Open Services.
Constellation State
Constellation state is one of the decisive factors for satellite navigation
systems to realize their service performance. So real-time monitoring and assess-
ment play a significant role for the users to use open services safely and reli -
ably. Monitoring and assessment of the constellation state include the following
content.
Constellation State
Constellation state refers to the working state of a single satellite or that of
each satellite in GNSS constellation at a particular moment. Common working
states can be divided into normal working state, testing and maintenance state,
fault state, etc. The number of satellites in various states and their orbit distri -
butions are used to describe those working states. In addition, such features as
the launch date and service life of each satellite can also be used as a reference
in assessing satellite state. Besides, information on constellation malfunction,
maintenance, and management released alone by each satellite navigation system
is also an important source of information for monitoring and assessing constel -
lation conditions.
Constellation DOP
Constellation DOP indicates values of various DOPs of healthy satellites in
their service range in a single or GNSS constellation, including GDOP, PDOP,
HDOP, VDOP, TDOP, etc. As an influence factor of satellites geometry distribution
on the error of navigation, positioning, and timing, DOP can be a comprehensive
reflection of the geometry distribution and health condition of constellations. As
for single-system constellations, instantaneous DOP is the most direct indicator for
assessing performances. When it comes to multi-system constellations, instanta -
neous DOP can also be used as an important reference indicator for assessing the
navigation and positioning performance of interoperable open signals.
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MONITORING AND ASSESSMENT OF GNSS OPEN SERVICES
Number of Visible Satellites
The number of visible satellites is still an important indicator for assessing
the space-time condition of constellations. Its instantaneous value has a strong
dependence on instantaneous DOP, whether it is a constellation of a single system
or multi-systems. As the interoperability of GNSS Open Services comes true,
the availability of more visible satellites will definitely reduce the sensitivity of
a single satellite to service performance and improve observations redundancy
at the same time. As a result, the precision, reliability, and availability of their
services can be improved greatly.
Spatial Signals
To assess the quality of GNSS spatial signals, relative assessment experiments
should be taken from time domain, frequency domain, modulation domain, and
correlation domain.
Time Domain Characteristics
To obtain baseband signals, those digital intermediate frequency signals col -
lected by a high-gain antenna should be conducted by quadrature carrier stripping
and Doppler removing using a software receiver. Then we can draw time domain
waveforms. And based on these, some characteristics such as the edge shape of
one chip, code sequence, code rate, code shape, degree of digital distortion and
analog distortion, etc. could be analyzed in detail (Hegarty and Ross, 2010).
Besides, eye diagrams of actual signals and ideal signals could be displayed on the
same graph to observe their similarity. In the meantime, related parameters of eye
diagrams, for example, open degree and noise tolerance, etc., can be calculated.
Thus we can assess the quality of received signals from time domain properties.
Frequency Domain Characteristics
Frequency domain characteristics are analyzed mainly with offline analysis
software, assisted by some standard measuring instruments such as a real-time
spectrum analyzer and so on. Through the test on signals from such aspects as car-
rier frequency, power spectrum and its envelope, bandwidth and center frequency,
beamwidth between two zero point on main lobe, etc., we can see the difference
of power spectrums between actual signals and ideal signals. In addition, some
other indicators such as spectrum asymmetry or distortion, signal stray, and carrier
leakage, etc., can be assessed comprehensively. Thus we can assess the quality of
received signals from frequency domain properties.
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Modulation Domain Characteristics
Both signal vector diagram and histogram are analyzed in detail mainly
with offline analysis software, assisted by some standard measuring instruments
such as a vector signal analyzer and so on. Using offline analysis software, vec -
tor diagrams of received signals can be drawn, with that of ideal signals in the
same diagram. Then we can easily compare these two vector diagrams. Besides,
error vector diagram can be constructed to extract indicators such as the phase
orthogonality, carrier orthogonality, amplitude imbalance of I/Q channels, etc.
In this way, phase error and amplitude error caused by channel distortions and
noise interference and so on could be analyzed. In addition, histograms drawn by
offline analysis software can be used to assess noise level. Using a vector signal
analyzer, a signal vector diagram can be drawn, with its center frequency offset,
SNR, EVM value, etc. shown on the screen. We can also see its stability by root-
mean-square deviation calculated by this analyzer.
Correlation Domain Characteristics
Correlation domain characteristics of received signals are analyzed mainly
from aspects such as the correlation curve, correlation loss, curve symmetry, code
delay, and S curve deviation of DLL discriminator, etc., by offline analysis soft -
ware (Lu and Zhou, 2010). The correlation curve of received signals is compared
with that of ideal duplicated code sequences to see its asymmetry and false lock
probability. Thus we can assess the degree of correlation distortion caused by
band limited filter, noise, multipath, cross-correlation, etc.
Navigation Information
Navigation information refers to those parameters such as satellite constella-
tion, satellite clock correction, ionosphere delay, time system deviation, etc., that
are provided by a satellite navigation system. It is the most important factor
that affects system service performance and is one of the most important factors for
monitoring and assessing GNSS Open Services signals.
Message Validity
The verification of navigation message validity includes the following two
points—consistency verification and the rationality and validity verification. As
for consistency verification, various parameters such as time information, constel-
lation, satellite clock, ephemeris, correction information, and so on are verified to
see if they are set and updated correctly according to the ICD file. In the period
of rationality and validity verification, it is necessary to determine according to
the specific attribute and generation method of each parameter.
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MONITORING AND ASSESSMENT OF GNSS OPEN SERVICES
Accuracy of Ionosphere Delay Correction
Model parameters of ionosphere delay correction are very important to
single-frequency users. Those ionosphere models and parameters in each satellite
navigation system are far from different. Accuracy of ionosphere delay correction
has a close relation not only with model types but also with accuracy and update
frequency of parameters. It can be assessed by obtained values of ionosphere delay
using double-frequency or multi-frequency pseudorange observations.
Accuracy of GNSS Time Deviations
GNSS time deviation reflects the deviations among timing biases of each sat-
ellite navigation system. It is important basic data to realize GNSS compatibility
and interoperability. And its accuracy will directly affect the PVT calculating
precision for various GNSS user equipments, especially for timing equipments.
So monitoring GNSS time deviations has more requirements for equipment to
get more reliable external accuracy.
Validity of Deviation Parameters Between Different Frequencies
Monitoring of deviation parameters between different frequencies contains
the following two parts. One is the time deviations of different frequency signals
when passing through satellite-borne equipments; these deviations have some -
thing to do with the calibrated values and signal frequency. The second is the
time deviations among different modulated codes for the same carrier, known as
the phase consistency between carrier and pseudo-code.
Service Performance
Satellite navigation systems provide three kinds of basic services—positioning,
velocity measuring, and timing (PVT)—for all types of users. Its service perfor-
mance is commonly described by such indicators as precision, availability, integrity.
and continuity (DOD, 2008).
Precision
The precision of spatial signals includes URE, URRE, URAE, and UTE. It
is an important indicator to assess the effect of satellite ephemeris and forecasted
clock deviation on the error of positioning, velocity measuring, or timing. To
assess the precision of signals, it is necessary to calculate the precise orbits and
clock deviation afterwards.
Service precision is used to describe the deviation between measured value
and the ideal value of positioning, velocity measuring, or timing for system
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users. It equals UERE multiplied by DOP, where UERE is determined by URE
(User Ranging Error) and UEE (User Equipment Error). UERE can be calculated
from the expression UERE = (URE)2 +(UEE)2 , and it is dependant on errors of
satellite atomic clock, ephemeris, atmosphere model, multipath effect, receiver
clock deviation, etc.
Availability
Service availability refers to the time percentage when the error of position -
ing, velocity measuring, or timing can meet the required threshold in a period
of time (a return cycle) and in a specified service area. According to the expres -
sion that precision equals UERE multiplied by PDOP, service availability can be
changed to DOP availability when setting UERE.
Integrity
Service integrity mainly refers to the probability for a navigation system to
provide a timely alarm within the limited period when the error of its positioning,
velocity measuring, or timing is larger than the threshold. It is generally expressed
by alarm threshold, alarm time, and hazard misleading information (HMI), where
alarm time refers to the maximum time delay allowed from the time a malfunc -
tion starts to the time an alarm generates. In addition, HMI probability refers to
the dangerous probability when the current measured value falls in the range of
alarm threshold.
Continuity
Service continuity refers to the time percentage when a satellite navigation
system can continuously meet required service precision in a period of time and
specified service area. The average continuity of service can be calculated accord-
ing to MTBF (Mean Time between Failures) and MTTR (Mean Time to Repair)
under the condition of the satellite’s unplanned interrupt.
FRAMEWORK OF IGMAS
Architecture and Functions
To monitor and assess GNSS Open Services worldwide, it is very neces -
sary to construct an iGMAS. The basic functions of iGMAS should include data
monitoring and collecting, data transmitting, data storing, data analyzing, and
information release. Figure 1 shows its architecture.
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MONITORING AND ASSESSMENT OF GNSS OPEN SERVICES
Communication satellite
GLONASS BeiDou GALILEO
GPS
Satellite
communication
Internet
Ground tracking
Data Center
network
Satellite
communication
Internet
Analyzing Center
Users
FIGURE 1 Framework of iGMAS.
Jiaoetal_Fig1.eps
landscape
Data Monitoring and Collecting
Data monitoring and collecting refers to the collecting and measuring of
GNSS navigation signals, in addition to the collecting of environmental observa -
tion data (such as electromagnetic data, meteorological data). The main functions
include:
1. Providing 4-overlap coverage observations for integrity monitoring and
precise orbit determination.
2. Real-time monitoring on the quality of all GNSS satellite signals using
digital multi-beam antennas and related equipment.
3. Realizing continuous and sophisticated observations on key satellites
using a 30-m high-gain antenna and related equipment.
Equipment for monitoring and data collecting mainly includes anti-multipath
omnidirectional antennas, multi-beam antennas that can receive all GNSS signals
in the visible world (with equivalent diameter of 2.4 m and gain of 28 dB), a 30-m
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114 GLOBAL NAVIGATION SATELLITE SYSTEMS
antenna, monitoring receiver, RF observations collecting equipment, baseband
signal collecting equipment, delay calibrating equipment, meteorological sensing
equipment, and electromagnetic environment analyzing equipment. Some other
auxiliary equipment includes atomic clocks, data processor, network switches, etc.
Data Storing
Basic tasks of data storing include the classifying, storing, and management of
monitored and collected data, and analyzing results, other data, or information, etc.
There are some data transmission links such as the Internet, satellite link
(VSAT), and wireless mobile communication network, etc.
Data Analyzing and Information Release
Data analyzing and information release refers mainly to the classifying and
processing of GNSS monitoring data. That means comprehensive analysis of
GNSS signals and information to assess its service performance. For example,
analyzing constellation characteristics such as the number of visible satellites,
constellation state, and constellation DOP; analyzing navigation signal proper-
ties from time domain, frequency domain, modulation domain, and correlation
domain; verifying the validity of navigation information, such as navigation mes -
sage, accuracy of ionosphere delay correction, accuracy of GNSS time deviations,
validity of time deviation parameters between different frequencies; and assessing
the precision, availability, integrity, and continuity of GNSS Open Services. And,
in the meantime, the release of statistical information on the working states of
GNSS satellites to users based on those comprehensive analysis results. Here the
equipment required includes real-time states displaying equipment, analyzing,
and assessing software, servers, working stations, network exchanging equipment,
mass storage, etc.
Data Transmission
Basic tasks of data transmission include data exchanging, control instruction
transmission, and transmitting released information to users.
There are some data transmission links such as the Internet, satellite link
(VSAT), and wireless mobile network, etc.
Tentative Plan of iGMAS Implementation
Preliminary Configuration Scheme
In iGMAS, those tracking stations scattered worldwide are used to implement
data collecting. There are mainly two factors in considering their configuration:
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MONITORING AND ASSESSMENT OF GNSS OPEN SERVICES
1. To achieve signal-quality monitoring, it is necessary to use multi-beam
antennas and a 30-m high-gain antenna to track satellites continuously. So
at least those tracking stations should meet the requirement of 1-overlap
coverage of satellites.
2. To achieve satellite-integrity monitoring, those tracking stations should
meet the requirement of 4-overlap coverage of satellites.
Here the tracking stations are selected from existing IGS stations, and a grid-
analysis method is used to optimize their layout (Stanton and Strother, 2007), with
the analysis range between 65° N and 65° S and the height of 19,000 km. Those
grids are divided into 1°*1° with the height angle’s deadline of 15°.
To meet the two requirements described above, preliminary analysis results
shows that 6 tracking stations and 24 stations are needed. In Table 2, we can see
the locations of iGMAS tracking stations. Two kinds of optimal design methods
for 1-overlap coverage and 4-overlap coverage are shown in Figures 2 and 3,
respectively.
Operational Mode
Here the iGMAS can be constructed through international cooperation among
providers and global civil users of the four global navigation systems.
The basic unit of iGMAS is called a node. Nodes can have five functions of
data collecting and monitoring, data transmitting, data storing, data analyzing,
and information release.
All nodes can be divided into three levels. Level one has all the five func-
tions described above; level two has functions like data collecting, transmitting,
TABLE 2 Locations of iGMAS tracking stations
Name Location Name Location
BEIJ* China MAS1 Spain
PERT* Australia BAHR Bahrain
RCMN* Kenya ONSA Sweden
LPGS* Argentina SANY China
CAGS* Canada IRKT Russia
TAH1* France WLMQ China
CHAT New Zealand NOUM France
KOKB America KERG France
COSO America HART South Africa
FAIR America CAS1 Antarctic
BOGT Colombia OHI3 Antarctic
FORT Brazil KELY Greenland
* Denotes those tracking stations belonging to both 4-overlap and 1-overlap coverage.
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FIGURE 2 Optimal design of 1-overlap coverage stations.
Jiaoetal_Fig2.eps
bitmap
FIGURE 3 Optimal design of 4-overlap coverage stations.
Jiaoetal_Fig3.eps
bitmap
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MONITORING AND ASSESSMENT OF GNSS OPEN SERVICES
storing, and analyzing; level three has only two functions of data collecting and
transmitting. To realize the goal of data sharing, each node provides data to the net
while automatically extracting data from it to perform signal assessing. All nodes
in level one will join together to realize the monitoring and assessment of GNSS
Open Services and information release. The net can work regularly through the
collaborative work of its nodes, which can access or exit the net freely.
PERFORMANCE MONITORING AND ASSESSING
FOR BEIDOU SYSTEM
Precision Monitoring and Assessing of Spatial Signals
To monitor and assess the performance of BeiDou open services from the
information layer, a BeiDou monitoring and assessment system was built suc-
cessfully in November 2007. It consisted of a monitoring and assessment center,
one data analyzing center, and six tracking stations. The tracking stations were
located in Xi’an, Shanghai, Changchun, Kunming, Urumqi, and the Antarctic,
with each station equipped with BeiDou measuring receivers, high-precision
atomic clocks, and computers, etc. The goal was to calculate the precise orbits
and clock deviation of BeiDou navigation satellites, to assess the performance of
satellite clocks and parameter accuracy of ionosphere models, and to verify the
validity and rationality of navigation message, etc.
Quality Monitoring and Assessing of Spatial Signals
In February 2009, the first BeiDou signal-quality monitoring and assessment
system was built successfully by NTSC, Chinese Academy of Sciences, in Lintong
district of Xi’an, Shaanxi province. This system consisted of a 7.3-m antenna, an
RF receiving subsystem, an RF observational data-collecting subsystem, a base -
band signal-collecting subsystem, monitoring receivers, a calibrating subsystem, a
data storing subsystem, and so on. Obtained results showed that this system could
achieve some deeper tasks of GNSS signal-quality monitoring and assessment
using many standard measuring instruments, monitoring receivers, high-speed
data collecting equipments, and offline analysis software.
At present, two key technologies of GNSS signal-quality monitoring and
assessment, that is, offline technology for analyzing signal performance based
on correlation curve and channel calibrating technology, have strived to make
important technological breakthroughs, while the anti-interference technology
has also made much progress. Since its successful running in April 2009, this
system has completed successfully signal-quality monitoring and assessment for
BeiDou GEOs and IGSOs. In the meantime, it has also collected and analyzed
GPS MEOs signals and Galileo Glove-B signals.
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CONCLUSIONS
Monitoring and assessment of GNSS Open Services can bring much benefit
to the healthy development of GNSS. It can not only extend the depth and breadth
of GNSS applications, but also provide the foundation for all kinds of civil users
to use system services safely and reliably. There is sufficient evidence to show that
the iGMAS proposed in this paper is technically feasible. For example, the pre -
liminary exploration of BeiDou in its open services monitoring and assessment,
the long-term successful operation of IGS, and achievements in navigation signal
monitoring and assessment made by Stanford University and DLR, etc. However,
the construction of iGMAS is a global and long-term work, and it needs more
organizations and countries to be involved. So it is very necessary to implement
international cooperation.
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of Navigation (ION GNSS 2010), Portland, Oregon, September 2010.
Lu, X.C., and H.W. Zhou. 2010. Methods of analysis for GNSS signal quality (in Chinese). Scientia
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