This document discusses GNSS errors, their sources, and mitigation techniques. It describes various unintentional errors from satellite clocks, orbits, and the ionosphere and troposphere. Receiver errors and multipath errors are also discussed. Intentional interference can come from jamming or spoofing. Real-time and post-processing techniques can be used to mitigate errors, such as using ground station corrections or processing with base station data. The goal is to understand error sources and how to apply models or corrections to improve GNSS positioning accuracy.

1. GNSS Errors, Sources and Mitigation Techniques
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2. Topics to be Covered/Objectives
Introduction to GNSS Errors
Sources of Errors
Error mitigation techniques
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3. At the end of this session, trainee will be able to:
Describe various sources of GNSS errors
Explain the mitigation techniques of GNSS errors
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4. Introduction to GNSS Errors
GPS to GLONASS and Galileo has intrinsic error sources that have to be taken into
account when a receiver reads the GNSS signals from the constellation of satellites in
orbit.
A GNSS receiver measures the apparent transit time(Pseudo range) of the satellite
signal from the satellite to the user. Pseudo range consists of the propagation delay and
receiver clock bias.
For the accurate user position calculation following parameters plays important role:
 1) Time of transmission
 2) Time of Reception
 3) Satellite signal propagation medium
 4) Position of satellites
Introduction to GNSS Errors
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5. Sources of error
Unintentional
Satellite
dependent
error
Satellite
clock
error
Relativistic
effect
Clock drift
Satellite
orbit
error
Selective
availability
Receiver
dependent
error
Receive
r clock
Cycle
slip
Antenn
a phase
center
movem
ent
Receive
r noise
Medium
based error
Ionosp
heric
based
Tropos
pheric
based
error
Station
based error
Multipat
h error
Intentional
Sources of GNSS Errors
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6. Satellite Clock Errors
• First effect:
the frequency is set a bit slow before launch (10.22999999545 MHz).
• Second effect:
It is attributable to eccentricity (0.02) of orbit causing time error of 45.8
ns. This error is corrected in GPS receiver itself avoiding an error of about
14 m.
Relativistic effect : Clock in orbit will appear to run faster than
on earth
• Rubidium clocks: 1 to 2 parts in 1013 over a period of one day or about
8.64 to 17.28 ns per day
• Caesium clocks: stability improves to 1 to 2 parts in 1014 over 10 days
• Hydrogen masers: 1 part in 1014.
• Unavoidable temporally variant clock errors are source of a significant
bias which are monitored by the control segment during tracking data
analysis
Clock drift: Stability of GPS clocks:
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7. Unintentional Errors
Satellite
Orbit/
Ephemeris
Errors
Receiver
Dependent
Error
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8. Ionospheric Based Error
The ionosphere regions can absorb or dampen radio signals, or they can bend radio waves, as well as
reflecting the signals.
The specific behaviour depends on both the frequency of the radio signal as well as the characteristics
of the ionosphere region involved.
Scientists constantly measure and produce computer models of the ever-changing ionosphere so that
people in charge of radio communications can anticipate disruptions.
Medium Based Error
Ionospheric Models for Single Frequency Receivers
1.Single frequency receivers need to apply a model to remove the ionospheric refraction which
can reach up to few tens of meters, depending on the elevation of rays and the ionospheric
conditions
The models used in GPS and Gallileo are described in klobuchar model, and NeQuick Model. The
GPS/Galileo satellites broadcast the parameters needed to run these ionospheric models.
In GLONAS, there is no ionospheric model applied and thus, there is no broadcast of any
parameter. However, any of the GPS or GALILEO ionospheric models could be used for GLONASS
signals, by applying a correction factor given by their relative squared frequencies ratio.
AAI-ISRO developed IONO model, known as IMLDF (Indian Multi Layer Data Fusion) which is
capable to correct IONO errors over Indian airspace.
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9. MLDF Model
 IGM-MLDF employs innovative scheme of modelling at two shell heights.
Through empirical analysis the shell heights of 250 km and 450 km are chosen.
The ionosphere measurement source for these two shells is obtained
through a novel idea of utilizing both the Indian reference equipment's
(INREEs) residing at each of INRESs
Kriging algorithm is applied to compute the grid vertical delay error and
error estimates at the IGP in the designated shell heights
A new approach of data fusion is applied at the vertical IGPs to fuse delays
and confidences at 350 km shell height
Ionosphere storm detection algorithm utilizes goodness of fit test to protect
the user from irregular behaviour of ionosphere
Ionospheric Based Error
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10. Medium Based Error
Troposphere Based Error
This delay depends on the temperature, pressure, humidity as well as the
transmitter and receiver antennas location
Tropospheric effects are not frequency dependent for the GNSS signals. Hence,
the carrier phase and code measurements are affected by the same delay
The only way to mitigate tropospheric effect is to use models and/or to estimate
it from observational data
Troposphere can be successfully modelled using the values of temperature,
pressure and relative humidity and satellite elevation angle
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11. Station Based Error
Multipath Error
The interference by multipath is generated when a signal arrives, by different ways, at the antenna
Its principal cause is the antenna closeness to the reflecting structures.
This error is different for different frequencies. It affects the phase measurements, as well as the code
measurements
The Multipath Estimating Delay-Lock-Loop (MEDLL) isa method for mitigating the effects due to multipath
within the receiver tracking loops.
The MEDLL does this by separating the signal into its line-of-sight and multipath components
The multipath signal will always arrive after the direct path signal
The MEDLL estimates the amplitude, delay, and phase of each multipath component using maximum
likelihood criteria.
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12. Unintentional Error
Jamming directed at non-aviation users
DME: as it shares a frequency band with GNSS
Spoofing
GNSS repeaters and pseudo-lites
Unintentional Error
Spectrum Regulation
States should prohibit all actions that lead to disruption of GNSS signals and
should develop and enforce a strong regulatory framework governing the use of
intentional in-band radiators, including GNSS repeaters, pseudo-lites, spoofers and
jammers.
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13. Error Mitigation Techniques
Real time technique
Corrections are computed from
ground station observations and
then uploaded to geostationary
satellites.
Post processing technique
Take advantage of base station data
available on the Internet. Base
station files are posted on the
Internet daily or hourly for GPS
users. They are less immediate but
offer greater accuracy than real-time
corrections.
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14. Questions?
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15. Thank You
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