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• Check consistency of redundant GPS measurements
• Use residual as indicator of excessive position error
typical failure mode
position error
residual
threshold
protection radius
FALSE ALARM
DETECTED FAILURE
MISSED
DETECTION
SAFE
The Boeing Company W100.30
NSE Driven RNP Availability Observed From
IASL Rooftop on a Randomly Chosen day
0 5 10 15 20 25
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
GMT (Hours)
RNP
(NM)
2 Receiver Overlay - Day 174
Rcv X
Rcv Y
Typical RAIM Performance when SA was On
The Boeing Company W100.31
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5
0
10
20
30
40
50
60
70
80
90
100
RNP (NM)
% of
Observations
Less than
RNP
Observed Cumulative RNP distributions for 2 Receivers
Rcv X
Rcv Y
RNP Availability Observed From IASL
Rooftop on a Randomly Chosen day
RNP
(NM)
Rcv X Rcv Y
0.05 16.2 % 25.0 %
0.1 85.2 % 86.9 %
0.15 93.7 % 94.5 %
0.3 100 % 99.9 %
The Boeing Company W100.32
SA Transition
The Boeing Company W100.33
Removal of SA Resulted in Dramatic
Improvement in Accuracy
Data collected by
Boeing on rooftop
of IASL Lab
before and after
SA removal
GPS Accuracy Post SA
0 1 2 3 4 5 6
0.001
0.003
0.01
0.02
0.05
0.10
0.25
0.50
0.75
0.90
0.95
0.98
0.99
0.997
0.999
Horizontal Error [meters] – 24 Hours of Observations
Probability
Normal Probability Plot
24 Hours of data
Collected 6/24/00
In Seattle
RAIM Availability with SA Off
0 100 200 300 400 500 600 700 800 900 1000
0.001
0.003
0.01
0.02
0.05
0.10
0.25
0.50
0.75
0.90
0.95
0.98
0.99
0.997
0.999
HIL [Meters]
Probability
Normal Probability Plot
•Distribution of HIL from 3 Different MMR Manufacturers
~ RNP 0.1 nm
Receivers with SA Assumptions
Hard Coded in RAIM Algorithms
SA Aware Receiver
Based on data collected for 24 to 48
hours on the rooftop of the IASL on
a randomly chosen day shortly after
SA was turned off
GPS/INS Integrity Monitoring
􀂄 Grover Brown first suggested a method based on a bank
of Kalman Filters
􀂄 Two commercial products use a variant of this approach
– Honeywell: Multiple Solution Separation Method
– Litton: Autonomous Integrity Monitor Extrapolator
GPS/INS
Filter
1
IMU
GPS
Receiver
. . .
. . .
2
3
4
N
Comparison
Function
Fault Detection
Exclusion
Protection Level
Each Filter uses a different
combination of n-1 satellites
The Boeing Company W100.37
Results from Availability Modeling
This is based on
simulating thousands of
geometries and removing
satellites from the
constellation using a
Markov model for
satellite constellation
state probabilities
Assumptions on satellite
availability are very
conservative relative to
historical performance
Absolute value of
availability computed is
sensitive to assumptions
and the typical
performance should be
better than predicted
here in all cases.
The real value of this kind of analysis is to compare the relative performance of
different ABAS approaches
0 0.5 1 1.5 2 2.5 3 3.5 4
100%
99.999%
99.99%
99.9%
99%
90%
0%
RNP (nm)
RNP Availability (percent)
RNP Availability (24 hours) (24/6 + 0 WAAS Satellite Constellation)
Tightly Coupled (SA On)
Loosely Coupled (SA On)
RAIM (SA On)
Loosely Coupled (SA Off)
RAIM (SA Off)
GBAS Status
The Boeing Company W100.39
Ground Based Augmentation
Systems (GBAS)
GLONASS satellitSeSBAS satellite
GPS
satellite
SBAS signal
ranging source
only
VHF Data Broadcast
(VDB) Signal
Differential Corrections
Integrity data
and Path definition data
GBAS ground
facility
GBAS
reference
receivers
Ranging
sources
Navigation satellites
Status
information
40
Typical GBAS Ground Segment Equipment
Picture Courtesy
Okalahoma University
Pictures Courtesy
Honeywell Inc.
　
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