Transcript EGNOS ICD presentation 22-06

SUPPORT TO IWG25
12th June 2013
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Contents
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
Reminder IWG#24
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2 families of candidate ICD’s
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UDRE ICD (ICD1 - limitation 51SV  no further studied) and its alternative (up to
90 active SV)
DFRE ICD (ICD2) and its alternative (use of spare CI bits to refresh DFRE when
less than 4 const.)
At IWG#25
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8 April, 2015
Analysis of clock prediction models (incl. OBAD)
ICD1 alternative / ICD2 Performance comparison
Conclusion - Comparison with IWG partners results
(Stanford) and Recommended way forward
PROSBAS
2
Analysis of clock prediction models
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To characterise the accurracy of clock prediction models
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Two different clock correction propagation models
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Two different clock estimates used as inputs for the analysis
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UDRE_ICD (ICD_1): RRC method (inherited from L1 MOPS)
DFRE_ICD (ICD_2): Linear clock model
Equivalent to current EGNOS design (EGNOS V2)
Potential evolution of EGNOS design: Precise Orbit and Clock
estimation algorithms (State of the art ODTS foreseen for EGNOS V3)
Same set of SV’s (from different blocks) and days used for the
comparison
8 April, 2015
PROSBAS
3
Analysis of clock prediction models
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
Definition of Study Cases. ICDs
Clock estimation
UDRE ICD
DFRE ICD
magicSBAS_ODTS_UDRE_ICD
magicSBAS_ODTS_DFRE_ICD
magicSBAS_UDRE_ICD
magicSBAS_DFRE_ICD
(Input)
magicSBAS ODTS
Fast Corrections
magicSBAS Fast
Corrections
UDRE ICD
RCC method: Linear extrapolation
of two previous clock estimations
to current epoch
8 April, 2015
DFRE ICD
Linear Clock model: offset and drift clock computation
from previous clock estimation data and propagation to
current epoch
PROSBAS
4
Analysis of clock prediction models
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
Results comparison
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Conclusion : two ways of improvement of clock corrections
propagation (valid for any ICD)
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•
8 April, 2015
Use Precise Orbit and Clock estimation algorithms in SBAS
Use a more accurate clock correction propagation method: Linear clock
model better than RRC
PROSBAS
5
Analysis of clock prediction models
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OBAD analysis
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Analysis to define a degradation model (OBAD or MT7/10 data)
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Acceleration model (ai parameter): from SBAS L1 MOPS
Polynomial model (Ccorr, Rcorr, Acorr): from DFRE proposal
Acceleration model (current L1 MOPS): to
be discarded.
Polynomial model OK
Recommendation: to tune scale factors for
Polynomial model
8 April, 2015
PROSBAS
6
Analysis of clock prediction models
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Conclusions
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Two ways of improving the extrapolation of clock corrections
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
Precise orbit and clock estimation algorithms in SBAS
Using a more accurate method for propagating the clock
corrections to the current epoch (linear clock model instead of RRC)
OBAD analysis
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8 April, 2015
Feasibility confirmed through experimentation that OBAD model
included in “L1/L5 SBAS MOPS to Support Multiple Constellations”
paper is feasible
Linear or polynomial degradation (no more quadratic as in L1 MOPS)
Include this model in UDRE ICD MT7/10
Highly recommended: a tuning of scale factors and effective ranges of
the OBAD to allow a better fit to the degradation factors
PROSBAS
7
SBAS L1/L5 ICD models:
Refinement of Definition & performances

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Strategy followed in this analysis
 Update the bandwidth considerations to refine key
parameters values (DeltaT_FC, DeltaT_IP) for each of the
candidate ICD’s
 Re-evaluate preliminary performances achieved with the
SBAS L1/L5 ICDs under analysis (ICD1, ICD2 and
alternatives)
8 April, 2015
PROSBAS
8
SBAS L1/L5 ICD models:
Refinement of Definition & performances
•
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Bandwidth tuned for 75% margins  FCs update intervals (DeltaT_FC values) used
to estimate the Delta_FC parameters (key parameter to estimate performance) updated
UDRE Alternative ICD (ICD1 alternative)
MT2
Update
MT2_Ne MT6-1 #
Int
MT2 # Mss w
Mss
SATS in SATS
MASK monit MT1
Num
Messages
per MT
MT
Update
interval
4C
3C
2C
1C
MT6-1
MT6-2 #
Mss
MT6-2
MT7+1
0
MT9
1
MT25 #
MT17 Mss MT25
MT12
1
1
1
3
120
0,0083
0,0083
0,0083
0,0083
60
0,0167
0,0167
0,0167
0,0167
300
0,0033
0,0033
0,0033
0,0033
300
0,0100
0,0100
0,0100
0,0100
MT28 #
Mss
MT30 #
MT 26 Mss
MT28 MT18
0
0
300
0,0000
0,0000
0,0000
0,0000
300
0,0000
0,0000
0,0000
0,0000
MT 30
TOTAL BW
91
82
58
31
91
68
45
24
120
0,0083
0,0083
0,0083
0,0083
54
24
11
5
4
3
4
2
0,0741
0,1250
0,3636
0,4000
1
1
0
0
6
0,1667
0,1667
0,0000
0,0000
1
1
1
1
6
0,1667
0,1667
0,1667
0,1667
23
17
12
6
240
0,09583
0,07083
0,05
0,025
46
34
23
12
240
0,1917
0,1417
0,0958
0,05
0
0
0
0
300
0,000
0,000
0,000
0,000
74,1574
71,7500
72,2803
68,8333
DFRE & DFRE Alternative ICD (ICD2 & ICD2 alternative)
SATS in SATS
MASK monit
MT_D
Upda MT_D
te Int No Mss MT_D
MT_B
MT_C
MT_F
MT_E
MT12
MT_G
MT18
MT30
No Mss
MT 26
MT 30
Num
Messages
per MT
MT
Update
interval
4C
91
91
120
0,0083
175
91
0,5200
6
0,1667
120
60
0,0083 0,0167
300
0,0033
120
0,0250
300
0,000
300
0,000
0
300
0,000
3C
68
68
0,0083
131
68
0,5191
0,1667
0,0083 0,0167
0,0033
0,0250
0,000
0,000
0
0,000
74,7417
2C
1C
45
24
45
24
0,0083
0,0083
87
47
45
24
0,5172
0,5106
0,1667
0,1667
0,0083 0,0167
0,0083 0,0167
0,0033
0,0033
0,0250
0,0250
0,000
0,000
0,000
0,000
0
0
0,000
0,000
74,5575
73,8972
1
1
1
1
1
3
0
0
TOTAL
BW
74,8333
 MT2 update intervals are much smaller than those considered in DFRE ICDs
8 April, 2015
PROSBAS
9
SBAS L1/L5 ICD models:
Preliminary Performances Summary
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Full System Protection Results (considering Integrity Message time-out for ICD2)
VPL 95% Nominal Case. ECAC + AFI
VPL 95% Optimistic Case. ECAC + AFI
14
12
12
10
10
8
8
ICD_1
6
6
ICD_1 Alt magicSBAS
ICD_1 Alt magicSBAS ODTS
4
ICD_1 Alt magicSBAS
4
ICD_2
ICD_2 Alt magicSBAS
2
ICD_1
ICD_1 Alt magicSBAS ODTS
ICD_2
2
ICD_2 Alt magicSBAS
ICD_2 Alt magicSBAS ODTS
ICD_2 Alt magicSBAS ODTS
0
0
VPL 95% Pessimistic Case. ECAC + AFI
16
14
12
 ICD1 alternative and ICD2 (with or w/o
alternative) provide quasi optimal
performance
10
ICD_1
8
ICD_1 Alt magicSBAS
6
ICD_1 Alt magicSBAS ODTS
4
ICD_2
ICD_2 Alt magicSBAS
2
ICD_2 Alt magicSBAS ODTS
0
8 April, 2015
NB:
- Pessimistic case slightly better for ICD1 alternative
than ICD2, yet felt due to (conservative) margins on
UDRE border effect in the model (effective
difference expected lower(tbc)).
- ICD1 performance suffers from DOP limitation when
more than 2 constellations
PROSBAS
10
SBAS L1/L5 ICD models:
Preliminary Performances Summary
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Full System Protection Results (considering Integrity Message time-out for ICD2)
Max VPL Optimistic Case. ECAC + AFI
Max VPL Nominal Case. ECAC + AFI
35
30
35 m
30
25
25
20
20
ICD_1
15
15
15 m
ICD_1 Alt magicSBAS ODTS
ICD_2
10 m
10
10
15 m
ICD_1 Alt magicSBAS ODTS
ICD_2
5
ICD_2 Alt magicSBAS
5
ICD_1
ICD_1 Alt magicSBAS
ICD_1 Alt magicSBAS
10 m
ICD_2 Alt magicSBAS
ICD_2 Alt magicSBAS ODTS
ICD_2 Alt magicSBAS ODTS
0
0
Max VPL Pessimistic Case. ECAC + AFI
40
35 m
35
30
25
ICD_1
20
ICD_1 Alt magicSBAS
15
ICD_1 Alt magicSBAS ODTS
10
ICD_2
15 m
10 m
ICD_2 Alt magicSBAS
5
ICD_2 Alt magicSBAS ODTS
0
8 April, 2015
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LPV-200: All cases below 35m
Cat I autoland (VAL 10m to 15m):
2 constellations cases always below 15m.
3 & 4 constellations and nom. & opt. cases
seem very promising especially with ICD1
alternative (and possibly also with ICD2,
since border effect is conservative in the
model), even for 10 m-threshold.
PROSBAS
11
ICD comparison
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
ICD comparison Status at IWG#25
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Availability: both ICD1 alternative and ICD2 (or its alternative)
achieve close to optimal performances: up to 4 constellation /
91SV’s, low DFREi/Delta FCi values (provided by optimised
ODTS and clock extrapolation), low VPL
•
ICD1 alternative (with up to 90 active SV)
 Flexible as per current L1 MOPS :
 Provides comfortable margins with respect to border effect
 Offers capability to rapidly react (updating all DFREi’s) upon event
 increasing (continuity) robustness
 not constraining system design
 Offers room for enhancement : removal of FC’s, replacement of user
RRC by system extrapolation parameter, optimised degradation model
and tuning of OBAD parameters
 Bandwidth limitation to be further analysed (LTC/MT28 rate)
8 April, 2015
PROSBAS
12
ICD comparison
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ICD2
 Basically tailored for simple scheduler
 Yet ICD2 rigidity (e.g. wrt. events impacting many SV, UDRE border
effect) compared to current L1 MOPS. This is due to limitation in
DFREi update mechanism
 ICD2 would deserve being enhanced with flexible/dynamic but simple
to implement mechanism (for instance by adding an on event pair of
MT6 like messages allowing to recover DFREi within 2s after a general
integrity alert message, or by another mechanism to be investigated)
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In the end, the enhanced ICD1 and enhanced ICD2 could
become very close to each other.
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Unification into a single/common (selected) DFMC ICD seems
now achievable target.
8 April, 2015
PROSBAS
13
Recommended way forward until end 2013 and for 2014
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
Analyse the enhanced ICD1 and enhanced ICD2 (as defined in
previous slide) so that
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ICD1 is better optimised (incl. for BW) see slide #12
ICD2 is made capable of handling dynamic events without constraining
the system design
(Tentatively) Unify the above enhanced ICD’s in a unique and
common (pre-)selected ICD < end of 2013
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Refine the mechanism to maintain integrity upon message loss
(handling of repetitions upon DFREi change, OBAD, DFREi
resolution table, etc.)
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2014 would then be devoted to validate/refine the very details of
the selected ICD (e.g. using EC/ESA pro-SBAS simulator)
 Objective : interim (validated) MOPS ICD < end 2014
8 April, 2015
PROSBAS
14