soutenance ouzeau

Ecole Nationalede l’Aviation civile

Laboratoire de Traitement du Signal et des Télécommunications

/47

Degraded Modes Resulting from

the Multi Constellation Use of GNSS

Christophe OUZEAU

Ph.D. Defense

1



/47

Context

• Multiplication of satellite radio navigation systems (Global Navigation

Satellite System: GNSS), the variety of radio navigation signals increases

• Global Positioning System (GPS) provides an accurate positioning service but

its standalone use cannot meet the civil aviation requirements

• The GPS is modernized progressively with new signals transmitted by new

satellites (GPS block II-R, II-F and III)

• Galileo is the European positioning system and will be operational in the next

years

• Galileo E1, E5a/E5b and GPS L1 C/A, L1C, L5 signals in Aeronautical Radio

Navigation Services (ARNS) frequency bands, interest for civil aviation

2

Context



/47

Context• The EURopean Organization for Civil Aviation Equipment provides a European

forum for resolving technical problems with electronic equipment for air

transport

• The EUROCAE deals with aviation standardization and organizes Working

Groups , in particular, the WG 62 (Galileo) objectives are to*:

– Make recommendations to the Galileo project on issues of concern to civil

aviation airborne and ground equipment

– Produce a list of working assumptions for the operational use of Global

Navigation Satellite System

– Produce a Minimum Operational Performance Standard for airborne

GPS/Galileo/Satellite Based Augmentation System receiver equipment

– Produce a MOPS for both ground and airborne equipment for precision approach

– Address the need for standardisation associated with the introduction of dual

frequency Satellite Based Augmentation System services

3

Context

*Terms Of Reference approved by EUROCAE council on July 8th, 2003



/47

Introduction

• This thesis was conducted in coordination with the WG 62 and focuses on the

multi-system and multiple frequency issues of satellite navigation in aviation

applications

• We propose a combined receiver architecture and we look for algorithms

performances for civil aviation application, we have to consider standardized

assumptions and comply with International Civil Aviation Organization (ICAO)

requirements

• We focus on the interferences detection and the particular case of ionospheric

code delay estimation, when a frequency is lost because of a jammer

4

Introduction



/47

Outline

1. GNSS applied to civil aviation operations

2. Combined receiver architecture

3. Interference detection

4. Ionospheric code delay estimation

5. Conclusion and future works

5


2. Combined receivers architecture




Outline



/47

Signal In Space performance requirements

Typical

Operation

Accuracy

Horizonta

l 95%

Accuracy

Vertical

95%

Integrity

risk

Time

To

Alert

Horizontal

Alert limit

Vertical

Alert

limit

Continuity Availability

En-route3.7 km

(2.0 NM)N/A 1-1× 10-7 /h 5 min 7.4 km N/A

1×10-4/h to

1×10-8/h

0.99 to

0.99999

En-route,

Terminal

0.74 km

(0.4 NM)N/A 1-1 ×10-7 /h 15 s 3.7 km N/A

1×10-4/h to

1×10-8/h

0.99 to

0.99999

Initial

approach

Intermediate,

NPA,

Departure

220 m

(720 ft)N/A 1-1× 10-7 /h 10 s 556 m N/A

1×10-4/h to

1×10-8/h

0.99 to

0.99999

APV I

16 m

(52 ft)

20 m

(66 ft)

1-2× 10-7 in

any

approach

10 s 40 m 50 m1-8×10-8 /h

per 15 s

0.99 to

0.99999

APV II16 m

(52 ft)

8 m

(26 ft)

1-2× 10-7 in

any

approach

6 s 40 m 20 m1-8×10-8/h

per 15 s

0.99 to

0.99999

Category I

Precision App

16 m

(52 ft)

6 m to 4m

(20ft to

13ft)

1-2× 10-7 in

any

approach

6 s 40 m15.0 m

to 10 m

1-8×10-8/h

per 15 s

0.99 to

0.99999

6

1. GNSS applied to civil aviation

1.1. SIS performance requirements

Source: [ICAO, 2006]

• Future combined receivers will have to comply with the following ICAO requirements:

ICAO SIS performance requirements



/47

Modes of operation

7


1.2. Modes of operation

• Aircraft modes of operation are defined in [EUROCAE, 2007]:

– Nominal mode of operation: the receiver achieves the required level ofperformance, using a pre-described, preferred combination of signals

– Alternate mode: the receiver achieves the same level of performancethan in the nominal mode, using alternative means or augmentations.The receiver enters into this mode when one or several signals of thenominal mode are not available

– Degraded mode: the receiver is unable to achieve the level ofperformance of the nominal mode. In this case, an alert must be flagged



/47

Modes of operation and GNSS components (1/2)

8

Typical

Operation

Nominal Alternate Degraded

En-route

down to

NPA

•Galileo Safety of Life

•Galileo E1/ E5b + SBAS

•GPS L1/L5 + SBAS

•GPS Single Frequency + SBAS

•Galileo Single Frequency +

Safety of Life

•Combination of all available

pseudo ranges + RAIM

No integrity information

APV I•Galileo Safety of Life

•Galileo E1/E5b + SBAS

•GPS L1/L5 + SBAS



SBAS


Safety of Life





• The WG 62 identified promising GNSS components combinations as nominal,alternate and degraded means to provide navigation solution and integrity tothe aircraft

• We focused on the APV I phase of flight because:

– It requires vertical guidance

– It has more restrictive requirements than En-route down to NPA

Source: ConOps [EUROCAE, 2008]Identified nominal, alternate and degraded modes GNSS combinations for En-Route to NPA and APV I

phases of flight



/47

Modes of operation and GNSS components (2/2)

9

Typical

Operation


En-route

down to

NPA


•Galileo E1/ E5b + SBAS

•GPS L1/L5 + SBAS



Safety of Life



No integrity information

APV I•Galileo Safety of Life


•GPS L1/L5 + SBAS



SBAS


Safety of Life





• The Galileo Safety of Life service (E1/E5b) satisfies needs for safety critical users and iscompliant with civil aviation applications. Integrity provided in the I/NAV message(satellites clock and ephemeris deviation) [EUROCAE, 2007], computation of the integrityrisk at the alert limit, no protection level computation

• The Satellite Based Augmentation System is used to provide ephemeris + clock +ionospheric corrections + DON’T USE flags to calculate protection levels (GPS SBAS)

• The Receiver Autonomous Integrity Monitoring algorithm is used to provide integritywhen GPS SBAS and Galileo SoL are not available

Source: [EUROCAE, 2008]Identified nominal, alternate and degraded modes GNSS combinations for En-Route to NPA and APV I

phases of flight



/47

Onboard combined receivers architecture (1/2)

10

• We proposed the following receiver architecture to the WG 62, for each mode of operation:

– Navigation function selects the GNSS components combinations and provides navigation solution and

integrity

• Protection levels calculation by augmentation systems: GBAS, SBAS, ABAS (RAIM)

• Fault Detection and Exclusion : alerts

• Integrity risk for Galileo SoL

– Detection function monitors degradations at different levels within the receiver


Navigation

function:

Selection of the

appropriate signal

combination and

integrity method

among all those

available

Detection

function:

Detection of GNSS

signals and

integrity means

loss or recovery

GNSS combination

selected

Performance level reached,

loss or recovery of

component

The detection function is

not an integrity monitoring

function, it monitors

performances degradation

Operation mode navigation and detection functions



/47

Onboard combined receivers architecture (2/2)

11

• We proposed this receiver architecture to the WG 62 based on the

following switching strategy

• Switches between modes of operation depends upon the availability

of the GNSS components combinations

• When the receiver enters a degraded mode, it flags an alert


Begin operation:

selection of the

performance level

required

Performance level

Navigation

Detection

Nominal mode of

operation

Navigation

Detection

Navigation

DetectionNo nominal

modes

available

No

min

al m

od

es

ava

ila

ble Alternate mode of

operation

Degraded mode of

operationNominal

modes

available

No nominal and

alternate modes

available

No nominal

modes available

and alternate

mode available

Nominal modes available

Alert



/47

Conclusion about combined receivers• The proposed architecture, based on switching between GNSS components

combinations, is driven by detection functions:

– Detection algorithms must be implemented to flag a loss or recovery of

component, more precisely, to monitor if the system is compliant with the

performance needed to start or continue an operation: integrity, continuity,

accuracy and availability matched or not

– The receiver can decide to initiate a switch after a detection flag

• In case of degraded mode, the receiver must flag an alert [EUROCAE, 2007], and:

– We propose to try to maintain as long as possible some performances during the

current operation (reconfiguration of the navigator)

– Otherwise, other means must be used to continue the current phase of flight (INS

etc.)

• We look for algorithms performances for civil aviation application under standardized

assumptions, regards to parameters linked to civil aviation requirements (False alarm

rate, missed detection probability, protection levels…). In particular, we focused on

interferences detection and ionospheric code delay estimation

12


2.1. Conclusion



/47

Interference detection

• Aircraft embedded receiver interference environment:

– Pulsed interferences (DME/TACAN on L5, E5a/E5b, Radars on E5b) can affect

in particular GPS L5 and Galileo E5a, their mitigation is already studied in

details for the WG 62 [Bastide, 2004], [Raimondi, 2008]

– In band Continuous Waves (CW) and Narrow Band (NB) interferences can

affect all GNSS signals (even simultaneously), for instance the GPS L1 C/A and

Galileo E1 OS signals [Bastide, 2001], [Rollet, 2008]

13









/47

Interference detection and combined receivers

• Future civil aviation combined receivers will be composed of filters

([EUROCAE, 2007]), for resistance to jammers (RF and IF filters). The resulting

interference threshold masks provide the characteristics of the interferences

mitigation receiver capability

• For civil aviation applications, interferences with power level below the

interference masks defined in [EUROCAE, 2007], are expected to generate

acceptable tracking errors

• But, CW can stay a certain time near highest amplitudes code spectrum lines

of the GNSS signals and generate larger tracking errors than expected by the

WG 62, signal-jammer relative Doppler shift rate, [Rollet, 2008] determined

this rate between 2.9 Hz/s and 3.1 Hz/s

• We focus on CW detection, with the maximum interference power specified

by the WG62: -155 dBW and a Doppler shift rate equal to 2 Hz/s

14


3.1. Context



/47

Impacted GNSS signals• Priority is given to L1 C/A (BPSK) and E1

OS/SoL (CBOC) signals, L5 and E5 major

threats are pulsed interferences (same band

than DME) already studied [EUROCAE, 2007]

• The PRN codes correlated at the receiver level:

• Theoretical receiver correlation functions

considering L1 C/A (BPSK) in blue, in the

following, E1 OS is assumed as a BOC signal

(red) instead of CBOC (black) 15

Characteristics GNSS signal

GPS L1 C/A Galileo E1 OS

Code line PRN 6 38

Freq w.r.t L1 227 kHz 673.5 kHz

Power w.r.t total

power-21.29 dB -28.81 dB

FR

fFC 2FC-Fc-2Fc

FR

fFC 2FC-Fc-2Fc

L1 C/A

E1

• PSD of the materialized PRN code (black) :

• PSD of the materialization waveform (green)

• PSD of the PRN sequence (blue)


3.2. Simulation assumptions

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1-0.5

0

0.5

1

Code Delay (Chips)

Nor

mal

ized

Cor

rela

tion

Fun

ctio

n

BPSK(1)BOC(1,1)CBOC(6,1,1/11)

No

rma

lize

d c

orr

ela

tor

ou

tpu

ts

Code delay (chips)

Characteristics of highest amplitude code lines

for each signal, within the main lobes



/47

Impact of CW interference on signals processing

• A CW hitting a code spectrum line, affects the receiver correlators outputs, code and carrier tracking outputs and code-carrier smoothing (100 s-Hatch filter)

• We used a MATLAB Rx simulator to process the GPS L1 C/A, the PRN 6 worst code line is impacted by – 155 dBW CW, Doppler shift rate = 2 Hz per second. CW starts 200 seconds after the tracking loop

16Phase tracking error (rad)Code tracking error (m)


3.3. Impact of CW on signals processing

C/N0 at the correlator output (dBHz)

39 dB Hz L1 C/A

DLL: 1st order,

BW: 1 Hz, dot

product

discriminator

PLL: 3rd order,

BW: 10 Hz,

arctan

discriminator



/47

Elaboration of detection techniques

17

• Because of the CW, sine waves appear on top

of the correlation peak when interference

occurs (on the I channel for instance)

• Their amplitudes are dependent of:

– The jammer power,

– The PRN code spectrum line amplitude,

– The frequency offset between jammer and

nearest PRN code line

• Detection is achieved through monitoring of multiple correlators outputs (68

for GPS L1 C/A and 72 for Galileo E1 OS, from the spectrum characteristics,

code lines spacing)

• Two proposed detection algorithms tested over 1.5 106 outputs for each

correlator:

– Monitoring instantaneous FFT of correlators outputs

– Monitoring Auto Regressive model errors of all correlators time variations

L1 C/A correlator output

Correlator index

No

rmal

ized

co

rrel

ato

r o

utp

uts


3.4. Detection algorithms

I prompt

correlator

output



/47

Detection algorithms performance evaluation process

• The performance evaluation process can be described in a few steps:

1. A detection criterion is defined from correlators outputs characteristics

2. Detection criterion parameters are set during a training stage without

interference under APV I phase of flight conditions (dynamics, multipath,

Doppler)

3. The detection threshold is set such that PFA < 1.6 10-5 /sample (for APV I

continuity, [ICAO, 2006])

4. Then the PMD value is determined, generating interferences, PMD = (number of

tests where the detection criterion is lower than the pre-defined threshold) /

(total number of tests)

5. The impact of non-detected interferences on tracking error at any time is then

discussed

18


3.4. Detection algorithms: performance

evaluation



/47

Simulation assumptions• We considered the following simulation assumptions for a receiver onboard an aircraft:

• Normal aircraft maneuvers generated according to maximum dynamics specifications([RTCA, 2006]):

• Multipath generated each time a tracking procedure is initiated thanks to theAeronautical Channel model (DLR), considering a 10 degree elevation satellite in view(Galileo satellites mask angle, [EUROCAE, 2008])

• Doppler shift between the jammer and the signal, with a Doppler shift rate of 2 Hz/s

• Received signals carrier to noise ratio at the correlator output level, according to thereceived power level specified in [EUROCAE, 2008]:

19

Dynamics parametersTypical maximum values for normal

aircraft manoeuvres ([EUROCAE, 2007])

Ground speed 800 Kt

Horizontal acceleration 0.58 g

Vertical acceleration 0.5 g

Total jerk 0.25 g/s


3.4. Detection: simulation assumptions

GNSS signal GPS L1 C/A Galileo E1 OS

C/N0 39 dBHz 34 dBHz



/47

Algorithm 1: FFT of the correlators outputs• Detection algorithm monitors the Fast Fourier

Transform of correlation outputs (snapshot),[Bastide, 2001]

• Criterion is defined as:

• Parameters inside criterion determinedthrough a training simulation withoutinterferences and under APV I conditions

• Instantaneous maximum of the correlationpeak FFT determined at each instant during theperformance test simulation

20

)(max_

)(max_max_

fourierstd

fouriermeanfourierinst −


3.4. Detection algorithms: FFT model

No

rmal

ized

co

rrel

ato

r o

utp

uts

Chip spacing

Test distributionNu

mb

er o

f co

rrel

ato

r o

utp

uts

Threshold for APV I

Correlators outputs

for the L1 C/A, PRN

6, impacted by a -

155 dBW CW



/47

Performances of the algorithm 1 (1/2)

21

• For GPS L1 C/A PRN 6 worst line, with:

• Maximum normal aircraft dynamics,

• Multipath (DLR model, elevation= 10°),

• Signal to jammer Doppler shift rate of 2 Hz/s,

• C/N0 = 39 dBHz at correlator output,

• PFA = 1.6 10-5 /sample (APV I)

• Tracking error when CW not detected

• DLL: 1st order, BW: 1 Hz, dot product

discriminator,

• PLL: 3rd order, BW: 10 Hz, arctan discriminator

• PMD as a function of raw tracking error.

PMD * (number of times tracking error = N

meters mod 1 meter)/number of tracking

errors



Mis

sed

det

ecti

on

pro

bab

ility

N =Raw tracking error in meters

PMD = 6.67 10-5



/47

Performances of the algorithm 1 (2/2)• Results for other L1 C/A PRN strong code

lines within main lobe, exemple of PRN 10

worst line, low tracking errors but same

PMD, considering:


• Multipath (DLR model, elevation= 10°),

• Signal to jammer Doppler shift rate of 2

Hz/s,

• C/N0 = 39 dBHz at correlator output

• PFA = 1.6 10-5 /sample (APV I)

• For E1 OS, non detected raw tracking

errors never exceed 9 meters (1.2 m after

smoothing) obtained for PRN 38 worst line

(Power of lines lower than L1 C/A lines),

• Same assumptions except C/N0 = 34 dBHz

22





/47

Algorithm 2: Multichannel AR model (1/2)• Interference implies abnormal

correlators outputs time variations

• A 3 rd-order multichannel AutoRegressive model used to monitorsimultaneously all correlators outputs,at t [Marple, 1987]:

23

∑=

−=3

1

][][][ˆk

iii ktxkatx


3.4. Detection algorithms: AR model

(xi: ith correlator, a: AR coefficient)

No

rmal

ized

co

rrel

ato

r o

utp

uts

No

rmal

ized

co

rrel

ato

r o

utp

uts

Chip spacing

Correlators outputs for the L1 C/A,

PRN 6, impacted by a -155 dBW CW



/47

Algorithm 2: Multichannel AR model (2/2)

• AR model error is determined, firstduring a training stage:

• And then during simulation tests, onstudied samples:

• Detection criterion is calculated(norm of the E vector containing thecorrelators outputs AR errors):

24

∑=

−+=−=3

1

][][][][ˆ][][k

iiiiii ktxkatxtxtxte

∑=

−+=−=3

1000000 ][][][][ˆ][][

k

iiiiii ktxkatxtxtxte

][

][log

0 tE

tE


3.4. Detection algorithms: AR model

• When impacting the L1 C/A PRN 6 worst

code line, considering:


• Multipath (DLR model, elevation=

10°),

• Signal to jammer Doppler shift rate of

2 Hz/s,

• C/N0 = 39 dBHz at correlator output

• PFA = 1.6 10-5 /sample

PMD = 10-5



/47

Estimation and repair algorithm• When the CW detection is successful,

we launch CW parameters estimation

thanks to a third order Prony model

• We repaired the correlators outputs (L1

C/A)

• We observed the code tracking error

(m), considering:

• DLL: 1st order, BW: 1 Hz, dot product

discriminator

• PLL: 3rd order, BW: 10 Hz, arctan

discriminator

• Red plot: when the L1 C/A PRN 6

highest code spectrum line is

impacted by a -155 dBW CW

• Blue plot: tracking loop output, the

sine wave is removed from the

correlator output

Statistics Before

correction

After

correction

Raw

Mean 19.9 m - 0.009 m

Standard

deviation10.5 m 1.9 m

Maximum 45.2 m 8.6 m

Smoothed

Mean 13.7 m 0.03 m

Standard

deviation

5.3 m0.04 m

Maximum 18.4 m 0.16 m

25


3.5. Estimation and repair algorithm

Raw and smoothed code tracking errors

statistics before and after correction

Code tracking error (m) as a function of time (sec)



/4726

Conclusions on interference detection (1/2)• Simulation assumptions:

• Worst cases considered in terms of:

- Interference power under interference mask: maximum CW power -155 dBW,

- Code spectrum lines impacted (on PRN 6 for L1 C/A, on PRN 38 for E1 OS),

- Dynamics (maximum parameters as defined in [EUROCAE, 2007]),

- Multipath (low elevation angle)

- Minimum C/N0

• Algorithms proposed:

• Two detection algorithms based on multi correlators outputs monitoring:

- Computation of correlators FFT

- Multi channel AR model of correlators outputs

• Results obtained:

• FFT: PMD = 6.67 10-5, AR: PMD = 10-5 , but interference probability of occurrence

unknown, integrity risk = PMD * probability of occurrence?

• Maximum smoothed tracking error resulting from non-detected CW: 15 m (raw: 52

m) for GPS L1 C/A and 1.2 m (raw < 9 m) for Galileo E1 with FFT algorithm

• Capability of repair algorithm: std of the tracking error divided by 5


3.6. Conclusions



/47

• Detection algorithms reduce integrity risk due to interferences

• When the CW was not detected we studied the impact on code tracking error

• When the CW was detected, a repair algorithm tested with good performances

• Possibility to switch to other GNSS components after detection, during APV I :

27Details of a detection function for the particular case of interference detection for APV I


3.6. Conclusions

Conclusions: contributions for CA receivers (2/2)



/47

Perspectives

28

• Need to determine minimum number of useful correlators without loss ofperformance for each signal

• Make simulations to determine how far interference detection + repair + RAIMprovide integrity and accuracy compliant with APV I requirements

• But interference probability of occurrence unknown• Tracking loop behavior during abnormal aircraft manoeuvres, repair algorithm

capability?• Tests over actual measurements must be performed

• The major risk induced by the loss of frequency is due to the ionosphere if theSBAS is not available, during a degraded mode


3.6. Perspectives








/47

Ionospheric code delay estimation: context

• In a dual frequency nominal mode of operation, smoothed ionospheric-free range

measurements are used. The ionospheric error is estimated and corrected thanks to the use

of dual frequency measurements

• In an alternate mode of operation, the SBAS is used to provide the ionospheric corrections

• In the case of loss of frequency leading to a degraded mode, an estimation of the

ionospheric delay may be provided either by the Klobuchar model for GPS or the NeQuick

one in case of Galileo. But, the models only estimate part of the error ([RTCA, 2006], [GSA,

2008])

• This implies large overbounded ionospheric std values, that does not allow to support flight

operations that require vertical protection levels computation

– In the following, we propose algorithms to keep the accuracy of the dual frequency

ionospheric delay estimation compatible with APV I, in a degraded mode of operation29


4.1. Context

Typical

Operation


APV I



•GPS L1/L5 + SBAS



SBAS


Safety of Life





/47

Ionospheric code delay estimation: introduction

• In order to keep the accuracy of the dual frequency nominal mode for APV I, apotential solution is the ionospheric delay estimation through the Code MinusCarrier Divergence [NATS, 2003], indeed, the receiver outputs code and carrierphase measurements

• But the carrier phase measurements can be affected by cycle slips, the integrityof the CMC technique has to be evaluated

• First, we focus investigations on the integrity of the CMC technique by adding acycle slip detection algorithm and assessing its performance

– Availability of the detection method within Europe, for GPS and Galileoconstellations, considering maximum normal maneuvers [EUROCAE, 2007]

• Then, a Kalman filtering technique is proposed to estimate the CMC parametersand to maintain the accuracy of dual frequency measurements

30


4.2. Introduction



/47

Candidate methods for cycle slip detection

• We identified different cycle slip detection algorithms:

– Monitoring derivatives of carrier phase measurements

– Comparing smoothed and raw code pseudo ranges

– Making a phase prediction using Doppler measurements: robust against

high aircraft manoeuvres, needs Doppler measurements

• Algorithm tested (Doppler-predicted phase):

– Compute predicted phase:

• Fd: Doppler frequency

• : time delay between the previous and the current measurement

– Cycle slip is detected if:

31


4.3. Cycle slip detection



/47

Cycle slip probability of occurrence calculation during APV I

32

• Pr[occurrence of cycle slip] =

Where:

is determined from classical carrier tracking

theory [Holmes, 1990], taking into account:

- The tracking loop std:

- The integration time TI

- The C/N0 = 30 dBHz

- The loop bandwidth WL = 10Hz

- The receiver dynamics ( )

- Jmax = 0.25 g/s (normal manoeuvers) or 0.74 g/s

(abnormal manoeuvers)

- is the signal wavelength

SIGNAL

TI PROBABILITY OF OCCURRENCE

OVER 150 SECONDS

NORMAL

MANOEUVRES

ABNORMAL

MANOEUVRES

GPS L1

C/A,

Galileo

E1

4 ms 1.0 10-3 9.2 10-2

10 ms 7.5 10-4 6.1 10-2

20 ms 4.7 10-4 3.8 10-2

GPS L5,

Galileo

E5a

4 ms 9.1 10-4 9.0 10-2

10 ms 6.8 10-4 6.0 10-3

20 ms 2.4 10-4 3.4 10-2

Galileo

E5b

4 ms 9.1 10-4 9.0 10-2

10 ms 6.9 10-4 6.0 10-3

20 ms 2.4 10-4 3.4 10-2

• =150 seconds corresponds to an aircraft

total approach duration, it includes APV I

t∆


4.3. Cycle slip detection



/47

Cycle slip detection and CA requirements

• The integrity risk due to cycle slip is expressed as the product of the algorithmmissed detection probability by the cycle slip probability of occurrence

– Integrity risk due to undetected cycle slips is taken as 10-8/approach:

• SIS integrity risk: 2. 10-7/approach or to manufacturer: 10-7 /approach[RTCA, 2006]

• But risk not only allocated to cycle slips, and probability to haveabnormal dynamics

– Probability of occurrence of cycle slips for all signals and all integrationtimes is assumed as 10-3 over 150 s for normal manoeuvres and up to 10-1

for critical abnormal ones

Missed detection probability is taken as PMD_theory =10-5 for normalmanoeuvres and 10-6 for abnormal manoeuvres

• False alarm rate is taken as PFA = 1.6 10-5/sample from the APV I continuityrequirements ([ICAO, 2006])

33


4.3. Cycle slip detection: requirements



/47

Cycle slip detector performance evaluation

• The methodology used to determine the smallest detectable bias with the

proposed detection algorithm can be summarized in a few steps:

1. Pseudo ranges measurements are generated without cycle slips. The detection

criterion is compared to varying thresholds

2. When PFA < 1.6 10-5/sample, the corresponding threshold is kept in memory

3. Then, pseudo ranges measurements are generated again with varying cycle slip

amplitudes. The missed detection probability is estimated for each amplitude

4. The experienced missed detection probabilities are compared to the

theoretically derived ones for normal (PMD_theory = 10-5) and abnormal

manoeuvres (PMD_theory = 10-6)

5. When PMD < PMD_theory, the corresponding cycle slip amplitude is recorded

as the minimum detectable error

34


4.3. Cycle slip detection: performance

evaluation



/47

Simulation assumptions

• Assumptions on pseudo ranges, worst conditions:

– Maximum dynamics defined in MOPS [EUROCAE, 2007] for normal and abnormal aircraft manoeuvres

– Multipath: at low elevation angles (10 degrees)

– Noise: standard deviation of PLL and DLL outputs, assuming C/N0 = 30 dB Hz

– Ionosphere and troposphere by drawing successive independent random Gaussian values multiplied by classical std models ([RTCA, 2006])

35


4.3. Cycle slip detection: assumptions



/47

Cycle slip detector performances

• These smallest detectable cycle slips imply an error on position which depends on

the geometry. The availability of protection against cycle slip compatible with APV I

depends on geometry and must be computed at every second

36

Continuity requirements Integrity requirements

False alarm rate obtained as a function of

the detection threshold used

Missed detection probability obtained as

a function the minimum detectable cycle

slip amplitude


4.3. Cycle slip detection: performances

PMD_theory



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Cycle slip detector performance: availability

• Determination of smallest detectable cycle slips for required PMD and PFA

through simulations

• Those cycle slips amplitudes were projected on the horizontal plane andthe vertical axis. When the position errors were lower than the alert limits,the detection algorithm is declared available

• The availabilities were computed over Europe for GPS and Galileoconstellations in standalone modes

37





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Availability of cycle slip detection over Europe

• Availability estimated overEurope, for both GPS andGalileo constellations, duringAPV I, maximum normaldynamics

• GPS (first map), elevation mask angle: 5 degrees, period of revolution: 24 hours

• Galileo (second map): elevation mask angle: 10 degrees elevation, period of revolution: 10 days

• Low availability mostly due tovertical requirements:

• HAL = 40 m, VAL = 50 m

38



Availability of cycle slip detection over Europe, APV I, degraded mode

Lati

tud

eLa

titu

de

Longitude-9° E 50° E

31°

N7

0°

N7

0°

N3

1°

N

97

,5 %

10

0 %

10

0 %

98

%

GPS: min=97%,

Galileo: min=98%



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Conclusions on cycle slip detection

• The results obtained are promising (min availability = 97% for GPS, 98%for Galileo), since:– The availability must take into account the probability of falling into degraded

single frequency mode

– The performance test algorithm relies on worst case assumptions (simulatedpseudo ranges: low elevations, low C/N0)

• Continuity, integrity and availability of cycle slip detection plus Code MinusCarrier divergence technique is evaluated

• In the following, the accuracy of ionospheric code delay estimation isstudied using a Kalman filter to estimate the CMC parameters

39


4.3. Cycle slip detection: conclusion



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• Code ( ) minus carrier phase( ) allows to estimate ionospheric code delay :

• Where:

- N is the carrier phase ambiguity from one satellite and at a given frequency (x)

- w and v are noise and multipath coming from code (w) and carrier phase (v)

Code Minus Carrier Divergence and Kalman filtering

40

xkxkxkxkxkxkxk vwNIP ++−=− λφ 2

( )satNbNNNI _210 ... X =

xφxP


4.4. CMC Kalman filtering

eR

EReceiver

IPP

Receiver

zenith

WGS 84

Ionosphere thin

shell model

[RTCA, 2006]

h

Re

• A Kalman filter is used to estimate ionospheric delay and

ambiguities:

•Where:

• is the mean vertical ionospheric code

delay at the Ionosphere Pierce Point,

• is the obliquity factor

depending on the satellite elevation angle [RTCA, 2006]

• The ionospheric delay at the receiver zenith can be

expressed thanks to I0 plus South-North (A) and West-

East (B) gradients: , in the following

we assume A=B=0



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Choice of actual aircraft measurements

• To comply with actual aircraftconditions, the Kalman filterperformance is evaluated thanksto measurements made by L1/L2dual frequency receiver onboarda flying Airbus aircraft around theBlagnac airport (Toulouse,France)

• 8 laps recorded, minimumnumber of 7 satellites in view

• Loss of L2 frequency, leading toGPS L1 C/A only simulated

• Comparison between single L1C/A Kalman estimations andclassical nominal dual (L1 C/A +L2) estimations

41

Aircraft path around the Blagnac airport


4.4. CMC Kalman filtering: measurements

Blagnac

Toulouse



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Kalman filter estimations

• The zenith ionospheric code delay is

estimated thanks to the Kalman filter

(in red) and compared to mean dual

frequency estimation (in green) over

all satellites in view

• The filter is initialized in dual

frequency mode and runs after a loss

of L2 frequency

42

Number of

samples

Mean vertical ionospheric delay

over all tracked satellites

measurements

Method Mean Standard

deviation

Dual

frequency3 104 11.1 m 3.3 m

Single

frequency3 104 10.9 m 1.5 m


4.4. CMC Kalman filtering: results

Co

de

de

lay a

mp

litu

de

(m

)

Time elapsed since the beginning of the simulation (sec)

6 m

24 m

Peaks observed due

to losses of

satellites,

results obtained

for one

particular set of

measurements



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Conclusions and future works on Kalman estimations• The performance of ionospheric delay estimation has been estimated in single

frequency mode for civil aviation application

• The method used is the Kalman filtering of Code Minus Carrier measurements SF : 10.9

m, DF : 11.9 m, and the std divided by 2

• The Kalman filter must be initialized in dual frequency mode, which implies to record

dual ionospheric code delay estimations to start the filter

• Trade-off between filter observation and state confidence. In our model, the

ionosphere state noise variance larger than observation noise variance (smooth

outputs), in case of scintillation, the filter innovation would increase (under-estimated

perturbation) and the filter would take time to converge (TTA during APV I?)

43


4.4. CMC Kalman filtering: conclusion








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Conclusions: combined receivers architecture (1/3)

• Original contribution: future combined receivers architecture is proposed

and discussed. A switching-based strategy between nominal, alternate

and degraded modes of operation is described

• The switching strategy depends upon the targeted operation (with or not

vertical guidance). In particular, this thesis focuses on the APV I phase of

flight

• To initiate the switches between modes of operation, detection algorithms

are implemented. The performances of such detection algorithms are

assessed through simulations

• The results obtained allow to determine whether or not the algorithms

can be applied to civil aviation operations

• Another important point assessed is how to maintain as long as possible

the levels of performance required during degraded modes

44

5. Conclusions

5.1. Combined receivers architecture



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Conclusions: interference threat during APV I (2/3)

• Focus on CW interference detection: can stay a long time near high power code

spectrum lines, maximum power in compliance with the interference masks

defined in [EUROCAE, 2007]

• Focus on the GPS L1 C/A and Galileo E1 OS signals: highest power code spectrum

lines

• Multi correlators-based algorithms, continuity-compliant, provide low PMD, under

worst conditions (multipath, C/N0, dynamics), alleviate integrity monitoring

• Integrity risk not discussed because of the lack of information about interference

probability of occurrence

• When a CW is detected:

– We propose the receiver can switch to another available GNSS combination

to continue the current operation

– Another solution can consist in estimating the CW characteristics and

removing the interference effects from the correlators outputs, promising

results

• When the CW is not detected:

– The impact on tracking loops outputs is studied45

5. Conclusions

5.2. Inteferences detection



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Conclusions: ionospheric code delay estimation (3/3)

• Method proposed: Code Minus Carrier divergence technique + Kalman + cycle

slip detector under APV I degraded mode of operation

• Original contribution: cycle slip detector integrity and continuity compliant

• The availability of this technique has been studied for GPS and Galileo

constellations

• Worst cases considered: dynamics, C/N0, multipath, atmosphere

• Expected low probability to fall into single frequency mode, to be determined

• Availability expected to be compliant with APV I requirement

• Original contribution for accuracy: CMC parameters estimated thanks to a

Kalman filter initialized in dual frequency mode, accuracy maintained

• Kalman algorithm tested over a set of actual measurements

• Need to detect ionosphere scintillations

46

5. Conclusions

5.3. Ionospheric delay estimation



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Future works

• The objective of this study (and future investigations) is to converge

towards a final architecture of receiver for each operation in all identified

configurations of operation modes

• The detection algorithms proposed in this thesis focus on interferences

(CW) and cycle slips detection. It is of interest to combine those

algorithms with RAIM-type algorithms in future investigations to know

precisely the performance of those combined algorithms for civil aviation

use

• This thesis focuses on the detection function and not on the navigation

function. However, future works may include a complete simulator of

protection levels computation, taking into account all the components

described

47

5. Future works

soutenance ouzeau

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