design and testing of an intelligent gps tracking loop for...

Design and Testing of an Intelligent GPS Tracking Loop for Noise Reduction and High Dynamics

Applications

Design and Testing of an Intelligent GPS Tracking Loop for Noise Reduction and High Dynamics

ApplicationsBy: Ahmed M. Kamel

Position, Location And Navigation (PLAN) GroupDepartment of Geomatics Engineering

University of Calgary

ION Alberta Lunch Meeting 22 OCT 2010

OutlineOutlineMotivation

Background

Fuzzy logic background

New design for FLL assisted PLL

Experimental Setup

Results

Conclusions

Motivation

Background

Fuzzy logic background

New design for FLL assisted PLL

Experimental Setup

Results

Conclusions

Design and Testing of an Intelligent GPS Tracking Loop for Noise Reduction and High Dynamics Applications2

MotivationMotivationChallenges:1- Missiles dynamics2- Signal interference

Design and Testing of an Intelligent GPS Tracking Loop for Noise Reduction and High Dynamics Applications

PLL bandwidth (BW) requirements :1- Missiles dynamics wide BW2- Signal interference narrow BW

3

Basic PLL block diagramBasic PLL block diagramLocally

generatedΔθ or Δωor both

-Specifies the loop bandwidth-Can be 1st , 2nd, or 3rd order-3rd order filter is chosen because it is sensitive to dynamic jerks


FLL Assisted PLL Classic DesignFLL Assisted PLL Classic Design

T

∑∑ ∑T 0.5

Z‐1

∑∑ ∑T 0.5

Z‐1

∑ ∑

FrequencyDiscriminatorFrequency

Discriminator

PhaseDiscriminator

PhaseDiscriminator

θ

ω

Velocity accumulatorAcceleration accumulator

•3rd order PLL assisted with 2nd order FLL•All gains are calculated from the loop bandwidth which is a design parameter

To NCO

Kaplan, E. D. (2006) Understanding GPS: Principles and Applications, Second Ed., Artech House, INC., Norwood, MA 02062


Fuzzy Logic Fuzzy Logic What Is Fuzzy Logic?

•Quantification of linguistic information while allowing for imprecision

Knowledge Base &

Fuzzy Inference

Tracking ErrorsTuning

parametersError

Sensors

LinguisticVariables

Defuzzification

Physical Variables

Fuzzification

Physical Variables

LinguisticVariables


Fuzzy Frequency Phase lock Loop (FFPLL)

Fuzzy Frequency Phase lock Loop (FFPLL)


Membership Functions Design (1/2)Membership Functions Design (1/2)

Design and Testing of an Intelligent GPS Tracking Loop for Noise Reduction and High Dynamics Applications

0 10 20 30 40 50 60 70-30

-20

-10

0

10

20

30

Time (s)

phas

e e

rror

(deg

)PLL phase discriminator output (deg)

-100 -80 -60 -40 -20 0 20 40 60 80 1000

100

200

300

Phase error (deg)

HistgramGuassian fitting

-BIG -SMALL ZERO +SMALL +BIG+MED-MED

8

Membership Functions Design (2/2)Membership Functions Design (2/2)Type Fuzzy Variable Number of MFs

Input(1) Phase 9

Input(2) Frequency 7

output NCO Tuning frequency 11

θ↓ ω→ -B -M -S Ze +S +M +B

-B +B +MB -M -M -M -MB -B-MB +B +MB -SM -M -M -MB -B-M +B +MB -S -SM -M -MB -B-S +B +MB Ze -S -SM -MB -BZe +B +MB +S Ze -S -MB -B+S +B +MB +SM +S Ze -MB -B+M +B +MB +M +SM +S -MB -B+MB +B +MB +M +M +SM -MB -B+B +B +MB +M +M +M -MB -B

B: Big, MB: Medium Big, M: Medium, SM: Small Medium, S: Small, Ze: Zero.

Fine Tuning Coarse TuningCoarse Tuning


Experiment Setup (1/2)Experiment Setup (1/2)

GPS H/W simulator Spirent GSS7700

National InstrumentRF Front End

Post processing

Parameters ValueSampling frequency fs = 10 MHzIntermediate frequency fIF = 0.42 MHzSampling Complex


Experiment Setup (2/2)Experiment Setup (2/2)

0 20 40 60 80 100 120 1400

500

Time (s)

Ve

l. (m

/s) Reciever dynamics

0 20 40 60 80 100 120 1400

10

20

Time (s)

Acc

. (g

)

0 20 40 60 80 100 120 1400

50

100

Time (s)

Jerk

(g/

s)51.3

51.451.5

51.651.7

-115

-114.8

-114.6

-114.41000

1500

2000

2500

3000

Latitude (deg)

Missile Maneuver

Longitude (deg)

Hei

ght

(m)

Scenario: Highly dynamic- Velocity: 400 m/s- Acceleration: up to 15 gJerk: up to 50 g/s


Results (1/3)Results (1/3)Continuity


Results (2/3)Results (2/3)Speed and Accuracy


Results (3/3)Results (3/3)Doppler Tracking Jitter (average)

1 2 3 4

PLL 14 HzFLL/PLL 3/4 Hz

PLL 4 HzFFPLL

0

1

2

3

4

5

Channel #

Ave

rag

e D

opp

ler j

itte

r (H

z)


ConclusionsConclusionsIt is difficult to solve for dynamic robustness and

noise rejection at the same time using classic PLL or FLL assisted PLL

Fuzzy systems can be used to replace the classic FLL assisted PLL noise filter and provide better dynamic performance and better noise rejection level

The proposed FFPLL performs as if it is a very narrow noise bandwidth PLL, in terms of noise level, and its dynamic performance is as fast as a wide PLL performance

Future work: Adaptive shaping of the input MFs to accommodate C/No variations due to signal interference



Questions????Questions????

• References• Bogatin, E. (2003) Signal Integrity - Simplified, Prentice Hall PTR• Kaplan, E. D. (2006) Understanding GPS: Principles and Applications, Second Ed.,

Artech House, INC., Norwood, MA 02062• Mao, W. L., H. W. Tsao, and F. R. Chang (2004) "Intelligent GPS receiver for robust

carrier phase tracking in kinematic environments," IEE proceedings. Radar, sonar and navigation, vol. 151, (no3), pp. 171-180

• Mao, W. L. (2007) "Applications of New Fuzzy Inference-Based Tracking Loops for Kinematic GPS Receiver," Circuits, Systems, and Signal Processing, Volume 26, (Number 1), February, 2007, 91-113

• Ross, T. J., J. M. Booker, and W. J. Parkinson (2002) Fuzzy Logic and Probability Applications, American Statistical Association Society for Industrial and Applied Mathematics, Alexandria, Virginia

• Sadati, N., and A. T. Balaei (2006) "Fuzzy goal coordination of large-scale systems using Tamura's method," Vancouver, BC, Canada, 1355-1361, Institute of Electrical and Electronics Engineers Inc.

• Simon, D., and H. El-Sherief (1994) "Fuzzy phase-locked loops," Las Vegas, NV, USA, 252-259, Publ by IEEE

• Unglaub, R. A. G., and D. Chit-Sang Tsang (1999) "Phase tracking by fuzzy control loop," Aerospace Conference, 1999. Proceedings. 1999 IEEE, 57-66 vol.55,

• Zadeh, L. A. (1965) "Fuzzy Sets," Information and Control, Volume 8, 338-353

• References• Bogatin, E. (2003) Signal Integrity - Simplified, Prentice Hall PTR• Kaplan, E. D. (2006) Understanding GPS: Principles and Applications, Second Ed.,

Artech House, INC., Norwood, MA 02062• Mao, W. L., H. W. Tsao, and F. R. Chang (2004) "Intelligent GPS receiver for robust

carrier phase tracking in kinematic environments," IEE proceedings. Radar, sonar and navigation, vol. 151, (no3), pp. 171-180

• Mao, W. L. (2007) "Applications of New Fuzzy Inference-Based Tracking Loops for Kinematic GPS Receiver," Circuits, Systems, and Signal Processing, Volume 26, (Number 1), February, 2007, 91-113

• Ross, T. J., J. M. Booker, and W. J. Parkinson (2002) Fuzzy Logic and Probability Applications, American Statistical Association Society for Industrial and Applied Mathematics, Alexandria, Virginia

• Sadati, N., and A. T. Balaei (2006) "Fuzzy goal coordination of large-scale systems using Tamura's method," Vancouver, BC, Canada, 1355-1361, Institute of Electrical and Electronics Engineers Inc.

• Simon, D., and H. El-Sherief (1994) "Fuzzy phase-locked loops," Las Vegas, NV, USA, 252-259, Publ by IEEE

• Unglaub, R. A. G., and D. Chit-Sang Tsang (1999) "Phase tracking by fuzzy control loop," Aerospace Conference, 1999. Proceedings. 1999 IEEE, 57-66 vol.55,

• Zadeh, L. A. (1965) "Fuzzy Sets," Information and Control, Volume 8, 338-353


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