Lightning detection and localization using extended Kalman filter
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Transcript of Lightning detection and localization using extended Kalman filter
Lightning detection Lightning detection and localization using extended and localization using extended
Kalman filterKalman filter
Ines Ben SaïdInes Ben SaïdU2S(ENIT) U2S(ENIT)
SYS’COM Master SYS’COM Master 2008-20092008-2009
National Engeneering School of Tunis
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ReferencesReferences
1 - 1 - T. G. Wood, Geo-location of individual lightning discharges using impul-
sive vlf electromagnetic waveforms, Phd thesis, The department of electrical
engineering and the committee on graduate studies of stanford university, De-
cember 2004.
2 - 2 - S. A. Cummer, Lightning and ionospheric remote sensing using vlf/elf radio
atmospherics, Phd thesis, The department of electrical engineering and the
committee on graduate studies of stanford university, August 1997.
3 - 3 - R. E. Kalman, A new approach to linear filtering and prediction problems,
Transaction of the ASME Journal of Basic Engineering, (pp. 35{45), March
1960.
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Lightning DetectionLightning DetectionEarth+ Ionosphere = waveguide[ELF-VLF] = [300Hz-30KHz] [ELF-VLF] = [300Hz-30KHz]
radio atmospherics (‘sferic’) = Waves that propagates in the ELF/VLF band with low attenuation (~3dB/1000Km)
Lightning detection via VLF data analyses
Receivers
Transmitters
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VLF receiver at LSAMAVLF receiver at LSAMA
Hardware Software
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VLF receiver schemaVLF receiver schema
Two data types: - narrow band
- broad band
A/D
Converter
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Broad band signalsBroad band signals
transmitters
sferic
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Sferic caracteristicsSferic caracteristics
Much of the sferic energy lies in [5KHz-15KHz] band (Much of the sferic energy lies in [5KHz-15KHz] band (Cummer 2004 Cummer 2004 )) Duration ~4ms: - ~ 1ms VLF impulseDuration ~4ms: - ~ 1ms VLF impulse - ~ 3ms ELF slow tail- ~ 3ms ELF slow tail
(Cummer 2004 )(Cummer 2004 )
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Sferics detection methodSferics detection method
Identification Two successif instants must be separated with an delay >= 4ms (sferic duration) Determinate the simultaneous instants for the N/S and E/W signals.
Proposed procedure N = 60000 samples
Te = 100KHz
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Lightning localizationLightning localizationIMPACTIMPACT
Tow receivers are sufficientTow receivers are sufficientPrecision depend on optimization methodPrecision depend on optimization method
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Lightning localizationLightning localization
Arrival azimuth calculation Arrival azimuth calculation
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TriangulationTriangulation
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Results and limitesResults and limites
IMPACT method tested by simulation
Source [45°N 60°E]1st receiver : Vieques 2nd receiver : Palmer
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Proposed method: Extended Kalman filterProposed method: Extended Kalman filter
Observation
State
Interest : non linear optimization used in GPS localization
State representation
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AlgorithmAlgorithm
Initialisation Initialisation
PredictionPrediction
CorrectionCorrection
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Simulation resultsSimulation results
Source P1 [45°N 60°E]1st receiver A: Vieques 2nd receiver B: Palmer
Estimated position
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Simulations resultsSimulations results
Real Source [45°N 60°E]1st receiver A: Vieques 2nd receiver B: PalmerAzimuth error 1°;Time difference Error 0.1ms Estimated
position
Real source
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Real dataReal data
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Real data localization Real data localization
Source localized in the triangle using the two methods
A difference of ~200Km between the two methods
Alger
Iso time difference
Extended kalman filter
Iso time difference
Alger
Researsh zone
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Conclusion and perspectiveConclusion and perspective
Automatic method for sferic detectionAutomatic method for sferic detection
Localization using extended Kalman filter Localization using extended Kalman filter
Introduction of signal dynamic in physics Introduction of signal dynamic in physics problemsproblems
Test of other optimization methodsTest of other optimization methods