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SLR Data Automatic SLR Data Automatic PreprocessingPreprocessing
BeiJing SLR StationChinese Academy of Surveying and Mapping
DING Jian QU Feng WEI Zhibin
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OutlineOutline
IntroductionSatellite Prediction Observation Data PreprocessingConclusions
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C: Velocity of lightT: Round-trip timeR: Range
Principle of SLRPrinciple of SLR
Cooperate Object
ERS-2TOPEX
LAGEOS1.Introduction1.Introduction
R=C×t/2
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Obtained satellite passes: to 30, Jun, 2008
Beijing:1850; San_Juan:5255
(From: http://ilrs.gsfc.nasa.gov)(From: http://ilrs.gsfc.nasa.gov)
The work of Beijing SLR station(1)The work of Beijing SLR station(1)
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Integrate SLR systemHardware: change fuel laser to diode pumped laser
Software:1) Satellite prediction based on CPF
2) Raw SLR data preprocessing (Preprocessing)
The work of Beijing SLR station(2)The work of Beijing SLR station(2)
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Introduction of SLR data preprocessingIntroduction of SLR data preprocessing
1) Satellite prediction- producing schedule - generating tracking file
2) tracking data acquire 3) preprocessing (Manual!/Automatic?)
- noise eliminated- generating NP
Reliability and efficiency are two necessary factors taken into account in automatic preprocessing method.
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2. Satellite prediction2. Satellite prediction
Introduction to CPF (1) CPF(Consolidated Prediction Format)
(2) Provide a standard ephemeris format
(3) Service for SLR and other astronomy calculation
(4) Make complex work become easy
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Features of CPFFeatures of CPF
A. Simply Calculation (1) Time system: UTC No Time System Transition (2) Coordinate system: Geocentric coordinate (3) Calculate: Interpolation No using EGM and integral B. High Precision (1) Azimuth and Elevation direction (2) Range direction C. Multiple Information (1) Multiple target: earth satellite, Lunar, Apollo (other stars??) (2) Multiple resources: hts, jax, sgf, gfz, cod (2) Multiple records: position, correction etc.
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Flow chat
FTP(CDDISA/EDC) CPF Downloading
Programming_01
Schedule Programming_02Satellite Prediction(Tracking File)
A B C
D
EFG
How to use CPF(1)How to use CPF(1)
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Program_01:
Function: to form satellite schedule
Program_02: Function: to generate satellite tracking file
How to use CPF(2)How to use CPF(2)
CPF(X/Y/Z) Interpolate Satellite(X/Y/Z:interval 1min)
Site/Satellite Information
Convert
Moon Position
Sun Position
Min_angle
Shadow Schedule
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Compare the CPF of GPS36 to IGS
Standard Deviation
The two days(Epoch:1~192):
dX=± 2.36cm; dY= ± 6.30cm; dZ= ± 5.58cm
All five days(Epoch:1~480):
dX=± 14.21cm; dY= ± 12.37cm; dZ= ± 8.09cm
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3. Observation3. Observation Data PreprocessingData Preprocessing
Objects of preprocessing1) eliminate noise from raw data
2) form Normal Point dataPrincipal of preprocessing In theory, satellite orbit is sequent, so the
rang of SLR observation and its change should be continuous.
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1) Manual
- please rub out the point that you think it is noise. Intuitive/Simple/Reliabile?/Inefficient/Tired
Now: Low repeat frequency
2) Automatic
- based on program control and let compute do it.
Arithmetic programmer/Reliable?/Efficient/Comfortable
Future: High repeat frequency
Methods of preprocessing
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• Requirements of automatic preprocessingRequirements of automatic preprocessing
1) Judge the raw data good or not: TB, RB and RMS
2) Reliable: Alarm Function, if data quality is not very good, the program can tell user.
3) Efficiency: as more data processed as possible
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Analysis the predictionAnalysis the prediction
SLR tracking work is based on satellite prediction (CPF), so the quality of CPF is one determinative on Data preprocessing.
Distance difference scope:
Difference
Raw data from Sat Sat prediction(CPF)
Scope of validate data
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The Scope of differenceThe Scope of difference
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Method of Automatic Data Method of Automatic Data preprocessing(1)preprocessing(1)
Step1: Based on CPF scope
[-36,12]
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Method of Automatic Data Method of Automatic Data preprocessing(2)preprocessing(2)
Step 2: Comparting on O-C
[Rmin,Rmax]
1 1
2 2
( ) ( )
100( ) /100, 1,2,..., , max (0 )
( ) /100, 100,99,..., , min (0 ) (100 )
Max o c Min o cR
Num i All i k R New Max c k R
Num i All i k R New Min c k R
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Method of Automatic Data Method of Automatic Data preprocessing(3)preprocessing(3)
Step 3: Comparting on Time
[Tmin,Tmax]
1 1
2 2
100( ) /100, 1,2,..., ,
( ) /100, 100,99,..., , (100 )
TStart TEndT
Num i All i k TMax TEnd k T
Num i All i k TMin TStart k T
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Method of Automatic Data Method of Automatic Data preprocessing(4)preprocessing(4)
Step 4: - Iterating Step2 and 3
- polynomial computing
- Form NP
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ConclusionsConclusions
About Prediction (1) ephemeris’ precision more high
(2) convenient using than beforeAutomatic preprocessing
(1) single to noise rate
(2) not very mature and still lots work to do
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Thanks!
谢谢!