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AMIGOS workshop, October 15 2005
Noise Characterization Using Transfer Functions: Examples from Spacecraft Doppler Tracking
John Armstrong for the Cassini Radio Science GW Group*
* R. Ambrosini, J.W. Armstrong, B. Bertotti, L. Iess, P. Tortora, H.D. Wahlquist
AMIGOS workshop, October 15 2005
Noise Characterization Using Transfer Functions
• The Doppler technique & its signal and noise transfer functions
• Examples of noise identification using transfer functions– Frequency & timing system– Antenna mechanical noises– Phase noise due to propagation through irregular media
• Model example for LISA: identifying proof mass noises
AMIGOS workshop, October 15 2005
QuickTime™ and aTIFF (LZW) decompressor
are needed to see this picture.
AMIGOS workshop, October 15 2005
Isolating Proof-Mass Noises with Transfer Functions
• LISA unequal-arm geometry• Nomenclature for proof
mass disturbances vi and vi*
• Idea: isolate which proof mass glitched (Braginsky, ≈2001) -- or which proof mass is noisier -- through their transfer functions
AMIGOS workshop, October 15 2005
Isolating Proof-Mass Noises with Transfer Functions
• Temporal transfer fucntion of 6 PM’s to the three unequal-arm Michelson combinations (X, Y, Z) + symmetrical Sagnac ()
• First generation TDI
AMIGOS workshop, October 15 2005
GW Transfer Function to TDI “X”
• Source/detector geometry dependent
• “8-pulse” response in general for first-gen TDI [equal arm lengths assumed in this example so it degenerates to 7-pulse response; ApJ 527, 814 (1999)]
• Will not be confused with PM glitches
AMIGOS workshop, October 15 2005
Isolating Proof-Mass Noises with Transfer Functions (Statistically)
• Noise-only spectra of first-generation TDI combinations X and Z (expressed here as spectra of fractional Doppler fluctuations, vs. phase)
• Proof mass 1 assumed 10X noisier than nominal
• PM1 does not enter in Z, so it is OK -- spectrum of X affected, however
CQG, 20, S283 (2003)
AMIGOS workshop, October 15 2005
Concluding Comments
• In spacecraft Doppler tracking, at least, the data themselves are much more sensitive than any of the engineering housekeeping channels which monitor experiment health -- so you have to use the data themselves, in general, to understand the noises
• I would expect this to be true for LISA, too
• Transfer functions of the signal and noises to the TDI combinations offer a way to use the “science” data to understand the noises and instrument performance