Probabilistic Residual Statics
, by Daniel Rothman
Conventional least squares residual statics solutions are known to fall
when noise contamination causes gross errots ("cyclic skips") in observed
time deviations. The statics problem presented here as a combination of
information in the form of probability density functions (Tarantola and Valette,
1982), allowing more flexibility in the determination of time deviations and less
tendency towards gross errors. Solution of a very large optimization problem with
many local maxima is necessary. The applicability of a recently propsed technique
of Monte Carlo optimization (Kirkpatrick et al, 1983) is examined.
STANFORD