Power law noise identification using the LAG 1 autocorrelation by overlapping samples
There are various random errors in the fiber optical gyroscope (FOG) output signal. At the aim of improving its accuracy, it is need to identify the kinds of errors. The most common method for power law noise identification is simply to observe the slope of a log-log plot of the Allan or modified Allan deviation versus averaging time, either manually or by fitting a line to it. The lag 1 autocorrelation method is a new method for power law noise identification that can determine the dominant noise type for all common noise processes, from phase or frequency data, for all averaging factors, in a consistent and analytic manner. This paper describes an improvement of it by overlapping samples, which improves the confidence of the resulting stability estimate at the expense of greater computational time.
POWER LAW NOISE IDENTIFICATION USING THE LAG 1 AUTOCORRELATION
This paper describes a new method for power law noise identification, based on the lag 1 autocorrelation function, that can determine the dominant noise type for all common noise processes, from phase or frequency data, for all averaging factors, in a consistent and analytic manner.
Early Cretaceous Feathers from Victoria
Unusually well preserved fossil feathers from Lower Cretaceous (VaIanginian-Aptian) claystones at Koonwarra, Victoria, are the oldest (c. 110-125 million years) bird remains yet found in the southern hemisphere, They are among the oldest bird remains known in the world, being antedated only by the toothed Archaeopteryx from the late Jurassic of Bavaria, and being more or less the same age as Gallornis from the Lower Cretaceous of France. The Victorian fossil feathers are evidence for essentially worldwide distribution of birds soon after the beginning of the Cretaceous, if not before. The feathers could conceivably have come from toothed birds.