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.
The Identification of Satellite Clock Noise Based on LAG1 Autocorrelation of Overlapping Samples
Atomic clock is composed of various components of electronic devices, and its comprehensive effect of the internal and external environment makes it get easily affected by many kinds of noise. The random part of the clock bias is mainly influenced by the noise. The noise identification of atomic clock plays an important role in establishing an accurate random model and the weighting strategy of multi-GNSS. The most common methods for power-law noise identification are slope method, B1 partial factor method, LAG1 autocorrelation function method, and so on. However, these methods have their own defects or shortcomings. In this paper, we propose an improved method of LAG1 autocorrelation function based on overlapping samples to accurately identify the type of noise. By this method, we analyzed the main noise types affecting GPS and BDS satellite clocks. The results showed that the BDS satellite clock is mainly affected by White FM, Flicker FM and Random Walk FM. GPS BLOCK IIA Cs, BLOCK IIA Rb, BLOCK IIR Rb, BLOCK IIR M and BLOCK IIF Cs are mainly affected by the White FM and Flicker PM, and BLOCK IIF Rb is mainly influenced by the White PM, Flicker PM and White FM. The proposed new method based on overlapping sampling of LAG1 autocorrelation function can accurately identify GPS satellite clock noise, because the frequency bias and drift is more stable.
DISCRETE SIMULATION OF POWER LAW NOISE
Power law noise plays an important role in the description of high performance oscillators. Commonly, five types of noise are considered to affect clocks and clock measurements: white phase, flicker phase, white frequency, flicker frequency and random walk frequency. These noise types are distinguished by the slopes of their spectral densities, S,@ =y (on a log-log scale). The noise is inherent both to the oscillators and to the measurement systems and defines the limits of stability of the clocks. Accurate simulation of the noise can be important for testing the measurement system and the characterization software. This paper presents a new algorithm and computer code for simulating power law noises with arbitrary a (it is not restricted to the integer values mentioned above). The general theory of noise simulation is investigated to determine the criteria for evaluating and deriving simulation methods. Past techniques are evaluted and the new method is shown to provide improvements, particularly because it results in non-stationary noise sequences that are also scale- invariant and causal and have the proper autospectral densities and Allan variances.