The Development of a New Kalman-Filter Time Scale at NIST
نویسندگان
چکیده
We report on a preliminary design of a new Kalman-filter Hydrogen-maser time scale at NIST. The time scale is composed of a few Hydrogen masers and a Cs clock. The Cs clock is used as a reference clock, to ease operations with existing data. All the data used in this paper are real measurement data, except mentioned specifically. Unlike most other time scales, this time scale uses three basic time-scale equations, instead of only one equation. Also, this time scale can detect a clock error (i.e., time error, frequency error, or frequency drift error) automatically. A frequency step of 6.8×10 s/s (which typically corresponds to ~ 2C temperature change of a H-maser chamber) in a clock only leads to ~ 2.5 ns change in the time scale in 100 days, thanks to the advanced error-detection technique. A frequency-drift step of 5.4×10 s/s in a clock only leads to ~ 11 ns change in the time scale in 100 days. These features make the new time scale stiff and less likely to be affected by a bad clock. Tests show that the time scale deviates from the UTC by less than ± 5 ns for ~100 days, when the time scale is initially aligned to the UTC and then is completely free running. Once the time scale is steered to an external frequency standard (such as a Cs fountain), it can maintain the time with little error even if the external frequency standard stops working for tens of days. At NIST, we have the Cs fountain running in 2015 September (23 days), 2015 December (14 days) and 2016 February (18 days). Although the Cs fountain runs for only 55 days in total, the time scale steered to the Cs fountain has a deviation of less than 4 ns (peak-to-peak) from the UTC, during MJD 57265 – 57500 (235 days). This can be helpful when we do not have a continuously-running fountain, or when the continuously-running fountain accidentally stops, or when optical clocks run occasionally.
منابع مشابه
Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter
The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...
متن کاملA New Adaptive Extended Kalman Filter for a Class of Nonlinear Systems
This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...
متن کاملDesign and Implementation of a Kalman Filter-Based Time-Varying Harmonics Analyzer
Nowadays with increasing use of numerous nonlinear loads, voltage and current harmonics in power systems are one of the most important problems power engineers encounter. Many of these nonlinear loads, because of their dynamic natures, inject time-varying harmonics into power system. Common techniques applied for harmonics measurement and assessment such as FFT have significant errors in presen...
متن کاملNew Adaptive UKF Algorithm to Improve the Accuracy of SLAM
SLAM (Simultaneous Localization and Mapping) is a fundamental problem when an autonomous mobile robot explores an unknown environment by constructing/updating the environment map and localizing itself in this built map. The all-important problem of SLAM is revisited in this paper and a solution based on Adaptive Unscented Kalman Filter (AUKF) is presented. We will explain the detailed algorithm...
متن کاملRotated Unscented Kalman Filter for Two State Nonlinear Systems
In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...
متن کامل