An Artificial Neural Network Model for Timescale Atomic Clock Ensemble Algorithm
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ORIGINAL PAPER
An Artificial Neural Network Model for Timescale Atomic Clock Ensemble Algorithm R. Sruthikeerthi Nandita* , S. Maharana, B. Rajathilagam, T. Subramanya Ganesh and S. Krishnamoorthy Navigation Systems Area, ISRO Telemetry Tracking and Command Network (ISTRAC), ISRO, Bangalore, India Received: 21 September 2020 / Accepted: 11 November 2020 Ó Metrology Society of India 2020
Abstract: Atomic clocks work on a standard frequency generated by the electron transitions in the atoms of the core material. A timescale is a reference frequency and phase measure generated by a set of atomic clocks. An ensemble algorithm combines the participating atomic clocks to form a ‘‘perfect’’ clock. The perfect clock is very stable and precise in terms of frequency and phase. There are many methods that exist to develop an ensemble for a timescale such as Kalman filter-based algorithms, inverse Allan variance-based algorithms, etc. A neural network-based realization of the ensemble algorithm for a timescale is discussed in this paper. The artificial neural network (ANN) model dynamically adapts the weights of the clocks to accommodate the behavioural changes in the clocks. This paper uses different types of M-sample deviations like overlapping Allan deviation and overlapping Hadamard deviation as the inputs to the model. Keywords: Allan deviation; Artificial neural networks; Atomic Clocks; Frequency stability analysis; Hadamard deviation; Indian regional navigation satellite system (IRNSS); IRNSS Network Timing Centre (IRNWT); Navigation with Indian Constellation (NavIC) 1. Introduction Precise time keeping is essential in various applications such as metrological timekeeping, satellite navigation, very-long-baseline interferometry and other strategic sectors. Time is measured using stable pulses generated by an oscillating device with a certain frequency. There are many types of oscillating devices used today. Atomic clocks, such as Caesium clocks and active hydrogen masers (AHM), use the energy transitions of the electrons in the atom to measure this frequency. This frequency is highly stable and reliable as it is unique to each element and common for every atom of the element [1]. However, the various physical characteristics of the apparatus have a huge impact on the frequency generated. Hence, the stability of the frequency is highly dependent on many external factors [2]. A timescale is the estimate of phase and frequency of the ‘‘perfect’’ clock derived from phase
*Corresponding author, E-mail: [email protected]
and frequency of the clocks that participate in the ensemble. An ensemble algorithm is said to be robust and reliable as it is highly fault tolerant, i.e. when a clock in the ensemble fails, the stability is maintained by the other clocks in the ensemble. The timescale generated through an ensemble of atomic clocks is expected to perform better than any of the individual participating clocks [3]. In this paper, we formulated ensembles of 3, 4 and 5 clocks, respectively. Navigation with Indian Co
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