Characterizing Dynamic Effects of Oscillator Power Cycling
David A. Howe, Danielle G. Lirette, Neil Ashby, Archita Hati, Craig W. Nelson
We create a measurement technique and metrics consistent with easy interpretation to be used in development of new oscillators specifically for applications in which the oscillators power is turned on and off. This is useful in predicting the performance in, for example, the frequency-difference-of-arrival (FDOA) geolocation technique which is used to monitor and track an emitters location by observing its Doppler frequency shifts at a set of receivers. To conserve energy, FDOA applications compute Doppler tracks from an emitter that is powered on or measured for short times (τon) after a long off period, called the stride interval (τs). For lowest size, weight, and power (SWaP) and lowest phase noise and best frequency stability, evaluations are focused on OCXOs and TCXOs. For illustration, we use τon = 3s and τs = 60s. This illustration shows the need to consider the dynamic behavior during the short 3s average frequency measurements as well as the 60s sampling time interval between measurements. Dynamic ADEV does not accurately capture different noise types for such a short 3s sample, so we propose using Dynamic ThêoH which characterizes the oscillator at power-on more accurately. Since RMS frequency differences vs. sampling time-intervals in multiples of 60s cannot be used in place of the ADEV, we regard frequency differences as an uncertainty on an oscillator's predicted frequency, not on a mean frequency. This mimics ADEV and one can distinguish the dominant component of frequency prediction due to random-walk FM (RWFM) or an even more divergent noise type. The paper: (1) describes a measurement setup to obtain low-noise, fast fractional-frequency, time-series measurements, (2) motivates and illustrates Dynamic ThêoH, the hybrid of ADEV and THEO, for τon = 3s, (3) constructs a statistic called Y(τon,τs) which estimates a τs = 60s frequency prediction error, and (4) transforms 3s time-series measureme
, Lirette, D.
, Ashby, N.
, Hati, A.
and Nelson, C.
Characterizing Dynamic Effects of Oscillator Power Cycling, Proceedings of 43rd Annual PTTI Meeting, Long Beach, CA
(Accessed February 20, 2024)