The paper is concerned with one aspect of our recent development carried out at Portsmouth Polytechnic (UK) regarding a novel approach for the simultaneous measurement of amplitude and phase nose in oscillators. A description of the measurement system and the associated processing techniques is presented.The measurement system includes a conventional complex (I & Q) demodulator, a high speed sampler and a digital computer. The techniques have been named time-domain phase unwrapping and real amplitude de-enveloping. They permit the reconstruction of the demodulated I and Q signals as a vector rotating at a convenient beat frequency randomised, in phase and magnitude, by noise. The problems encountered in conventional AM and PM detection can be overcome using the afore-mentioned approaches. As a result, direct and true amplitude and phase noise can be measured and characterised.
This paper is concerned with two related aspects of the recent research work carried out at Portsmouth Polytechnic in the UK regarding numerical and digital techniques for the measurement and synthesis of phase noise in oscillators.The first aspect concerns the introduction of a statistical quantity termed extended Hadamard variance to be applied in frequency stability analysis by making use of digital frequency counter measurements. The properties, the potential interest and the usefulness of this parameter are briefly demonstrated and applied to the study of a signal from a synthesizer f.m. modulated by white noise followed by the frequency counter and signal processing. It is shown that not only the Hadamard variance but the Allan variance and the extended twosample variance are such sets of this variance.The second aspect quite important and closely related to the first one refers to modem requirements for numerical simulation of random noise. emulating phase or frequency fluctuations, and with the following features: (a) variable slope a of the power spectrum S, cf ) -f a with a a positive or negative real number (not necessarily integer), and (b), in parallel with (a), the ability to generate noise with a predetermined amplitude distribution (uniform, Gaussian, etc). The paper describes the autoregressive integrated moving average technique used to generate the various types of random noise including the radio propagation f.m. noise (S,(f) and the Monte Carlo approach to transform from one distribution to another.
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