Abstract
This paper introduces the Prism, a new type of signal processing block, as a contribution to the challenges of 21st Century metrology. The Prism is a fully recursive, dual output, FIR filter: the computational burden is low and independent of data window length. Prism design is trivial, so that networks of Prisms can be created, whether at design time or autonomously in real time, to carry out a range of metrological tasks. Prism-based trackers can generate sample-by-sample estimates of frequency, phase, and/or amplitude of a sinusoid. A simulation example of sensor validation demonstrates how Prism signal processing can be used to autonomously detect, track, and compensate for an undesired frequency component in a frequency-based sensor.
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