The effect of clock jitter on the performance of continuous-time delta-sigma ADC for GNSS signals

Next generation Global Navigation Satellite System (GNSS) receivers will operate in multiple navigation bands. An efficient way to achieve this with lower power and cost is to employ BandPass Sampling (BPS); nevertheless, the sampling operation injects large amounts of jitter noise, which degrades the performance of the receiver. Continuous–Time (CT) Delta–Sigma (ΔΣ) modulators are capable of suppressing this noise but the impact of clock jitter at the output of the Digital– to–Analog Converter (DAC) in the feedback path of the modulator should be taken into account. This paper presents an analytical approach for describing clock jitter in GNSS receivers when a CT–ΔΣ modulator is utilized for Analog–to–Digital Conversion (ADC). The validity of the presented approach is verified through time–domain simulations using a behavioural model of the fourth–order CT–ΔΣ modulator with 1–bit NRZ DAC feedback pulse.

Flipped clock

Flipped Clock is a working modified digital clock. Although it tells the current time, every digit has been rotated by 180 degrees. In doing so, the act of telling the time is once again rendered unfamiliar to us, reminding us of its artifice and almost invisible authority.

The Finometer can function as a standalone instrument in blood pressure variability studies and does not require support equipment to determine breathing frequency

Objective: The Finometer (FMS, Finapres Measurement Systems, Amsterdam) records the beat-to-beat finger pulse contour and has been recommended for research studies assessing shortterm changes of blood pressure and its variability. Variability measured in the frequency domain using spectral analysis requires that the impact of breathing be restricted to high frequency spectra (> 0.15 Hz) so data from participants needs to be excluded when the breathing impact occurs in the low frequency spectra (0.04 - 0.15 Hz). This study tested whether breathing frequency can be estimated from standard Finometer recordings using either stroke volume oscillation frequency or spectral stroke volume variability maximum scores. Methods: 22 healthy volunteers were tested for 270s in the supine and upright positions. Finometer recorded the finger pulse contour and a respiratory transducer recorded breathing. Stoke volume oscillation frequency was calculated manually while the stroke volume spectral maximums were obtained using the software Cardiovascular Parameter Analysis (Nevrokard Kiauta, Izola, Slovenia). These estimates were compared to the breathing frequency using the Bland-Altman procedures. Results: Stroke volume oscillation frequency estimated breathing frequency to <±10% 95% levels of agreement in both supine (-7.7 to 7.0%) and upright (-6.7 to 5.4%) postures. Stroke volume variability maximum scores did not accurately estimate breathing frequency. Conclusions: Breathing frequency can be accurately derived from standard Finometer recordings using stroke volume oscillations for healthy individuals in both supine and upright postures. The Finometer can function as a standalone instrument in blood pressure variability studies and does not require support equipment to determine breathing frequency.