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Sampling Continuous Time Signal

Sampling Continuous Time Signal

In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
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Downsampling

Downsampling

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Continuous -time Fourier Transform

The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...

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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...

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Deconvolution

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Detrending Technique for Denoising in CW Radar.

In-Seong Lee¹, Jae-Hyun Park¹, Jong-Ryul Yang¹

¹Department of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Gyeongbuk, Korea.

Sensors (Basel, Switzerland)

|October 13, 2021

Summary

A novel detrending technique effectively removes direct current (DC) drift in continuous-wave (CW) radar systems. This method enhances accuracy for displacement measurements and improves signal-to-noise ratio (SNR) in vital sign detection.

Keywords:

DC drift DC offset I/Q calibration circle fitting method continuous-wave radar denoising detrending displacement measurement vital signal detection

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Area of Science:

Radar signal processing
Biomedical engineering
Metrology

Background:

Direct current (DC) offset and drift degrade continuous-wave (CW) radar performance.
DC drift, caused by vibrations or component heating, impacts I/Q imbalance calibration and DC offset removal accuracy.
Existing methods struggle to effectively mitigate slow noise near DC.

Purpose of the Study:

To propose and validate a novel detrending technique for removing DC drift in CW radar baseband signals.
To improve the accuracy of displacement measurements and the signal-to-noise ratio (SNR) for vital sign detection.
To enhance the performance of the circle fitting method used in radar calibration.

Main Methods:

A polynomial fitting-based detrending technique applied to time-domain baseband signals.
Utilizing a 5.8 GHz CW radar system for experimental validation.
Implementing fifth-order polynomial fitting for DC drift removal.

Main Results:

The proposed technique effectively removes DC drift from CW radar signals.
Displacement measurement error decreased from 1.34 mm to 0.62 mm on average at 1 m distance.
Signal-to-noise ratio (SNR) improved by 7.2 dB for respiration and 6.6 dB for heartbeat detection at 0.8 m distance.

Conclusions:

The polynomial fitting detrending technique offers a robust solution for DC drift in CW radar.
Significant improvements in measurement accuracy and vital sign detection SNR were demonstrated.
This technique enhances the reliability and applicability of CW radar in various sensing applications.