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Related Concept Videos

Bandpass Sampling01:17

Bandpass Sampling

183
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
183
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

251
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.
In the...
251
Electronic Distance Measuring Instruments01:30

Electronic Distance Measuring Instruments

37
Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over short...
37
Aliasing01:18

Aliasing

136
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
136
Sampling Theorem01:15

Sampling Theorem

341
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
341
Upsampling01:22

Upsampling

238
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
238

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High-precision time measurement electronics using the bandpass sampling method.

Yichun Fan1,2, Lei Zhao1,2, Jiajun Qin1,2

  • 1State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China.

The Review of Scientific Instruments
|January 19, 2024
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Summary
This summary is machine-generated.

This study presents a novel bandpass sampling method for high-precision time measurements using lower sampling rates. The developed system achieves typical RMS precision better than 0.4 picoseconds, advancing timing electronics.

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Instrumentation

Background:

  • High-precision time measurements are crucial in various scientific and engineering fields.
  • Traditional methods often require very high sampling rates (giga-samples per second), increasing hardware complexity and cost.
  • There is a growing research interest in achieving high timing precision at lower sampling rates.

Purpose of the Study:

  • To develop a time measurement system capable of high precision at a lower sampling rate (around 100 MSps).
  • To investigate the application of bandpass sampling for enhanced timing accuracy.
  • To design and implement a real-time time extraction algorithm suitable for low-sampling-rate systems.

Main Methods:

  • An analog front-end circuit was designed for bandpass filtering and amplification of input pulse signals.
  • A pipelined real-time time extraction algorithm was developed, incorporating interpolation and cross-correlation techniques.
  • A 1024-point fast Fourier transform (FFT) was utilized for efficient cross-correlation computation.
  • Four time measurement channels were implemented on a mid-range field-programmable gate array (FPGA).

Main Results:

  • The system successfully achieved high-precision time measurements at a sampling rate of approximately 100 MSps.
  • A measurement rate of 116 kHz was attained with the FPGA implementation.
  • The typical Root Mean Square (RMS) precision of the timing system was demonstrated to be better than 0.4 picoseconds.

Conclusions:

  • The bandpass sampling method is effective for achieving high-precision time measurements at reduced sampling rates.
  • The developed real-time algorithm and FPGA implementation provide a practical solution for advanced timing applications.
  • The achieved sub-picosecond precision opens possibilities for more cost-effective and accessible high-resolution timing systems.