Related Experiment Video
Updated: Jun 11, 2025
13:31
High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis
Published on: December 22, 2015
15.0K
Re-configurable digital bandwidth interleaved sampling system based on fast spectrum sensing
The Review of Scientific Instruments
|October 2, 2024
Summary
This study introduces a novel re-configurable bandwidth interleaved acquisition architecture for enhanced sampling accuracy and reduced data redundancy in high-bandwidth systems. The method significantly improves signal-to-noise ratio and spurious-free dynamic range.
Area of Science:
- Electrical Engineering
- Signal Processing
- Instrumentation
Background:
- Increasing signal bandwidth in parallel acquisition systems challenges sampling precision.
- Signals often exhibit sparsity in the frequency domain, a property exploitable for efficient acquisition.
Purpose of the Study:
- To propose a re-configurable bandwidth interleaved acquisition architecture for improved test flexibility and accuracy.
- To address the challenges of sampling precision in high-bandwidth systems.
Main Methods:
- A two-stage sampling process: sensing and re-configurable acquisition.
- Utilizing sparse Fourier transform for initial spectrum sensing.
- Employing subband selection and adaptive local oscillator adjustment based on spectrum sensing results.
Main Results:
- Demonstrated effectiveness on a 10 GHz acquisition system, significantly reducing data redundancy.
- Achieved improved acquisition accuracy compared to traditional bandwidth interleaved systems.
- Reported over 7.4 dB signal-to-noise ratio improvement and 4.7 dB spurious-free dynamic range improvement.
Conclusions:
- The proposed re-configurable sampling method significantly enhances the quality of sampling results.
- This architecture offers a viable solution for accurate and flexible high-bandwidth signal acquisition.
Related Concept Videos
01:17Bandpass Sampling
165
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....
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
165
01:22Upsampling
209
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...
209
01:18Aliasing
122
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...
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
122
01:10Reconstruction of Signal using Interpolation
179
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...
179
01:15Sampling Theorem
310
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.
310
01:11Sampling Continuous Time Signal
215
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...
In the...
215