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Aliasing

Aliasing

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.
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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.

Upsampling

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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...

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Rapid Repetition Rate Fluctuation Measurement of Soliton Crystals in a Microresonator

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Instantaneous frequency measurement based on photonic compressive sensing with sub-Nyquist pseudo-random binary

Runcheng Li, Shuna Yang, Bo Yang

|April 1, 2024

Summary

This study introduces a new method for instantaneous frequency measurement using photonic compressive sensing (CS) and pseudo-random binary sequences (PRBSs). This approach achieves ultrahigh bandwidth and reduces data processing requirements.

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Area of Science:

Photonics
Signal Processing
Electrical Engineering

Background:

Instantaneous frequency measurement (IFM) is crucial for various applications, including electronic warfare and radar systems.
Traditional IFM techniques often face limitations in measurement bandwidth and resolution.
Photonic compressive sensing (CS) offers a promising avenue for high-speed signal analysis.

Purpose of the Study:

To develop a novel photonic compressive sensing (CS) approach for instantaneous frequency measurement (IFM).
To achieve ultrahigh measurement bandwidth with reduced data processing requirements.
To demonstrate the feasibility of the proposed IFM technique in the Ku band.

Main Methods:

Utilizing a three-channel photonic compressive sensing (CS) system.
Employing sub-Nyquist pseudo-random binary sequences (PRBSs) to induce aliasing.
Implementing a frequency identification algorithm to recover the original signal frequency from aliased components.

Main Results:

Successfully demonstrated instantaneous frequency measurement in the Ku band.
Achieved ultrahigh measurement bandwidth through the proposed CS approach.
Significantly reduced the required bit rate of PRBSs and the sampling rate of digitizers.

Conclusions:

The proposed three-channel photonic CS method enables high-performance IFM with reduced hardware complexity.
This technique offers a significant advancement in achieving ultrahigh bandwidth frequency measurement.
The proof-of-concept experiment validates the effectiveness of the approach for practical applications.