Related Experiment Video
Updated: Apr 3, 2026

15:25
Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
Published on: February 4, 2018
6.7K
Broadband lightwave synthesized frequency sweeper using self-induced auto-tracking filter
Optics Express
|September 15, 2015
Summary
Researchers developed a novel self-induced auto-tracking filter (SIATF) to significantly broaden the sweeping span of lightwave synthesized frequency sweepers (LSFS). This method enhances optical signal sweeping capabilities while suppressing amplified spontaneous emission noise.
Area of Science:
- Optoelectronics
- Fiber Optics
- Laser Technology
Background:
- Lightwave synthesized frequency sweepers (LSFS) are crucial for various optical applications.
- The sweeping span of LSFS is often limited by the homogeneous broadening of erbium-doped fiber (EDF).
- Existing methods for broadening the sweeping span can be complex or inefficient.
Purpose of the Study:
- To introduce a new scheme for broadening the sweeping span of LSFS.
- To utilize the spatial-hole-burning effect in unpumped EDF for creating a self-induced auto-tracking filter (SIATF).
- To demonstrate experimental enhancement of LSFS sweeping span and suppression of amplified spontaneous emission (ASE) noise.
Main Methods:
- Implementing a self-induced auto-tracking filter (SIATF) based on the spatial-hole-burning effect in unpumped EDF.
- The SIATF functions as a dynamically adjusting Bragg grating, automatically tracking incident optical signal frequencies.
- Experimental validation of the proposed scheme to measure sweeping span and power change.
Main Results:
- Achieved a broadened sweeping span of 12.48nm for the LSFS.
- Maintained a power change within 3.5dB across the broadened sweeping span.
- Demonstrated effective suppression of amplified spontaneous emission (ASE) noise.
- The 12.48nm sweeping span corresponds to a frequency span of 1.56THz.
Conclusions:
- The proposed SIATF scheme effectively broadens the sweeping span of LSFS beyond the limitations of EDF homogeneous broadening.
- This method offers a practical approach to enhance frequency sweeping capabilities in optical systems.
- The technique simultaneously improves signal quality by reducing ASE noise.
Related Concept Videos
Bandpass Sampling
627
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....
627
Linear Approximation in Frequency Domain
434
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
434
Aliasing
811
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...
811
Reconstruction of Signal using Interpolation
857
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...
857
Load-frequency control
794
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
794
Time and frequency -Domain Interpretation of Phase-lag Control
447
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
447

