High-power fiber laser has been emerged great potential in a wide range of applications and becomes a robust candidate for high energy solid state laser system. To further increase the output brightness of single-channel fiber laser, high-brightness pump sources and high-power-handling passive components should be fabricated and utilized in the fiber laser systems, in addition to the advanced techniques for multiple nonlinear effects managements. The state-of-the-art high power fiber lasers are reviewed, in terms of narrow-linewidth fiber lasers, broadband fiber lasers and fiber lasers at 2 µm. Coherent beam combining is a promising technique to obtain higher output power while maintaining excellent beam quality simultaneously, which breaks through the bottlenecks of single-channel fiber laser. Based on a series of key techniques for coherent beam combining, high-power coherent beam combining of fiber lasers could be enabled with high combining efficiency. In this paper, we review the progress of high-power fiber lasers and their coherent beam combining in the recent decade, particularly the relevant work in our group. The future prospects of fiber lasers and coherent beam combining technique are also discussed.
Black
phosphorus (BP) ranks among the most promising saturable
absorber materials for ultrafast pulse generations at 2 μm.
However, the easy-to-degrade characteristic of BP seriously limits
the long-term operation of ultrafast fiber lasers and hence becomes
a bottleneck for its relevant practical applications. In this paper,
a modified electrochemical delamination exfoliation process was explored
to produce high-performance, large-size, and oxidation-resistant BP
nanosheets, where BP nanosheets in high yield with evenly coated tetra-n-butyl-ammonium organics by precisely controlling the intercalation
chemistry can be obtained. A mode-locked Tm/Ho co-doped fiber laser
with high temporal stability and long-term operation capability was
demonstrated based on the innovatively fabricated BP saturable absorber.
The self-starting mode-locking operation featuring a high signal-to-noise
ratio of 58 dB and long-term stability has been verified for at least
3 weeks, which indicates the successful passivation of the employed
synthesis method. These results fully indicated that passivated BP
is an efficient candidate in a 2 μm range ultrafast photonic
field, which will promote the ultrafast optical application of BP
and also other infrared photonic and photoelectronic devices.
We propose and demonstrate a tunable multiwavelength mode-locked Tm/Ho-doped fiber laser based on a nonlinear amplified loop mirror (NALM). Without using polarization-maintaining fiber, only passive fibers with low birefringence were inserted into the NALM to help overcome mode competition and realize mode-locking. The spacing between adjacent channels was measured to be ∼6 nm. By adjusting the polarization controllers (PCs) to an appropriate position, self-started mode-locking was achieved, which further overcame the mode competition in the fiber laser. A multiwavelength mode-locked fiber laser with at least three available channels were tunable in the widest range of 30 nm (from 1935 to 1965 nm) with a 3 dB channel bandwidth of ∼1.6 nm. This multiwavelength mode-locked fiber laser is quite stable with the maximum peak fluctuation within 0.47 dB in long-term observations.
Statistical characteristics of signal reception conditions vary greatly in different types of environments. Hence, Global National Satellite System (GNSS) receivers must recognize surroundings for choosing the most suitable positioning methods in real time. Targeting vehicular positioning applications in a city, a novel environment recognition algorithm based only on the GNSS signal characteristics is proposed to distinguish between six distinct settings. To characterize different environmental interferences, a signal feature vector is built to represent the signal attenuation, blockage, and multipath. By training the classification model with labeled feature vectors, the support vector machine (SVM) algorithm is used to predict the scene type. A temporal filtering method is proposed to improve the accuracy. With advanced training of the model, this recognition method can work for the receiver in real time. To prove the extensive applicability of the proposed algorithm, the prediction data set and the training data set are collected in different cities. The testing results show overall recognition accuracy of 89.3% across different environments.
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