We demonstrate 32-channel dispersive optical phased arrays on a Si3N4-on-SOI integration platform. The phase difference is introduced by the arrayed waveguide. Beam steering in phased-array direction with an aliasing-free range of 22.4° and free spectrum ranges of ∼ 60 nm and ∼ 6 nm is achieved. Meanwhile, the main lobe is deflected simultaneously by 19.67° in the other direction by tuning the wavelength from 1500 nm to 1630 nm. Measurement results show that the dispersive optical phased array provides a compact, low-power and massively parallel solution for LiDAR applications.
We demonstrate a 32-element silicon OPA chip with on-chip phase calibration. The on-chip phase calibration structure consists of interferometric structures and germanium silicon photodetectors (GeSi PDs). This structure can control any angle deflection within the scanning range without detecting the far-field patterns. In the horizontal direction, the on-chip phase calibration structure is used to achieve beam steering within the 36° scanning range, and the side-lobe suppression ratio can be close to 7dB.
We demonstrate a hybrid solid-state beam scanner based on 32-channel silicon nitride optical switch with the assistance of transmission blazed grating. The optical switch exhibits rather low power consumption of 7.2 mW/π. Besides, end-fire antennas offer high optical efficiency with less reflection. Non-mechanical two-dimensional beam steering with range of 14.32° × 9.94° and beam divergence of <0.1° is achieved by wavelength tuning and onchip optical path switching. The proposed system eliminates complex control and time-consuming array phase calibration, providing a flexible, scalable and effective solution for all solid-state coaxial light detection and ranging (LiDAR) technology.
We demonstrate a 63-channel grating-lobe-free optical phased array, in which end-fire antennas were fabricated with a pitch of 775 nm to eliminate grating lobe. Phase mismatch was configured to suppress the optical crosstalk in the dense waveguides. Two-dimensional beam steering within 16°× 2.7° were presented by thermal phase shifting and wavelength tuning.
KEYWORDS: Sensors, Signal to noise ratio, Wavelets, Temperature metrology, Convolutional neural networks, Sensing systems, Reflectometry, Optical fibers, Modulation, Signal processing
We propose an instantaneous temperature measurement method based on wavelet convolutional neural network (wavelet-CNN) to extract Brillouin frequency shift (BFS) in Brillouin optical time domain reflectometer (BOTDR) sensor and map the BFS to the temperature. Compared to Lorentzian curve fitting (LCF), both the simulation and experimental results show the wavelet-CNN has better accuracy and shorter processing time.
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