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A real-time ranging lidar with 0.1 Mega Hertz update rate and few-micrometer resolution incorporating dispersive Fourier transformation and instantaneous microwave frequency measurement is proposed and demonstrated. As time-stretched femtosecond laser pulse passing through an all-fiber Mach-Zehnder Interferometer, where the detection light beam is inserted into the optical path of one arm, the displacement is encoded to the frequency variation of the temporal interferogram. To deal with the challenges in storage and real-time processing of the microwave pulse generated on a photodetector, we turn to all-optical signal processing. A carrier wave is modulated by the time-domain interferogram using an intensity modulator. After that, the frequency variation of the microwave pulse is uploaded to the first order sidebands. Finally, the frequency shift of the sidebands is turned into transmission change through a symmetric-locked frequency discriminator. In experiment, A real-time ranging system with adjustable dynamic range and detection sensitivity is realized by incorporating a programmable optical filter. Standard deviation of 7.64 {mu}m, overall mean error of 19.10 {mu}m over 15 mm detection range and standard deviation of 37.73 {mu}m, overall mean error of 36.63 {mu}m over 45 mm detection range are obtained respectively.
Microwave photonics (MWP) studies the interaction between microwave and optical waves for the generation, transmission and processing of microwave signals (i.e., three key domains), taking advantages of broad bandwidth and low loss offered by modern
Photonic signal processing is essential in the optical communication and optical computing. Numerous photonic signal processors have been proposed, but most of them exhibit limited reconfigurability and automaticity. A feature of fully automatic impl
This paper presents a field-programmable gate array (FPGA) design of a segmentation algorithm based on convolutional neural network (CNN) that can process light detection and ranging (LiDAR) data in real-time. For autonomous vehicles, drivable region
We design and experimentally demonstrate a radio frequency interference management system with free-space optical communication and photonic signal processing. The system provides real-time interference cancellation in 6 GHz wide bandwidth.
With recent rapid advances in photonic integrated circuits, it has been demonstrated that programmable photonic chips can be used to implement artificial neural networks. Convolutional neural networks (CNN) are a class of deep learning methods that h