We propose and demonstrate a passive compensation based stable radio-frequency dissemination system based on a mode-locked laser (MLL). The MLL is used as a timing signal source, which can provide multiple frequency references so that avoiding the use of multiple frequency multipliers. In the experiment, an 8.032-GHz signal is obtained with phase being compensated at a 3-km away remote site. Its single-sideband phase noise is reduced by 8.7 dB@10 Hz and 19.8 dB@10 kHz respectively compared to the uncompensated signal. The phase fluctuation of the compensated signal is kept around 2.7-degree level within 600s.
A Photonics-enabled Compressed Sensing (PCS) system for sparse Radio Frequency (RF) signals acquiring is proposed and experimentally validated, utilizing an optical pulse stretching and compression structure. A pulse train is first stretched by a dispersion module to carry the signal under measurement and a bipolar Pseudo-Random Binary Sequence (PRBS), then the pulse is compressed by another complementary dispersion module to perform integration process. The measurement matrix can be directly obtained from the envelope of the stretched pulse, avoiding the necessity of accurately obtaining the link impulse response including the Low-Pass Filter (LPF) in the traditional systems. A preliminary proof-of-concept experiment has been successfully carried out. A two-tone signal with frequencies of 400MHz and 800MHz is successfully reconstructed using a sampling rate of 100MHz, which is 1/16th of the Nyquist rate of the input two-tone signal.
An optical multi-path wideband self-interference (SI) cancellation system with adaptive feedback function is proposed and demonstrated. With the help of wavelength-division multiplexing, multiple independent reference channels are constructed to mitigate the multipath effect. The particle swarm optimization (PSO) algorithm is used to adaptively adjust the operating parameters of the corresponding optical devices to optimize the cancellation performance. Experimental results show that a cancellation depth exceeding 30dB across a 200-MHz instantaneous bandwidth is achieved. A 16QAM signal with a symbol rate of 10 MBaud is successfully recovered with the assist of the proposed cancellation system.
A pre-trained Transformer network is proposed for the application in temporal photonic compressive sampling, which can address the neck-strangling issues in classical compressive sampling algorithms when using random or orthogonal measurement matrices. The Transformer network is pre-trained to accommodate a diverse array of needs, and specific application requirements can be addressed by fine-tuning the network parameters to learn prior information. In this paper, we preliminarily validated the algorithm model through simulation to address the waveform measurement performance of linear frequency modulated (LFM) signals. Using a photonic compressive sampling architecture with an average sampling rate of only 40 MSa/s, the Transformer accurately realized waveform reconstruction of LFM signals with a frequency range from 0.1 to 50 GHz and an instantaneous bandwidth as large as 10 GHz under strong interference. A frequency identification error of less than 0.3 GHz was achieved, corresponding to a compression ratio of 1500:1.
A lidar system for simultaneous detection of distance, velocity and direction of a moving target is proposed and experimentally demonstrated based on an optical multi-chirped LFM signal generator. The optical multi-chirped linearly frequency-modulated (LFM) signal generator is realized by an optical frequency shifting loop (OFSL) that is driven by an electrical LFM signal. After the OFSL, a sequence of optical LFM signals with incremental chirps are generated. The signal is then emitted into the space and captured again after being reflected by a target. A lidar system is thus realized. An experiment is carried out. A sequence of LFM signals with chirps incremented from 0.389 to 2.713 GHz/s are generated. A distance of 19.1 m and velocities of -2.203 m/s and 4.170 m/s are measured based on a lidar system built based on the LFM signal.
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