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Optical sampling system using periodically-poled lithium niobate waveguide and nonlinear polarization rotation mode-locked fiber laser 被引量:2
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作者 Jian LI Aiying YANG +2 位作者 Lin ZUO Junsen LAI Yunan SUN 《Frontiers of Optoelectronics》 2012年第2期208-213,共6页
A novel design of optical sampling system has been developed by using sum-frequency generation (SFG) in a periodically-poled lithium niobate (PPLN) waveguide and using passive mode-locked fiber laser pulses as opt... A novel design of optical sampling system has been developed by using sum-frequency generation (SFG) in a periodically-poled lithium niobate (PPLN) waveguide and using passive mode-locked fiber laser pulses as optical sampling pulses. The system achieved high temporal resolution and high sensitivity using a 30 mm length PPLN with quasi phase match period of 19.3 μm and 151 fs sampling pulses which were generated by passive modelock fiber laser based on nonlinear polarization rotation (NPR). Clear eye-diagram of 10 Gbit/s non-return-to-zeros (NRZ) pseudorandom binary sequence (PRBS) optical signal were successfully reconstructed by this system. 展开更多
关键词 periodically-poled lithium niobate (PPLN) optical sampling nonlinear polarization rotation (NPR)fiber laser sum-fi'equency generation (SFG)
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Near-field time-frequency localization method using sparse representation
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作者 WANG Bo LIU Juan-juan +1 位作者 SUN Xiao-ying ZHANG Yan-jun 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2012年第6期29-34,共6页
This paper presents a novel near-field source localization method based on the time-frequency sparse model. Firstly, the method converts the time domain data of array output into time-frequency domain by time-frequenc... This paper presents a novel near-field source localization method based on the time-frequency sparse model. Firstly, the method converts the time domain data of array output into time-frequency domain by time-frequency transform; then constructs sparse localization model by utilizing the specially selected time-frequency points, and finally the greedy algorithms are chosen to solve the sparse problem to localize the source. When the coherent sources exist, we propose an additional iterative selection procedure to improve the estimation performance. The proposed method is suitable for uncorrelated and coherent sources, moreover, the improved estimation accuracy and the robustness to low signal to noise ratio (SNR) are achieved. Simulations results verify the efficiency of the proposed algorithm 展开更多
关键词 near-field source time-fi'equency distribution sparse representation DOA estimation range estimation greedy algorithm
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