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Experimental optimization of an erbium-doped super-fluorescent fiber source for fiber optic gyroscopes
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作者 常金龙 谭满清 《Journal of Semiconductors》 EI CAS CSCD 北大核心 2011年第10期62-66,共5页
Double-pass forward and double-pass backward erbium-doped super-fluorescent fiber sources(EDSFSs) were combined in one configuration.A 980 nm laser diode pumped the same erbium-doped fiber from both directions using... Double-pass forward and double-pass backward erbium-doped super-fluorescent fiber sources(EDSFSs) were combined in one configuration.A 980 nm laser diode pumped the same erbium-doped fiber from both directions using a coupler as a power splitter.The double-pass configuration was achieved by coating the fiber end face.Firstly,an optimal fiber length was found to obtain a high stability of output light wavelength with pump power, and then 1530/1550 nm wavelength division multiplexing was used for spectrum planarization,which expanded the bandwidth to more than 22 nm.The final step was a test of temperature stability.The results show that the rate of the central wavelength change kept to below 3.5 ppm/℃in the range of -40 to 60℃and 1-2 ppm/℃in the range of 20-30℃.Considering all the three factors of the fiber optic gyro applications,we selected 80 mA as the pump current,in which case the central wavelength temperature instability was calculated as 2.70 ppm/℃, 3 dB bandwidth 22.85 nm,spectral flatness 0.2 dB,output power 5.17 mW and power efficiency up to 9.92%.This experimental result has a significant reference value to the selection of devices and proper design of ED-SFSs for the application of high-precision fiber optic gyroscopes. 展开更多
关键词 erbium-doped super-fluorescent fiber source central wavelength stability pump from both directions spectrum planarization coating on the fiber end high-precision fiber optic gyroscope
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运动物体速度场估计的新方法
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作者 陈丽亚 戚飞虎 《上海交通大学学报》 EI CAS CSCD 北大核心 1994年第1期55-61,共7页
本文提出了一种具有一定应用价值的运动物体速度场的计算方法.本算法避开了现有的一些算法所遇到的图像分割问题,用一种类Hopfield神经网模型实现局部图像的Gabor分解,得到分解系数,对用Gabor基函数和式形式表示... 本文提出了一种具有一定应用价值的运动物体速度场的计算方法.本算法避开了现有的一些算法所遇到的图像分割问题,用一种类Hopfield神经网模型实现局部图像的Gabor分解,得到分解系数,对用Gabor基函数和式形式表示的图像进行傅立叶变换,求出其频谱不为零的点,并由这些点约束的平面方程求出速度.神经元网络的应用,缩短了优化计算所需时间而不降低计算精度.本算法在AST-386微机上进行了实现。 展开更多
关键词 速度场 Gabor分解 运动物体 估计
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