基于非线性最小二乘法的条纹相机标定数据处理方法
Calibration data processing of streak camera with nonlinear-least-squares method
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摘要: 使用基于非线性最小二乘法的方法处理扫速标定数据，获得了条纹相机的全屏扫速数据，消除了扫速非线性和空间畸变对测量结果的影响。该方法的不确定度约为0.04%，远小于条纹相机的系统误差。利用该方法得到了各个像素对应的扫速，其不确定度约为1.5%，显著减小了条纹相机测量结果的误差。Abstract: The result of full-screen sweeping rates of streak camera(SC) is obtained using a nonlinear-least-squares method. The uncertainty of this method is about 0.04%, far below SC’s systematic uncertainty. Full-screen result eliminates nonlinearity and space-distortion of sweeping rates, minimizes the error of SC’s measurement to about 1.5%. The robustness and time-efficiency of this method make full-screen calibration of time-domain and space-domain feasible．
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Key words:
- nonlinear-least-squares /
- streak camera /
- calibration /
- full-screen sweeping rates /
- multi-gaussian fit /
- uncertainty
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