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Application of neural network and spheric harmonics function to system error correction of electro-optical tracker system with X-Y gimbal

机译:神经网络和球形谐波功能在X-Y万向节电光跟踪系统系统纠错的应用

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摘要

Correction of the System error of electro-optical tracker system could improve the measurement accuracy and guidance accuracy. Least square method has lower accuracy than spheric harmonics function method. Neural network could fit precisely complicated curves or curved faces and the system error of electro-optical tracker system with X-Y gimbal is locate on a curve composed of angle values Analysis and simulation prove that BP neural network method improves the accuracy than spheric harmonics function method for about 8% and could have wider application scope.
机译:电光跟踪系统的系统误差校正可以提高测量精度和引导精度。最小二乘法比球体谐波功能方法较低。神经网络可以符合精确复杂的曲线或弯曲的曲线,并且具有XY Gimbal的电光跟踪系统的系统误差位于由角度值分析和仿真组成的曲线上,证明BP神经网络方法提高了比球体谐波功能方法的精度。大约8%,可以具有更广泛的应用范围。

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