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20 September 2002 Modeling and non-linear correction of two-dimension photoelectric position sensitive detector
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Abstract
A modeling and non-linear correction method for the two-dimension photoelectric position sensitive detector (PSD) is presented by means of a radial basis function (RBF) neural network. Utilizing its powerful ability in function approximation, the RBF network can perform the mapping between the PSD's readings and the light spot actual position. In order to obtain the mapping, the RBF network is trained by learning algorithm with the input/output data pairs of the PSD. The mapping is used as an inverse model of the PSD from the readings to the light spot actual position or as a forward model of it from the light spot actual position to the readings. The inverse model based on RBF network is used as a corrector. This model provides a linear response when the PSD's readings applied to the inputs of the RBF network during operation. The example shows that the measuring system with a proper RBF network correction can provide a high linearity over a wide position range. Furthermore, the forward model that expresses the characteristics of the PSD will be beneficial to provide the theoretical instruction for the analysis, design and application of the PSD.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaodong Wang and Meiying Ye "Modeling and non-linear correction of two-dimension photoelectric position sensitive detector", Proc. SPIE 4919, Advanced Materials and Devices for Sensing and Imaging, (20 September 2002); https://doi.org/10.1117/12.471887
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