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An effective procedure to operate tests of star tracker software routines using a sensor model

This paper presents a procedure for the validation of the software of an advanced star sensor by using a hardware model in a laboratory star field simulator. The mutual calibration of the sensor under test and of the simulator is realised by means of a neural network. It corrects errors from different sources adaptively, without need for specific models. Its correction capability has been compared to analytical models. Results of the procedure operation are presented to show that the angular measurement accuracy can be improved from 0.2° to 0.01°. Finally, its successful adoption for the validation of two star tracker software routines is reported.