Adaptive genetic algorithm-based method for antenna location optimization in RF relative measurement

The Radio Frequency (RF) relative measurement is a novel and compelling technology in the spacecraft formation flying aimed at detecting, acquiring, and tracking the relative position and attitude between spacecrafts. In the development of RF relative measurement sensors, it has been found that the locations of antennas affect the measurement accuracy of the relative position and attitude to a large extend. Thus, in this study, the selection of antenna location is modeled as a function optimization problem and an adaptive genetic algorithm-based optimization method is proposed to solve it. This method can adaptively optimize the locations of antennas on the spacecraft to improve the accuracy of RF relative measurement. The experimental results demonstrate that the proposed method can indeed improve the measurement accuracy and can be adapted for different mission requirements.

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