Abstract
The JAXA/ISAS SLIM project aims to land a small unmanned spacecraft on the Moon with pinpoint accuracy at its destination. This research aims to realize a method for estimating the flight position of a lunar explorer using image matching technology. The flight position is estimated by high-precision image matching between the lunar surface image taken by the probe and the lunar surface map image. However, the lunar surface image taken by the spacecraft is assumed to be a degraded low-resolution image due to various disturbances. This causes positional errors in the corresponding points between the captured image and the map image, which hinders the improvement of the accuracy of the transformation matrix. Therefore, an optimization method of transformation matrices based on the Gauss-Newton method is used to improve the accuracy of spacecraft flight position estimation. Besides, this method cannot eliminate the position error of the corresponding points themselves, thus limiting the improvement of position estimation accuracy. Then this study proposes a method for selecting corresponding points with small position error by utilizing the transformation matrix optimized by the Gauss-Newton method. Compared to the conventional method, the proposed method improved the number of successful estimates and the estimated average error from the true value. In particular, the proposed method was found to be effective for brightness, contrast, and noise disturbances, for which the conventional method had low position estimation accuracy.
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Itoh, M., Kamata, H. (2022). A Study of Self-position Estimation Method by Lunar Explorer by Selecting Corresponding Points Utilizing Gauss-Newton Method. In: Fan, W., Zhang, L., Li, N., Song, X. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2022. Communications in Computer and Information Science, vol 1712. Springer, Singapore. https://doi.org/10.1007/978-981-19-9198-1_25
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DOI: https://doi.org/10.1007/978-981-19-9198-1_25
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