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This paper aims to explore the switching intention and behaviour of cloud storage services (CSS) individual users in China by integrating the variables of switching cost and habit into the expectation disconfirmation theory.

Based on 419 valid responses, structural equation modelling was used to examine the research model.

The results indicated that perceived usefulness and expectation disconfirmation have a positive and negative effect on user satisfaction, respectively. While expectation disconfirmation has a negative impact on perceived usefulness, user satisfaction positively affects users’ habit and switching cost. At the same time, switching intention is affected significantly and negatively by perceived usefulness, user satisfaction, as well as switching cost, where in switching intention and habit can commendably predict switching behaviour. The results can guide for CSS providers on how to successfully retain users in the competitive CSS market.

Previous researches have investigated the effects of perceived usefulness, switching cost and user traits on CSS adoption and continuance intention, as well as behaviour; they neglected the antecedents of switching cost and the effect of user habit on them. Additionally, relatively few studies have been devoted to an empirical examination of the switching behaviour from a particular CSS product to its rival products at the individual user level. This research tries to fill these gaps.

The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy.

In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter.

The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy.

Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors.

Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination.

This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.