Abstract
The cooperative localization as a satellite enhanced mean can extend the availability of positioning system and improve the accuracy of localization in some harsh environments, such as urban canyons, dense foliage, building block and so on. However, if there is a large amount of cooperative objectives in a densely deployed scenario, much connected links will cost a large number of time-frequency resources. The goal of this paper is to address the above question by a link selection algorithm based on an Extended Kalman Filter (EKF) and overlapping coalition formation (OCF) game. First, the EKF is used to obtain real-time state information updates. Then, a criterion is developed to determine whether users are well localized. If the criterion is satisfied, the efficient link selection problem is considered as an OCF game; otherwise, the user cooperates with others as many as possible to obtain accuracy state information. Numerical results show that the proposed algorithm can achieve performance improvement in localization accuracy compared to the no-cooperative approach, and achieve a much fewer link number at the cost of appropriate performance degradation.
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Ke, M., Tian, S., Wang, C., Zhong, X. (2019). A Link Selection Algorithm Based on EKF and Overlapping Coalition Formation Game for Hybrid Cooperative Positioning. In: Yu, Q. (eds) Space Information Networks. SINC 2018. Communications in Computer and Information Science, vol 972. Springer, Singapore. https://doi.org/10.1007/978-981-13-5937-8_19
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DOI: https://doi.org/10.1007/978-981-13-5937-8_19
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