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<p>By taking global navigation satellite system (GNSS) measurement information into account in the computation, the posterior integrity risk in comparison with prior integrity risk can better represent the actual integrity risk under given GNSS measurements. Researchers have actively explored posterior integrity monitoring. However, previous posterior integrity monitoring approaches compute the probabilities of position error and event hypothesis within the posterior integrity risk of each hypothesis separately. Furthermore, the continuity risk of posterior integrity monitoring is still an unresolved issue. We propose a Bayesian posterior integrity monitoring algorithm which maximizes the posterior integrity risk of each hypothesis by jointly optimizing the probability components of position error and event hypothesis. The false alarm contribution to the continuity risk of the proposed posterior integrity monitoring is evaluated by constructing the largest inscribed sphere in the parity space. Experiments based on real and simulated GNSS data demonstrate that the posterior integrity risk computed by the proposed algorithm is reliable and the posterior continuity risk is conservatively bounded.</p>

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GNSS posterior integrity and continuity risk bounds based on joint optimization

  • 期刊论文

  • 发表日期：

    2025年3月31日

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  • Baoyu Liu,
  • Yang Gao,
  • Guanwen Huang,
  • Wei Ding

摘要

By taking global navigation satellite system (GNSS) measurement information into account in the computation, the posterior integrity risk in comparison with prior integrity risk can better represent the actual integrity risk under given GNSS measurements. Researchers have actively explored posterior integrity monitoring. However, previous posterior integrity monitoring approaches compute the probabilities of position error and event hypothesis within the posterior integrity risk of each hypothesis separately. Furthermore, the continuity risk of posterior integrity monitoring is still an unresolved issue. We propose a Bayesian posterior integrity monitoring algorithm which maximizes the posterior integrity risk of each hypothesis by jointly optimizing the probability components of position error and event hypothesis. The false alarm contribution to the continuity risk of the proposed posterior integrity monitoring is evaluated by constructing the largest inscribed sphere in the parity space. Experiments based on real and simulated GNSS data demonstrate that the posterior integrity risk computed by the proposed algorithm is reliable and the posterior continuity risk is conservatively bounded.