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Indoor wireless location technology using UWB base stations has many advantages, such as low power consumption, easy layout and high accuracy. Therefore, this technology has attracted great attention from industry and academia. However, indoor positioning accuracy is always affected by non-line of sight (NLOS) propagation, which originates from the reflection, refraction or scattering of UWB radio signals that will occur frequently due to the complexity of the indoor environment, resulting in gross errors. In extreme indoor environments, the system may not be available due to physical damage of the UWB base station. In view of this situation, we propose an integrity monitoring algorithm that can effectively detect faults and alarm in time to solve the adverse effects of system faults. UWB positioning system realizes positioning by combining trilateral measurement and least square method. In addition, the integrity detection algorithm (IM) integrating multiple hypothesis solution separation (MHSS) and UWB indoor error model is used to warn users in real time to avoid the risk that the positioning accuracy does not meet user requirements. The performance of the proposed IM algorithm has been extensively tested through simulation and field experiments. The experimental results show that IM algorithm significantly improves the positioning accuracy of UWB and the robustness of the positioning system. The experimental results show that IM algorithm can effectively identify the gross errors of 1m and above and improve the positioning accuracy of UWB and the robustness of the positioning system significantly.