Because of the challenges faced by GNSS/INS high-precision integrated navigation models in complex urban canyon environments, which are prone to occlusion, multipath effects, and fault interference, this article proposes a hierarchical resilient tightly coupled RTK/INS integrated navigation method that ensures system accuracy and robustness by implementing a multi-stage framework of detection, fault exclusion and multi-source enhancement. Initially, during the satellite RTK positioning stage, the method achieves rapid fault identification in the observation data of each epoch by introducing a Chi-square test-based fault detection method. If a fault is detected, a solution separation method is applied to accurately identify and isolate the faulty satellite, thereby enhancing the reliability of the satellite navigation system. However, due to the inherent limitations of threshold detection methods, while a loose threshold setting helps ensure the timely detection of large faults, it may also trigger false alarms, leading to the incomplete exclusion of some small faults. To further improve the resilience and reliability of the integrated navigation system, this article employs the IGG-III robust estimation method. By dynamically adjusting the observation weights within the integrated navigation system, this approach effectively enhances the system's capability to suppress small faults that fall below the threshold, thereby boosting its overall performance in complex environments. The experimental results indicate that the proposed algorithm reduces the eastward positioning error by 34.29% and the northward error by 13.22%. Notably, it achieves a significant 55.87% reduction in the upward positioning error. The overall performance evaluation results show that the proposed algorithm improves 3D positioning performance by 46% compared to conventional methods, which strongly validates its effectiveness and robustness in urban canyon environments.