As a potential solution for future urban transportation, the using of electric vertical takeoff and landing (eVTOL) aircraft, has great potential to alleviate urban traffic congestion and improve air traffic efficiency. In its commonly used navigation systems, integrated navigation and sensor redundancy technology are usually used to improve system reliability and safety. However, in the current sensor redundancy technology of navigation systems, redundant sensors only serve as data backup, resulting in insufficient information utilization of measurement data. To address this issue, this paper took the integrated navigation system of a triple redundant strapdown inertial navigation system (SINS) and a global navigation satellite system (GNSS) as the research object and proposed a real-time estimation method for gyroscope noise based on second-order differencing and redundant information of the inertial measurement unit (IMU). It derived recursive expressions for gyroscope noise estimation in the case of two and three redundancies. After obtaining the estimated noise value of the gyroscope, the navigation information of SINS and GNSS was fused to improve the accuracy and robustness of the integrated navigation system. Through simulation and real sports car tests on the SINS/GNSS integrated navigation system, the results show that the method proposed in this paper can accurately estimate gyroscope noise. Compared with traditional fusion methods, the navigation accuracy and anti-interference ability of the combined navigation system are improved after introducing the real-time estimation of gyroscope noise, which has practical engineering significance.