Apart from positioning accuracy, the reliability of a navigation system is also significant, especially for safety–critical applications, such as intelligent vehicle navigation. Generally, the Global Navigation Satellite System (GNSS) positioning algorithm assumed that measurement noise is uncorrelated white noise. However, the appearance of colored noise, which comes from various noise sources, does not follow the Gaussian white noise assumption in the Kalman filter and would degrade both the accuracy and reliability of positioning. To deal with this problem, we propose a linear Kalman filter-based integrity monitoring method, which is based on a linear colored Kalman filter (CKF) considering measurement time correlation colored noise by a first-order Gauss–Markov model. Both simulated and real dynamic experiments were conducted to test the proposed algorithm. The results proved that CKF is capable of modeling time correlation with a realistic filter covariance in both simulated static and in-field dynamic tests. Furthermore, the performance of an integrity monitoring system with a protection level based on the CKF has proved to be more feasible and effective to bound position errors. Besides, the simulated results demonstrate that it can typically reduce false alarm by 24.81% in the horizontal direction and 39.47% in the vertical direction in a simulated experiment. The dynamic test shows that the proposed method can reduce the false alarm rate by 22.11% and 15.62% in the horizontal and vertical directions, respectively.

除定位精度外，导航系统的可靠性也很重要，尤其是对于安全性至关重要的应用，例如智能车辆导航。通常，全球导航卫星系统（GNSS）定位算法假定测量噪声是不相关的白噪声。但是，来自各种噪声源的有色噪声的出现不符合卡尔曼滤波器中的高斯白噪声假设，并且会降低定位的准确性和可靠性。为了解决这个问题，我们提出了一种基于线性卡尔曼滤波器的完整性监控方法，该方法基于一阶高斯-马尔可夫模型考虑测量时间相关色噪声的线性有色卡尔曼滤波器（CKF）。进行了模拟和实际动态实验，以测试该算法。结果证明，CKF能够在模拟的静态和现场动态测试中，以逼真的滤波器协方差建模时间相关性。此外，事实证明，具有基于CKF的保护级别的完整性监控系统的性能对于约束位置错误更为可行和有效。此外，仿真结果表明，在模拟实验中，它通常可以将水平方向的虚警减少24.81％，将垂直方向的虚警减少39.47％。动态测试表明，该方法在水平和垂直方向上的误报率分别降低了22.11％和15.62％。结果证明，CKF能够在模拟的静态和现场动态测试中，以逼真的滤波器协方差建模时间相关性。此外，事实证明，具有基于CKF的保护级别的完整性监控系统的性能对于约束位置错误更为可行和有效。此外，仿真结果表明，在模拟实验中，它通常可以将水平方向的虚警减少24.81％，将垂直方向的虚警减少39.47％。动态测试表明，该方法在水平和垂直方向上的误报率分别降低了22.11％和15.62％。结果证明，CKF能够在模拟的静态和现场动态测试中，以逼真的滤波器协方差建模时间相关性。此外，事实证明，具有基于CKF的保护级别的完整性监控系统的性能对于约束位置错误更为可行和有效。此外，仿真结果表明，在模拟实验中，它通常可以将水平方向的虚警减少24.81％，将垂直方向的虚警减少39.47％。动态测试表明，该方法在水平和垂直方向上的误报率分别降低了22.11％和15.62％。事实证明，基于CKF的具有保护级别的完整性监控系统的性能对于约束位置错误更为可行和有效。此外，仿真结果表明，在模拟实验中，它通常可以将水平方向的虚警减少24.81％，将垂直方向的虚警减少39.47％。动态测试表明，该方法在水平和垂直方向上的误报率分别降低了22.11％和15.62％。事实证明，基于CKF的具有保护级别的完整性监控系统的性能对于约束位置错误更为可行和有效。此外，仿真结果表明，在模拟实验中，它通常可以将水平方向的虚警降低24.81％，将垂直方向的虚警降低39.47％。动态测试表明，该方法在水平和垂直方向上的误报率分别降低了22.11％和15.62％。