A cooperative integrity monitoring (CIM) algorithm is proposed in this work. Under the CIM architecture, the algorithm can fully exploit the global navigation satellite system (GNSS) data and inter-vehicle measurements data to improve the detection and isolation of faulty measurements due to multipath or non line of sight (NLOS). Taking the advantages of cooperative scheme, a residual decomposition method is used to model the measurement errors into common and specific parts, a greedy search strategy is used to exclude the faulty measurements based on its sub-statistics. Simulation results show that CIM has better detection of GNSS fault than traditional receiver autonomous integrity monitoring (RAIM). Also, CIM is capable of detecting the faulty outliers in inter-vehicle measurements. The results indicate that CIM can be applied to many existing multi-sensor cooperative positioning algorithms.

中文翻译：

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多传感器协同定位的完整性

在这项工作中提出了一种协作完整性监控（CIM）算法。在CIM架构下，该算法可以充分利用全球导航卫星系统（GNSS）数据和车辆间测量数据，提高对多径或非视距（NLOS）导致的错误测量的检测和隔离。利用协作方案的优点，利用残差分解方法将测量误差建模为公共部分和特定部分，采用贪婪搜索策略基于其子统计量排除错误测量。仿真结果表明，CIM 比传统的接收机自主完整性监测（RAIM）具有更好的 GNSS 故障检测能力。此外，CIM 能够检测车辆间测量中的错误异常值。