Reliable continuing positioning is a critical requirement for intelligent transportation systems (ITS). An integrated positioning system is presented, where the global navigation satellite systems (GNSS) real-time kinematic (RTK) method was mainly used. When RTK is not available, positioning was maintained by using Doppler measurements or by low-cost inertial measurement unit (IMU) coupled with vehicle odometer measurements. A new integrity monitoring (IM) method is presented that addresses each positioning mode of the proposed integrated system. Models for the protection levels (PLs) are presented to bound the position error (PE) along the direction of motion of the vehicle and for the cross-track direction. Both direction components are needed, for instance for collision avoidance and for lane identification. The method was assessed through a kinematic test performed in a dense urban environment. Results showed that by integrating GNSS RTK, Doppler with IMU + odometer, positioning was available all the time. For RTK, positioning accuracy was less than a decimetre and the IM availability was 99%, where the PLs bounded the PEs and were less than an alert limit of 1 m. Positioning using Doppler and IMU + odometer measurements bridged RTK breaks but at the sub-meter level accuracy when used for short periods.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-its.2018.0106

Integrity monitoring for Positioning of intelligent transport systems using integrated RTK-GNSS, IMU and vehicle odometer

Continuous and trustworthy positioning is a critical capability for advanced driver assistance systems (ADAS). To achieve continuous positioning, methods such as global navigation satellite systems real-time kinematic (RTK), Doppler-based positioning, and positioning using low-cost inertial measurement unit (IMU) with car speedometer data are combined in this study. To ensure reliable positioning, the system should have integrity monitoring above a certain level, such as 99%. Achieving this level when combining different types of measurements that have different characteristics and different types of errors is a challenge. In this study, a novel integrity monitoring approach is presented for the proposed integrated system. A threat model of the measurements of the system components is discussed, which includes both the nominal performance and possible fault modes. A new protection level is presented to bound the maximum directional position error. The proposed approach was evaluated through a kinematic test in an urban area in Japan with a focus on horizontal positioning. Test results show that by integrating RTK, Doppler with IMU/speedometer, 100% positioning availability was achieved. The integrity monitoring availability was assessed and found to meet the target value where the position errors were bounded by the protection level, which was also less than an alert level, indicating the effectiveness of the proposed approach.

Integrity monitoring of vehicle positioning in urban environment using RTK-GNSS, IMU and speedometer

Advanced receiver autonomous integrity monitoring (ARAIM), based on multi-constellation and dual-frequency, can provide vertical navigation in terminal approaches. The baseline ARAIM receiver algorithm is based on the multiple hypothesis solution separation (MHSS). The fault modes determination scheme, proposed in the ARAIM baseline algorithm, is a sequential structure and a core processing which can be summarized in three steps: calculating the maximum number of simultaneous faults, forming all subsets, and filtering the subsets. The fault modes determined by the maximum number of simultaneous faults are sufficient, but not necessary. A set of redundant fault modes is included, which reduces the ARAIM performance and increases the computation burden. The continuity risk is not considered in the filtering. We propose a new fault modes determination scheme based on feedback structure with probability accumulation. The number of fault modes in the baseline algorithm is defined subject to a given integrity risk requirement. In the proposed algorithm, the fault modes are directly determined subject to this parameter. The fault modes are accumulated in descending order of fault probability. The probability of not monitored risk obtained in probability accumulation is closer to the integrity risk requirement compared to the baseline method, and the number of fault modes is reduced noticeably. The continuity detection is added to the feedback structure to find the severe integrity risk in time. The fault modes, determined in the proposed scheme, are sufficient and necessary. The performance evaluation results under a GPS-Galileo dual-constellation situation for localizer precision vertical 200 (LPV-200) requirements show that the proposed scheme can improve the availability of ARAIM from 84.92 to 92.25%. An enhanced effective monitor threshold (EMT) mainly contributes to this improvement. Furthermore, the proposed scheme also shows positive superiority in calculation load. The reduction in fault modes can directly contribute to the alleviation of the receiver calculation burden, which saves nearly 40% computational time on a PC-based software-defined receiver.

Improved ARAIM fault modes determination scheme based on feedback structure with probability accumulation

Advanced receiver autonomous integrity monitoring using triple frequency data with a focus on treatment of biases

Intelligent transportation systems (ITS) depend on global navigation satellite systems (GNSS) as a major positioning sensor, where the sensor should be able to detect and exclude faulty observations to support its reliability. In this article, two fault detection and exclusion (FDE) approaches are discussed. The first is its application in the observation domain using Chi-square test in Kalman filter processing. The second approach discusses FDE testing in the positioning domain using the solution separation (SS) method, where new FDE forms are presented that are tailored for ITS. In the first form, the test is parameterized along the direction of motion of the vehicle and in the cross-direction, which are relevant to applications that require lane identification and collision alert. A combined test is next established. Another form of the test is presented considering the maximum possible positioning error, and finally a direction-independent test. A new test that can be implemented in the urban environment is presented, which takes into account multipath effects that could disrupt the zero-mean normal distribution assumption of the positioning errors. Additionally, a test is presented to check that the position error resulting from the remaining measurements lies within acceptable limits. The proposed methods are demonstrated through a kinematic test run in various environments that may be experienced in ITS.

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C. Yang

Papers

Limited sensitivity analysis of ARAIM availability for LPV-200 over Australia using real data