A novel GNSS based V2V cooperative localization to exclude multipath effect using consistency checks

Abstract

Global Navigation Satellite System (GNSS) is essential for autonomous driving by providing absolute positioning solutions. However, the performance of GNSS measurement is significantly degraded in urban areas, due to the severe multipath and non-line-of-sight (NLOS) effects. To ensure the operation safety of autonomous driving applications, the GNSS localization performance is required to improve. In this study, a novel vehicle-to-vehicle (V2V) based cooperative localization algorithm with double-layers of consistency check (CC) is developed. GNSS pseudorange measurements of the ego-vehicle and surrounding vehicles conduct the first-layer of CC independently to exclude the multipath-biased measurement and obtaining their absolute positions. Then, the survived GNSS measurement and the absolute positions of each vehicles are shared in between, and further applied with double difference (DD) technique to obtain an accurate relative position between the surrounding vehicles. The second-layer CC is conducted during the GNSS DD-based relative positioning, to exclude the multipath and NLOS effects more comprehensively. Finally, the absolute and relative positions of surrounding vehicles are cooperated to optimize the final position of all participating vehicles. By the both simulation and real experimental results, the proposed algorithm is able to mitigate the multipath effect and significantly improve the accuracy of GNSS localization solutions to fulfill the safety requirements for autonomous driving.

GNSS Vulnerabilities and Existing Solutions: A Review of the Literature

“…In [93], Consistency check and double difference were used to mitigate physical degradation in GNSS pseudorange and vehicle-to-vehicle (V2V) ranging. Consistency check was individually applied to GNSS pseudorange and the V2V ranging.…”

Infrastructure Wi-Fi for connected autonomous vehicle positioning: A review of the state-of-the-art

“…Two techniques known as consistency check (CC) [61] and double difference (DD) [62] were applied in [63] to mitigate the effects of multipath/NLOS signals in GNSS pseudoranges and V2V radio ranging. In the proposed algorithm, the first CC was applied to the raw measurements obtained from the GNSS receiver and a second applied to measurements obtained in the V2V-DD ranging.…”

Collaborative GNSS Positioning with the Aids of 3D City Models

“…The survived measurements of each vehicle will be cooperated and applied with double difference to obtain the relative positions in between vehicles. Meanwhile, the consistency check will be employed again during the DD calculation, ensuring the consistency of measurements [8]. Based on the 3D building model in the operating area and the broadcast ephemeris, the GNSS range measurement that consisted of multipath and NLOS delay can be predicted using ray-tracing algorithm [13].…”

“…2) SDM: Shadow matching technique, regarding as an innovative 3D map aided positioning for a single user. [14] 3) CP-DD2CC: Collaborative positioning based on double layers consistency check [8]. 4) CP-3DMA: The proposed 3D map aided GNSS collaborative positioning algorithm.…”

“…First, due to the error distribution of GNSS shadow matching, its positioning solution is still able to combine with the 3D building model and ephemeris to classify and exclude the NLOS satellites. The survived raw GNSS measurements of each vehicle can be further applied with consistency check based fault detection and exclusion (FDE) [8]. After the 3D building model based and consistency check based FDE, the survived measurements can be considered as clean measurements to conduct DD technique, obtaining accurate relative positioning solutions between the vehicles.…”