A Seamless Navigation System and Applications for Autonomous Vehicles Using a Tightly Coupled GNSS/UWB/INS/Map Integration Scheme

Abstract

Seamless positioning systems for complex environments have been a popular focus of research on positioning safety for autonomous vehicles (AVs). In particular, the seamless high-precision positioning of AVs indoors and outdoors still poses considerable challenges and requires continuous, reliable, and high-precision positioning information to guarantee the safety of driving. To obtain effective positioning information, multiconstellation global navigation satellite system (multi-GNSS) real-time kinematics (RTK) and an inertial navigation system (INS) have been widely integrated into AVs. However, integrated multi-GNSS and INS applications cannot provide effective and seamless positioning results for AVs in indoor and outdoor environments due to limited satellite availability, multipath effects, frequent signal blockages, and the lack of GNSS signals indoors. In this contribution, multi-GNSS-tightly coupled (TC) RTK/INS technology is developed to solve the positioning problem for a challenging urban outdoor environment. In addition, ultrawideband (UWB)/INS technology is developed to provide accurate and continuous positioning results in indoor environments, and INS and map information are used to identify and eliminate UWB non-line-of-sight (NLOS) errors. Finally, an improved adaptive robust extended Kalman filter (AREKF) algorithm based on a TC integrated single-frequency multi-GNSS-TC RTK/UWB/INS/map system is studied to provide continuous, reliable, high-precision positioning information to AVs in indoor and outdoor environments. Experimental results show that the proposed scheme is capable of seamlessly guaranteeing the positioning accuracy of AVs in complex indoor and outdoor environments involving many measurement outliers and environmental interference effects.

Ultrawideband coupled relative positioning algorithm applicable to flight controller for multidrone collaboration

“…This is also true for the GPS-enabled environments. Some studies have used combinations of UWB, GNSS, and INS as anchor tag systems to obtain ground-truth coordinates, rather than for relative localization among multiple robots [16,17].…”

Improved-UWB/LiDAR-SLAM Tightly Coupled Positioning System with NLOS Identification Using a LiDAR Point Cloud in GNSS-Denied Environments

“…For indoor positioning scenarios in which NLOS errors exist, traditional NLOS identification techniques are broadly classified into three categories [5], namely, distance estimationbased methods [6,7], channel statistics-based methods [8][9][10][11][12][13][14] and position estimation-based methods [15][16][17][18][19]. Distance estimation-based methods distinguish between line-of-sight (LOS) and NLOS errors by comparing the variance in the distance estimate with a predefined threshold or by using the probability density function (PDF).…”

“…Suski et al and Zhu et al [16,17] improved UWB positioning accuracy by building a database of error fingerprints for indoor static environments. Wang et al [18,19] used manually drawn 2-D maps matched with line segment information for NLOS identification and adjusted the weights of UWB ranging values according to the obstruction situation, effectively eliminating the effect of NLOS errors. Although the methods in [16][17][18][19] are accurate, the preliminary measurements required to generate environmental maps can be a daunting task for large buildings, e.g., [16] distributed 8000 positioning error measurement points in a space of 12 × 8 m and collected a total of 4 million measurements, which was very time-consuming and tedious.…”

“…Wang et al [18,19] used manually drawn 2-D maps matched with line segment information for NLOS identification and adjusted the weights of UWB ranging values according to the obstruction situation, effectively eliminating the effect of NLOS errors. Although the methods in [16][17][18][19] are accurate, the preliminary measurements required to generate environmental maps can be a daunting task for large buildings, e.g., [16] distributed 8000 positioning error measurement points in a space of 12 × 8 m and collected a total of 4 million measurements, which was very time-consuming and tedious. Such an expensive data collection phase increases labor costs and reduces availability, and if the space changes in any way, including the movement of people or objects, the corresponding positioning error maps or digital maps are no longer valid.…”

GAN-FDSR: GAN-Based Fault Detection and System Reconfiguration Method

“…The global navigation satellite system (GNSS)/inertial navigation system (INS) integrated system compensates well for the deficiencies of a single navigation system by fusing the information of GNSS and INS [ 1 ], so as to obtain more accurate and reliable navigation results, and is widely used in many fields such as agricultural automation, robot control, traffic safety, and unmanned driving [ 2 , 3 , 4 ].…”