<h3>Abstract</h3> Factor graph optimization (FGO) recently has attracted attention as an alternative to the extended Kalman filter (EKF) for GNSS-INS integration. This study evaluates both loosely and tightly coupled integrations of GNSS code pseudorange INS measurements real-time positioning, using conventional EKF FGO with a dataset collected in urban canyon Hong Kong. The strength is analyzed by degenerating FGO-based estimator into "EKF-like estimator." In addition, effects window size...

GNSS/INS integrated solution has been extensively studied over the past decades. However, its performance relies heavily on environmental conditions and sensor costs. The GNSS positioning can obtain satisfactory in open area. Unfortunately, accuracy be severely degraded a highly urbanized area, due to notorious multipath effects none-line-of-sight (NLOS) receptions. As result, excessive outliers occur, which causes huge error integration. This paper proposes apply fish-eye camera capture sky...

Mapping and localization is a critical module of autonomous driving, significant achievements have been reached in this field. Beyond Global Navigation Satellite System (GNSS), research point cloud registration, visual feature matching, inertia navigation has greatly enhanced the accuracy robustness mapping different scenarios. However, highly urbanized scenes are still challenging: LIDAR- camera-based methods perform poorly with numerous dynamic objects; GNSS-based solutions experience...

Absolute positioning is an essential factor for the arrival of autonomous driving. At present, GNSS indispensable source that can supply initial in commonly used high definition map-based LiDAR point cloud solution However, non-light-of-sight (NLOS) reception dominates performance super-urbanized areas. The recent proposed 3D map aided (3DMA) mitigate majority NLOS caused by buildings. same phenomenon moving objects urban areas currently not modeled geographic information system (GIS)....

Urban canyon is typical in megacities like Hong Kong and Tokyo. Accurate positioning urban canyons remains a challenging problem for the applications with navigation requirements, such as pedestrian, autonomous driving vehicles unmanned aerial vehicles. The GNSS can be significantly degraded canyons, due to signal blockage by tall buildings. visual LiDAR considerably affected numerous dynamic objects. To facilitate research development of robust, accurate precise using multiple sensors we...

Global navigation satellite systems (GNSS) are one of the utterly popular sources for providing globally referenced positioning autonomous systems. However, performance GNSS is significantly challenged in urban canyons, due to signal reflection and blockage from buildings. Given fact that measurements highly environmentally dependent time-correlated, conventional filtering-based method cannot simultaneously explore time-correlation among historical measurements. As a result, estimator...

This paper proposes a 3D LiDAR aided global navigation satellite system (GNSS) non-line-of-sight (NLOS) mitigation method due to both static buildings and dynamic objects. A sliding window map describing the environment of ego-vehicle is first generated, based on real-time point clouds from sensor. Subsequently, NLOS receptions are detected using proposed quick searching which eliminates reliance initial guessing position GNSS receiver. Instead directly excluding satellites further...

Pedestrian location tracking in emergency responses and environmental surveys of indoor scenarios tend to rely only on their own mobile devices, reducing the usage external services. Low-cost small-sized inertial measurement units (IMU) have been widely distributed devices. However, they suffer from high-level noises, leading drift position estimation over time. In this work, we present a graph-based 3D pedestrian with inertial-only perception. The proposed method uses onboard sensors...

Robust and lane-level positioning is essential for autonomous vehicles. As an irreplaceable sensor, Light detection ranging (LiDAR) can provide continuous high-frequency pose estimation by means of mapping, on condition that enough environment features are available. The error mapping accumulate over time. Therefore, LiDAR usually integrated with other sensors. In diverse urban scenarios, the feature availability relies heavily traffic (moving static objects) degree urbanization. Common...

We present a novel method to detect the GNSS NLOS and correct pseudorange measurements based on on-board sensing. This paper demonstrates use of LiDAR scanner list building heights describe perceived environment. To estimate geometry pose top edges buildings (TEBs) relative receiver, surface segmentation is employed TEBs surrounding using 3D point clouds. The are extracted extended height in Skyplot identify NLOS-affected ones. Innovatively, delay corrected detected TEBs. Weighted least...

This article proposes an improved global navigation satellite system (GNSS) positioning method that explores the time correlation between consecutive epochs of code and carrier-phase measurements, which significantly increases robustness against outlier measurements. Instead relying on difference carrier phase only considers two neighboring using extended Kalman filter estimator, this proposed to employ measurements inside a window, so-called window (WCP), constrain states factor graph. A...

<h3>Abstract</h3> Accurate positioning in urban canyons remains a challenging problem. To facilitate the research and development of reliable precise methods using multiple sensors canyons, we built multisensory dataset, <i>UrbanNav</i>, collected diverse, scenarios Hong Kong. The dataset provides multi-sensor data, including data from multi-frequency global navigation satellite system (GNSS) receivers, an inertial measurement unit (IMU), light detection ranging (lidar) units, cameras....

Integration of global navigation satellite system (GNSS) and inertial (INS) is extensively studied in the past decades. Conventionally, two most common integration solutions are loosely tightly coupled integrations using extended Kalman filter (EKF). Recently, factor graph technique adopted to integrate GNSS/INS improved performance obtained compared with EKF-based integration. However, only simulated data tested show effectiveness graph-based method existing work. Moreover, reason that why...

Absolute positioning is an essential factor for the arrival of autonomous driving. Global Navigation Satellites System (GNSS) receiver provides absolute localization it. GNSS solution can provide satisfactory in open or sub-urban areas, however, its performance suffered super-urbanized area due to phenomenon which are well-known as multipath effects and NLOS receptions. The dominate area. recent proposed 3D map aided (3DMA) mitigate most receptions caused by buildings based on city models....

Performing precise positioning is still challenging for autonomous driving. Global navigation satellite system (GNSS) performance can be significantly degraded due to the non-line-of-sight (NLOS) reception. Recently, studies of 3D building model aided (3DMA) GNSS show promising improvements in urban canyons. In this study, benefits 3DMA are further extended GNSS/inertial (INS) integration system. Based on shadow matching solution and scoring information candidate positions, two methods...

Robust and globally‐referenced positioning is indispensable for autonomous driving vehicles. Global navigation satellite system (GNSS) still an irreplaceable sensor. Satisfactory accuracy (about 1 m) can be obtained in sparse areas. However, the GNSS error up to 100 m dense urban areas due multipath effects non‐line‐of‐sight (NLOS) receptions caused by reflection blockage from buildings. NLOS currently dominant factor degrading performance of positioning. Recently, camera has been employed...

Accurate, continuous and seamless state estimation is the fundamental module for intelligent navigation applications, such as self-driving cars autonomous robots. However, it often difficult a standalone sensor to fulfill demanding requirements of precise in complex scenarios. To fill this gap, letter proposes exploit complementariness global satellite system (GNSS), inertial measurement unit (IMU) vision via tightly coupled integration method, aiming achieve accurate urban environments....

Intelligent vehicles demand reliable, continuous, and accurate positioning capability. Light Detection Ranging (LiDAR)-inertial odometry (LIO) provides precise continuous relative pose estimation but suffers from drift over large-scale operations. Global navigation satellite system (GNSS) offers drift-free absolute capability the accuracy is strongly affected by non-line-of-sight (NLOS) receptions multipath effects arising reflections of surrounding environments. The tightly-coupled...

In the field of autonomous driving, micro-electromechanical systems (MEMS)-based vehicle navigation usually adopts multi-sensor integrated to achieve high-precision positioning. However, due complex environments, accuracy and reliability sensors may be significantly reduced. To address these challenges, interacting multiple model (IMM)-based strapdown inertial system/global satellite system/odometer/non-holonomic constrain (SINS/GNSS/OD/NHC) is adopted. Unfortunately, use traditional...

In this paper, a two-way thermal-fluid coupling model of aviation transmission systems is proposed. The influence oil-gas temperature rise obtained, and the cooling mechanism gear-side oil injection bearing under-race lubrication analyzed. Windage loss at high speed leads to significant rise, up 18℃, which becomes main factor affecting high-speed light-load gear end chain. Gear-side creates steeper gradient on side, thereby reducing by 3 8°C. For bearings, employs centrifugal forces...