2,481 research outputs found
Improving performance of pedestrian positioning by using vehicular communication signals
Pedestrian-to-vehicle communications, where pedestrian devices transmit their position information to nearby vehicles to indicate their presence, help to reduce pedestrian accidents. Satellite-based systems are widely used for pedestrian positioning, but have much degraded performance in urban canyon, where satellite signals are often obstructed by roadside buildings. In this paper, we propose a pedestrian positioning method, which leverages vehicular communication signals and uses vehicles as anchors. The performance of pedestrian positioning is improved from three aspects: (i) Channel state information instead of RSSI is used to estimate pedestrian-vehicle distance with higher precision. (ii) Only signals with line-of-sight path are used, and the property of distance error is considered. (iii) Fast mobility of vehicles is used to get diverse measurements, and Kalman filter is applied to smooth positioning results. Extensive evaluations, via trace-based simulation, confirm that (i) Fixing rate of positions can be much improved. (ii) Horizontal positioning error can be greatly reduced, nearly by one order compared with off-the-shelf receivers, by almost half compared with RSSI-based method, and can be reduced further to about 80cm when vehicle transmission period is 100ms and Kalman filter is applied. Generally, positioning performance increases with the number of available vehicles and their transmission frequency
Satellite Navigation for the Age of Autonomy
Global Navigation Satellite Systems (GNSS) brought navigation to the masses.
Coupled with smartphones, the blue dot in the palm of our hands has forever
changed the way we interact with the world. Looking forward, cyber-physical
systems such as self-driving cars and aerial mobility are pushing the limits of
what localization technologies including GNSS can provide. This autonomous
revolution requires a solution that supports safety-critical operation,
centimeter positioning, and cyber-security for millions of users. To meet these
demands, we propose a navigation service from Low Earth Orbiting (LEO)
satellites which deliver precision in-part through faster motion, higher power
signals for added robustness to interference, constellation autonomous
integrity monitoring for integrity, and encryption / authentication for
resistance to spoofing attacks. This paradigm is enabled by the 'New Space'
movement, where highly capable satellites and components are now built on
assembly lines and launch costs have decreased by more than tenfold. Such a
ubiquitous positioning service enables a consistent and secure standard where
trustworthy information can be validated and shared, extending the electronic
horizon from sensor line of sight to an entire city. This enables the
situational awareness needed for true safe operation to support autonomy at
scale.Comment: 11 pages, 8 figures, 2020 IEEE/ION Position, Location and Navigation
Symposium (PLANS
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A Qualitative Analysis of Vehicle Positioning Requirements for Connected Vehicle Applications
Achieving genuinely dynamic road user charging : issues with a GNSS-based approach
Peer reviewedPostprin
Technologies and solutions for location-based services in smart cities: past, present, and future
Location-based services (LBS) in smart cities have drastically altered the way cities operate, giving a new dimension to the life of citizens. LBS rely on location of a device, where proximity estimation remains at its core. The applications of LBS range from social networking and marketing to vehicle-toeverything communications. In many of these applications, there is an increasing need and trend to learn the physical distance between nearby devices. This paper elaborates upon the current needs of proximity estimation in LBS and compares them against the available Localization and Proximity (LP) finding technologies (LP technologies in short). These technologies are compared for their accuracies and performance based on various different parameters, including latency, energy consumption, security, complexity, and throughput. Hereafter, a classification of these technologies, based on various different smart city applications, is presented. Finally, we discuss some emerging LP technologies that enable proximity estimation in LBS and present some future research areas
3D LiDAR Aided GNSS NLOS Mitigation for Reliable GNSS-RTK Positioning in Urban Canyons
GNSS and LiDAR odometry are complementary as they provide absolute and
relative positioning, respectively. Their integration in a loosely-coupled
manner is straightforward but is challenged in urban canyons due to the GNSS
signal reflections. Recent proposed 3D LiDAR-aided (3DLA) GNSS methods employ
the point cloud map to identify the non-line-of-sight (NLOS) reception of GNSS
signals. This facilitates the GNSS receiver to obtain improved urban
positioning but not achieve a sub-meter level. GNSS real-time kinematics (RTK)
uses carrier phase measurements to obtain decimeter-level positioning. In urban
areas, the GNSS RTK is not only challenged by multipath and NLOS-affected
measurement but also suffers from signal blockage by the building. The latter
will impose a challenge in solving the ambiguity within the carrier phase
measurements. In the other words, the model observability of the ambiguity
resolution (AR) is greatly decreased. This paper proposes to generate virtual
satellite (VS) measurements using the selected LiDAR landmarks from the
accumulated 3D point cloud maps (PCM). These LiDAR-PCM-made VS measurements are
tightly-coupled with GNSS pseudorange and carrier phase measurements. Thus, the
VS measurements can provide complementary constraints, meaning providing
low-elevation-angle measurements in the across-street directions. The
implementation is done using factor graph optimization to solve an accurate
float solution of the ambiguity before it is fed into LAMBDA. The effectiveness
of the proposed method has been validated by the evaluation conducted on our
recently open-sourced challenging dataset, UrbanNav. The result shows the fix
rate of the proposed 3DLA GNSS RTK is about 30% while the conventional GNSS-RTK
only achieves about 14%. In addition, the proposed method achieves sub-meter
positioning accuracy in most of the data collected in challenging urban areas
Security of GPS/INS based On-road Location Tracking Systems
Location information is critical to a wide-variety of navigation and tracking
applications. Today, GPS is the de-facto outdoor localization system but has
been shown to be vulnerable to signal spoofing attacks. Inertial Navigation
Systems (INS) are emerging as a popular complementary system, especially in
road transportation systems as they enable improved navigation and tracking as
well as offer resilience to wireless signals spoofing, and jamming attacks. In
this paper, we evaluate the security guarantees of INS-aided GPS tracking and
navigation for road transportation systems. We consider an adversary required
to travel from a source location to a destination, and monitored by a INS-aided
GPS system. The goal of the adversary is to travel to alternate locations
without being detected. We developed and evaluated algorithms that achieve such
goal, providing the adversary significant latitude. Our algorithms build a
graph model for a given road network and enable us to derive potential
destinations an attacker can reach without raising alarms even with the
INS-aided GPS tracking and navigation system. The algorithms render the
gyroscope and accelerometer sensors useless as they generate road trajectories
indistinguishable from plausible paths (both in terms of turn angles and roads
curvature). We also designed, built, and demonstrated that the magnetometer can
be actively spoofed using a combination of carefully controlled coils. We
implemented and evaluated the impact of the attack using both real-world and
simulated driving traces in more than 10 cities located around the world. Our
evaluations show that it is possible for an attacker to reach destinations that
are as far as 30 km away from the true destination without being detected. We
also show that it is possible for the adversary to reach almost 60-80% of
possible points within the target region in some cities
Nonvisible Satellite Estimation Algorithm for Improved UAV Navigation in Mountainous Regions
This paper presents a very simple and computationally
efficient algorithm for the calculation of the occlusion points
of a scene, observed from a given point of view. This algorithm
is used to calculate, in any point of a control volume, the
number of visible satellites and the Dilution Of Precision (DOP).
Knowledge of these information is extremely important to reject
measurements of non-visible satellites and for the reconstruction
of a fictitious Digital Elevation Map (DEM), that envelops all
the regions characterized by a number of visible satellites lower
than a given threshold. This DEM evolves in time according to
the platform motion and satellite dynamics. Because of this time
dependency, the Digital Morphing Map (DMM) has been defined.
When the DMM is available, it can be used by the path planning
algorithm to optimise the platform trajectory in order to avoid
regions where the number of visible satellites is dramatically
reduced, the DOP value is very high and the risk to receive
corrupted measurement is large. In this paper also presents the
concept of a Safety Bubble Obstacle Avoidance (SBOA) system.
This technique takes advantage from the numerical properties
of the covariance matrix defined in the Kalman filtering process.
A space and time safety bubble is defined according to the DOP
value and is used to automatically determine a minimum fly
distance from the surrounding obstacles
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