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Special Issue "Sensors and System for Vehicle Navigation"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 29 February 2020.

Special Issue Editors

Prof. Dr. Andrzej Stateczny
E-Mail Website
Guest Editor
Department of Geodesy, Faculty of Civil and Environmental Engineering, Gdansk Technical University, Narutowicza St. 11/12, 80-233 Gdańsk, Poland
Tel. +48 609568961
Interests: navigation; multisensory data fusion; radar and sonar target detection and tracking; deep learning; geoinformatics
Special Issues and Collections in MDPI journals
Dr. Witold Kazimierski
E-Mail Website
Guest Editor
Faculty of Navigation, Chair of Geoinformatics, Maritime University of Szczecin, Poland
Tel. 0048 91 48 77 177
Interests: target tracking, navigation, radar, hydrography, data fusion, geoinformatics, cartography, spatial analysis
Special Issues and Collections in MDPI journals
Dr. Pawel Burdziakowski
E-Mail Website
Guest Editor
Department of Geodesy, Faculty of Civil and Environmental Engineering, Gdansk Technical University, Narutowicza St. 11/12, Gdansk, Poland
Interests: unmanned aerial vehicles indoor navigation; autonomous navigation and algorithms; non-GNSS navigation; photogrammetry; real-time photogrammetry; UAV technology; computer vision
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, vehicle navigation and especially autonomous navigation has been at the center of several major developments, both in civilian and defense applications. New technologies like multisensory data fusion, big data processing or deep learning are changing the quality of areas of applications, improving sensors and systems used. Recently, the influence of artificial intelligence on sensors data processing and understanding has emerged. Radar, LiDAR, visual sensors, sonar systems, and other sensors are mounted onboard of smart and flexible platforms and also on several types of unmanned vehicles in all types of environment. These technologies focusing on vehicle navigation may encounter many common scientific challenges. Particularly interesting is autonomous navigation for non-GNSS applications, like underwater and indoor vehicle navigation.

In this Special Issue of Sensors, we will collect articles covering many aspects of vehicle navigation like autonomous navigation, multisensor fusion, big data processing for vehicle navigation, sensors related to science/research, algorithms/technical development, analysis tools, synergy with sensors in navigation, data fusion, and artificial intelligence methods for navigation.

Prof. Dr. Stateczny Andrzej
Dr. Witold Kazimierski
Dr. Pawel Burdziakowski
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Multisensor data fusion for navigation
  • Sensors-based autonomous navigation
  • Comparative (terrain reference) navigation
  • Aerial, vehicle navigation
  • Surface vehicle navigation
  • Underwater vehicle navigation
  • Non-GNSS autonomous vehicle navigation
  • 3D radar and 3D sonar for vehicle navigation
  • Gravity and geomagnetic sensors for navigation
  • Sensor data processing, data reduction, feature extraction, and image understanding
  • Automatic target and obstacle detection and classification
  • Target tracking and anticollision algorithms and methods
  • Artificial Intelligence for navigation and sensors data processing
  • Big data processing for vehicle navigation
  • Path-planning methods for autonomous vehicle navigation
  • Real-time terrain matching images
  • Close range photogrammetry and commuter vision methods for vehicle navigation
  • Deep learning algorithms for vehicle navigation

Published Papers (7 papers)

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Research

Open AccessArticle
Implementing Autonomous Driving Behaviors Using a Message Driven Petri Net Framework
Sensors 2020, 20(2), 449; https://doi.org/10.3390/s20020449 - 13 Jan 2020
Abstract
Most autonomous car control frameworks are based on a middleware layer with several independent modules that are connected by an inter-process communication mechanism. These modules implement basic actions and report events about their state by subscribing and publishing messages. Here, we propose an [...] Read more.
Most autonomous car control frameworks are based on a middleware layer with several independent modules that are connected by an inter-process communication mechanism. These modules implement basic actions and report events about their state by subscribing and publishing messages. Here, we propose an executive module that coordinates the activity of these modules. This executive module uses hierarchical interpreted binary Petri nets (PNs) to define the behavior expected from the car in different scenarios according to the traffic rules. The module commands actions by sending messages to other modules and evolves its internal state according to the events (messages) received. A programming environment named RoboGraph (RG) is introduced with this architecture. RG includes a graphical interface that allows the edition, execution, tracing, and maintenance of the PNs. For the execution, a dispatcher loads these PNs and executes the different behaviors. The RG monitor that shows the state of all the running nets has proven to be very useful for debugging and tracing purposes. The whole system has been applied to an autonomous car designed for elderly or disabled people. Full article
(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)
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Open AccessArticle
Automatic Waypoint Generation to Improve Robot Navigation Through Narrow Spaces
Sensors 2020, 20(1), 240; https://doi.org/10.3390/s20010240 - 31 Dec 2019
Abstract
In domestic robotics, passing through narrow areas becomes critical for safe and effective robot navigation. Due to factors like sensor noise or miscalibration, even if the free space is sufficient for the robot to pass through, it may not see enough clearance to [...] Read more.
In domestic robotics, passing through narrow areas becomes critical for safe and effective robot navigation. Due to factors like sensor noise or miscalibration, even if the free space is sufficient for the robot to pass through, it may not see enough clearance to navigate, hence limiting its operational space. An approach to facing this is to insert waypoints strategically placed within the problematic areas in the map, which are considered by the robot planner when generating a trajectory and help to successfully traverse them. This is typically carried out by a human operator either by relying on their experience or by trial-and-error. In this paper, we present an automatic procedure to perform this task that: (i) detects problematic areas in the map and (ii) generates a set of auxiliary navigation waypoints from which more suitable trajectories can be generated by the robot planner. Our proposal, fully compatible with the robotic operating system (ROS), has been successfully applied to robots deployed in different houses within the H2020 MoveCare project. Moreover, we have performed extensive simulations with four state-of-the-art robots operating within real maps. The results reveal significant improvements in the number of successful navigations for the evaluated scenarios, demonstrating its efficacy in realistic situations. Full article
(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)
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Open AccessArticle
Direction of Arrival Estimation of GPS Narrowband Jammers Using High-Resolution Techniques
Sensors 2019, 19(24), 5532; https://doi.org/10.3390/s19245532 - 14 Dec 2019
Abstract
GPS jamming is a considerable threat to applications that rely on GPS position, velocity, and time. Jamming detection is the first step in the mitigation process. The direction of arrival (DOA) estimation of jamming signals is affected by resolution. In the presence of [...] Read more.
GPS jamming is a considerable threat to applications that rely on GPS position, velocity, and time. Jamming detection is the first step in the mitigation process. The direction of arrival (DOA) estimation of jamming signals is affected by resolution. In the presence of multiple jamming sources whose spatial separation is very narrow, an incorrect number of jammers can be detected. Consequently, mitigation will be affected. The ultimate objective of this research is to enhance GPS receivers’ anti-jamming abilities. This research proposes an enhancement to the anti-jamming detection ability of GPS receivers that are equipped with a uniform linear array (ULA) and uniform circular array (UCA). The proposed array processing method utilizes fast orthogonal search (FOS) to target the accurate detection of the DOA of both single and multiple in-band CW jammers. Its performance is compared to the classical method and MUSIC. GPS signals obtained from a Spirent GSS6700 simulator and CW jamming signals were used. The proposed method produces a threefold advantage, higher accuracy DOA estimates, amplitudes, and a correct number of jammers. Therefore, the anti-jamming process can be significantly improved by limiting the erroneous spatial attenuation of GPS signals arriving from an angle close to the jammer. Full article
(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)
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Open AccessArticle
Beam Search Algorithm for Ship Anti-Collision Trajectory Planning
Sensors 2019, 19(24), 5338; https://doi.org/10.3390/s19245338 - 04 Dec 2019
Abstract
The biggest challenges in the maritime environment are accidents and excessive fuel consumption. In order to improve the safety of navigation at sea and to reduce fuel consumption, the strategy of anti-collision, shortest trajectory planning is proposed. The strategy described in this paper [...] Read more.
The biggest challenges in the maritime environment are accidents and excessive fuel consumption. In order to improve the safety of navigation at sea and to reduce fuel consumption, the strategy of anti-collision, shortest trajectory planning is proposed. The strategy described in this paper is based on the beam search method. The beam search algorithm (BSA) takes into account many safe trajectories for the present ship and chooses the best in terms of length and other criteria. The risk of collision of present ship with any target ships is detected when the closest point of approach (CPA) of the present ship is violated by the target ship’s planned trajectory. Only course alteration of the present ship is applied, and not speed alteration. The algorithm has been implemented in the decision support system NAVDEC and tested in a real navigation environment on the m/f Wolin, a Polish ferry. Almost all BSA trajectories calculated were shorter in comparison to the standard NAVDEC-calculated algorithm. Full article
(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)
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Open AccessArticle
A Robust Cubature Kalman Filter with Abnormal Observations Identification Using the Mahalanobis Distance Criterion for Vehicular INS/GNSS Integration
Sensors 2019, 19(23), 5149; https://doi.org/10.3390/s19235149 - 25 Nov 2019
Cited by 1
Abstract
INS/GNSS (inertial navigation system/global navigation satellite system) integration is a promising solution of vehicle navigation for intelligent transportation systems. However, the observation of GNSS inevitably involves uncertainty due to the vulnerability to signal blockage in many urban/suburban areas, leading to the degraded navigation [...] Read more.
INS/GNSS (inertial navigation system/global navigation satellite system) integration is a promising solution of vehicle navigation for intelligent transportation systems. However, the observation of GNSS inevitably involves uncertainty due to the vulnerability to signal blockage in many urban/suburban areas, leading to the degraded navigation performance for INS/GNSS integration. This paper develops a novel robust CKF with scaling factor by combining the emerging cubature Kalman filter (CKF) with the concept of Mahalanobis distance criterion to address the above problem involved in nonlinear INS/GNSS integration. It establishes a theory of abnormal observations identification using the Mahalanobis distance criterion. Subsequently, a robust factor (scaling factor), which is calculated via the Mahalanobis distance criterion, is introduced into the standard CKF to inflate the observation noise covariance, resulting in a decreased filtering gain in the presence of abnormal observations. The proposed robust CKF can effectively resist the influence of abnormal observations on navigation solution and thus improves the robustness of CKF for vehicular INS/GNSS integration. Simulation and experimental results have demonstrated the effectiveness of the proposed robust CKF for vehicular navigation with INS/GNSS integration. Full article
(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)
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Open AccessArticle
Assessment of the Accuracy of Determining the Angular Position of the Unmanned Bathymetric Surveying Vehicle Based on the Sea Horizon Image
Sensors 2019, 19(21), 4644; https://doi.org/10.3390/s19214644 - 25 Oct 2019
Abstract
The paper presents the results of research on assessing the accuracy of angular position measurement relative to the sea horizon using a camera mounted on an unmanned bathymetric surveying vehicle of the Unmanned Surface Vehicle (USV) or Unmanned Aerial Vehicle (UAV) type. The [...] Read more.
The paper presents the results of research on assessing the accuracy of angular position measurement relative to the sea horizon using a camera mounted on an unmanned bathymetric surveying vehicle of the Unmanned Surface Vehicle (USV) or Unmanned Aerial Vehicle (UAV) type. The first part of the article presents the essence of the problem. The rules of taking the angular position of the vehicle into account in bathymetric surveys and the general concept of the two-camera tilt compensator were described. The second part presents a mathematical description of the meters characterizing a resolution and a mean error of measurements, made on the base of the horizon line image, recorded with an optical system with a Complementary Metal-Oxide Semiconductor (CMOS) matrix. The phenomenon of the horizon line curvature in the image projected onto the matrix that appears with the increase of the camera height has been characterized. The third part contains an example of a detailed analysis of selected cameras mounted on UAVs manufactured by DJI, carried out using the proposed meters. The obtained results including measurement resolutions of a single-pixel and mean errors of the horizon line slope measurement were presented in the form of many tables and charts with extensive comments. The final part presents the general conclusions from the performed research and a proposal of directions for their further development. Full article
(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)
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Open AccessArticle
Method of Evaluating the Positioning System Capability for Complying with the Minimum Accuracy Requirements for the International Hydrographic Organization Orders
Sensors 2019, 19(18), 3860; https://doi.org/10.3390/s19183860 - 06 Sep 2019
Cited by 4
Abstract
According to the IHO (International Hydrographic Organization) S-44 standard, hydrographic surveys can be carried out in four categories, the so-called orders—special, 1a, 1b, and 2—for which minimum accuracy requirements for the applied positioning system have been set out. These amount to, respectively: 2 [...] Read more.
According to the IHO (International Hydrographic Organization) S-44 standard, hydrographic surveys can be carried out in four categories, the so-called orders—special, 1a, 1b, and 2—for which minimum accuracy requirements for the applied positioning system have been set out. These amount to, respectively: 2 m, 5 m, 5 m, and 20 m at a confidence level of 0.95. It is widely assumed that GNSS (Global Navigation Satellite System) network solutions with an accuracy of 2–5 cm (p = 0.95) and maritime DGPS (Differential Global Positioning System) systems with an error of 1–2 m (p = 0.95) are currently the two main positioning methods in hydrography. Other positioning systems whose positioning accuracy increases from year to year (and which may serve as alternative solutions) have been omitted. The article proposes a method that enables an assessment of any given navigation positioning system in terms of its compliance (or non-compliance) with the minimum accuracy requirements specified for hydrographic surveys. The method concerned clearly assesses whether a particular positioning system meets the accuracy requirements set out for a particular IHO order. The model was verified, taking into account both past and present research results (stationary and dynamic) derived from tests on the following systems: DGPS, EGNOS (European Geostationary Navigation Overlay Service), and multi-GNSS receivers (GPS/GLONASS/BDS/Galileo). The study confirmed that the DGPS system meets the requirements for all IHO orders and proved that the EGNOS system can currently be applied in measurements in the orders 1a, 1b, and 2. On the other hand, multi-GNSS receivers meet the requirements for order 2, while some of them meet the requirements for orders 1a and 1b as well. Full article
(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)
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