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6 pages, 202 KiB

Open AccessEditorial

Sensors and System for Vehicle Navigation

by Andrzej Stateczny, Witold Kazimierski and Pawel Burdziakowski

Sensors 2022, 22(5), 1723; https://doi.org/10.3390/s22051723 - 23 Feb 2022

Cited by 2 | Viewed by 1819

Abstract

In recent years, vehicle navigation, in particular autonomous navigation, has been at the center of several major developments, both in civilian and defense applications [...] Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

Research

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20 pages, 11228 KiB

Open AccessArticle

Performance Evaluation of IMU and DVL Integration in Marine Navigation

by Gen Fukuda, Daisuke Hatta, Xiaoliang Guo and Nobuaki Kubo

Sensors 2021, 21(4), 1056; https://doi.org/10.3390/s21041056 - 04 Feb 2021

Cited by 14 | Viewed by 5137

Abstract

Global navigation satellite system (GNSS) spoofing poses a significant threat to maritime logistics. Many maritime electronic devices rely on GNSS time, positioning, and speed for safe vessel operation. In this study, inertial measurement unit (IMU) and Doppler velocity log (DVL) devices, which are [...] Read more.

Global navigation satellite system (GNSS) spoofing poses a significant threat to maritime logistics. Many maritime electronic devices rely on GNSS time, positioning, and speed for safe vessel operation. In this study, inertial measurement unit (IMU) and Doppler velocity log (DVL) devices, which are important in the event of GNSS spoofing or outage, are considered in conventional navigation. A velocity integration method using IMU and DVL in terms of dead-reckoning is investigated in this study. GNSS has been widely used for ship navigation, but IMU, DVL, or combined IMU and DVL navigation have received little attention. Military-grade sensors are very expensive and generally cannot be utilized in smaller vessels. Therefore, this study focuses on the use of consumer-grade sensors. First, the performance of a micro electromechanical system (MEMS)-based yaw rate angle with DVL was evaluated using 60 min of raw data for a 50 m-long ship located in Tokyo Bay. Second, the performance of an IMU-MEMS using three gyroscopes and three accelerometers with DVL was evaluated using the same dataset. A gyrocompass, which is equipped on the ship, is used as a heading reference. The results proved that both methods could achieve less than 1 km horizontal error in 60 min. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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18 pages, 6365 KiB

Open AccessArticle

Bionic Integrated Positioning Mechanism Based on Bioinspired Polarization Compass and Inertial Navigation System

by Qingyun Zhang, Jian Yang, Panpan Huang, Xin Liu, Shanpeng Wang and Lei Guo

Sensors 2021, 21(4), 1055; https://doi.org/10.3390/s21041055 - 04 Feb 2021

Cited by 10 | Viewed by 2195

Abstract

In this paper, to address the problem of positioning accumulative errors of the inertial navigation system (INS), a bionic autonomous positioning mechanism integrating INS with a bioinspired polarization compass is proposed. In addition, the bioinspired positioning system hardware and the integration model are [...] Read more.

In this paper, to address the problem of positioning accumulative errors of the inertial navigation system (INS), a bionic autonomous positioning mechanism integrating INS with a bioinspired polarization compass is proposed. In addition, the bioinspired positioning system hardware and the integration model are also presented. Concerned with the technical issue of the accuracy and environmental adaptability of the integrated positioning system, the sun elevation calculating method based on the degree of polarization (DoP) and direction of polarization (E-vector) is presented. Moreover, to compensate for the latitude and longitude errors of INS, the bioinspired positioning system model combining the polarization compass and INS is established. Finally, the positioning performance of the proposed bioinspired positioning system model was validated via outdoor experiments. The results indicate that the proposed system can compensate for the position errors of INS with satisfactory performance. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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14 pages, 857 KiB

Open AccessArticle

Multiple Object Detection Based on Clustering and Deep Learning Methods

by Huu Thu Nguyen, Eon-Ho Lee, Chul Hee Bae and Sejin Lee

Sensors 2020, 20(16), 4424; https://doi.org/10.3390/s20164424 - 07 Aug 2020

Cited by 27 | Viewed by 5109

Abstract

Multiple object detection is challenging yet crucial in computer vision. In This study, owing to the negative effect of noise on multiple object detection, two clustering algorithms are used on both underwater sonar images and three-dimensional point cloud LiDAR data to study and [...] Read more.

Multiple object detection is challenging yet crucial in computer vision. In This study, owing to the negative effect of noise on multiple object detection, two clustering algorithms are used on both underwater sonar images and three-dimensional point cloud LiDAR data to study and improve the performance result. The outputs from using deep learning methods on both types of data are treated with K-Means clustering and density-based spatial clustering of applications with noise (DBSCAN) algorithms to remove outliers, detect and cluster meaningful data, and improve the result of multiple object detections. Results indicate the potential application of the proposed method in the fields of object detection, autonomous driving system, and so forth. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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27 pages, 3039 KiB

Open AccessArticle

Path Planner for Autonomous Exploration of Underground Mines by Aerial Vehicles

by Carlos Rubio-Sierra, Diego Domínguez, Jesús Gonzalo and Alberto Escapa

Sensors 2020, 20(15), 4259; https://doi.org/10.3390/s20154259 - 30 Jul 2020

Cited by 6 | Viewed by 3152

Abstract

This paper presents a path planner solution that makes it possible to autonomously explore underground mines with aerial robots (typically multicopters). In these environments the operations may be limited by many factors like the lack of external navigation signals, the narrow passages and [...] Read more.

This paper presents a path planner solution that makes it possible to autonomously explore underground mines with aerial robots (typically multicopters). In these environments the operations may be limited by many factors like the lack of external navigation signals, the narrow passages and the absence of radio communications. The designed path planner is defined as a simple and highly computationally efficient algorithm that, only relying on a laser imaging detection and ranging (LIDAR) sensor with Simultaneous localization and mapping (SLAM) capability, permits the exploration of a set of single-level mining tunnels. It performs dynamic planning based on exploration vectors, a novel variant of the open sector method with reinforced filtering. The algorithm incorporates global awareness and obstacle avoidance modules. The first one prevents the possibility of getting trapped in a loop, whereas the second one facilitates the navigation along narrow tunnels. The performance of the proposed solution has been tested in different study cases with a Hardware-in-the-loop (HIL) simulator developed for this purpose. In all situations the path planner logic performed as expected and the used routing was optimal. Furthermore, the path efficiency, measured in terms of traveled distance and used time, was high when compared with an ideal reference case. The result is a very fast, real-time, and static memory capable algorithm, which implemented on the proposed architecture presents a feasible solution for the autonomous exploration of underground mines. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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33 pages, 13767 KiB

Open AccessArticle

Elevation Angle Estimations of Wide-Beam Acoustic Sonar Measurements for Autonomous Underwater Karst Exploration

by Yohan Breux and Lionel Lapierre

Sensors 2020, 20(14), 4028; https://doi.org/10.3390/s20144028 - 20 Jul 2020

Cited by 4 | Viewed by 2882

Abstract

This paper proposes a solution for merging the measurements from two perpendicular profiling sonars with different beam-widths, in the context of underwater karst (cave) exploration and mapping. This work is a key step towards the development of a full 6D pose SLAM framework [...] Read more.

This paper proposes a solution for merging the measurements from two perpendicular profiling sonars with different beam-widths, in the context of underwater karst (cave) exploration and mapping. This work is a key step towards the development of a full 6D pose SLAM framework adapted to karst aquifer, where potential water turbidity disqualifies vision-based methods, hence relying on acoustic sonar measurements. Those environments have complex geometries which require 3D sensing. Wide-beam sonars are mandatory to cover previously seen surfaces but do not provide 3D measurements as the elevation angles are unknown. The approach proposed in this paper leverages the narrow-beam sonar measurements to estimate local karst surface with Gaussian process regression. The estimated surface is then further exploited to infer scaled-beta distributions of elevation angles from a wide-beam sonar. The pertinence of the method was validated through experiments on simulated environments. As a result, this approach allows one to benefit from the high coverage provided by wide-beam sonars without the drawback of loosing 3D information. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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16 pages, 4909 KiB

Open AccessArticle

Malicious UAV Detection Using Integrated Audio and Visual Features for Public Safety Applications

by Sonain Jamil, Fawad, MuhibUr Rahman, Amin Ullah, Salman Badnava, Masoud Forsat and Seyed Sajad Mirjavadi

Sensors 2020, 20(14), 3923; https://doi.org/10.3390/s20143923 - 15 Jul 2020

Cited by 38 | Viewed by 7886

Abstract

Unmanned aerial vehicles (UAVs) have become popular in surveillance, security, and remote monitoring. However, they also pose serious security threats to public privacy. The timely detection of a malicious drone is currently an open research issue for security provisioning companies. Recently, the problem [...] Read more.

Unmanned aerial vehicles (UAVs) have become popular in surveillance, security, and remote monitoring. However, they also pose serious security threats to public privacy. The timely detection of a malicious drone is currently an open research issue for security provisioning companies. Recently, the problem has been addressed by a plethora of schemes. However, each plan has a limitation, such as extreme weather conditions and huge dataset requirements. In this paper, we propose a novel framework consisting of the hybrid handcrafted and deep feature to detect and localize malicious drones from their sound and image information. The respective datasets include sounds and occluded images of birds, airplanes, and thunderstorms, with variations in resolution and illumination. Various kernels of the support vector machine (SVM) are applied to classify the features. Experimental results validate the improved performance of the proposed scheme compared to other related methods. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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16 pages, 4458 KiB

Open AccessArticle

Improving Robot Localization Using Doppler-Based Variable Sensor Covariance Calculation

by Bibiana Fariña, Jonay Toledo, Jose Ignacio Estevez and Leopoldo Acosta

Sensors 2020, 20(8), 2287; https://doi.org/10.3390/s20082287 - 17 Apr 2020

Cited by 9 | Viewed by 2841

Abstract

This paper describes a localization module for an autonomous wheelchair. This module includes a combination of various sensors such as odometers, laser scanners, IMU and Doppler speed sensors. Every sensor used in the module features variable covariance estimation in order to yield a [...] Read more.

This paper describes a localization module for an autonomous wheelchair. This module includes a combination of various sensors such as odometers, laser scanners, IMU and Doppler speed sensors. Every sensor used in the module features variable covariance estimation in order to yield a final accurate localization. The main problem of a localization module composed of different sensors is the accuracy estimation of each sensor. Average static values are normally used, but these can lead to failure in some situations. In this paper, all the sensors have a variable covariance estimation that depends on the data quality. A Doppler speed sensor is used to estimate the covariance of the encoder odometric localization. Lidar is also used as a scan matching localization algorithm, comparing the difference between two consecutive scans to obtain the change in position. Matching quality gives the accuracy of the scan matcher localization. This structure yields a better position than a traditional odometric static covariance method. This is tested in a real prototype and compared to a standard fusion technique. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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25 pages, 7118 KiB

Open AccessArticle

Integrity Concept for Maritime Autonomous Surface Ships’ Position Sensors

by Paweł Zalewski

Sensors 2020, 20(7), 2075; https://doi.org/10.3390/s20072075 - 07 Apr 2020

Cited by 12 | Viewed by 6031

Abstract

The primary means for electronic position fixing currently in use in majority of contemporary merchant ships are shipborne GPS (Global Positioning System) receivers or DGPS (Differential GPS) and IALA (International Association of Lighthouse Authorities) radio beacon receivers. More advanced GNSS (Global Navigation Satellite [...] Read more.

The primary means for electronic position fixing currently in use in majority of contemporary merchant ships are shipborne GPS (Global Positioning System) receivers or DGPS (Differential GPS) and IALA (International Association of Lighthouse Authorities) radio beacon receivers. More advanced GNSS (Global Navigation Satellite System) receivers able to process signals from GPS, Russian GLONASS, Chinese Beidou, European Galileo, Indian IRNSS, Japan QZSS, and satellite-based augmentation systems (SBAS), are still relatively rare in maritime domain. However, it is expected that such combined or multi-system receivers will soon become more common in maritime transport and integrated with gyro, inertial, radar, laser, and optical sensors, and they will become indispensable onboard maritime autonomous surface ships (MASS). To be prepared for a malfunction of any position sensors, their state-of-the-art integrity monitoring should be developed and standardized, taking into account the specificity of MASS and e-navigation safety. The issues of existing requirements, performance standards, and future concepts of integrity monitoring for maritime position sensors are discussed and presented in this paper. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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16 pages, 6671 KiB

Open AccessArticle

Doppler-Spectrum Feature-Based Human–Vehicle Classification Scheme Using Machine Learning for an FMCW Radar Sensor

by Eugin Hyun and YoungSeok Jin

Sensors 2020, 20(7), 2001; https://doi.org/10.3390/s20072001 - 02 Apr 2020

Cited by 20 | Viewed by 5349

Abstract

In this paper, we propose a Doppler-spectrum feature-based human–vehicle classification scheme for an FMCW (frequency-modulated continuous wave) radar sensor. We introduce three novel features referred to as the scattering point count, scattering point difference, and magnitude difference rate features based on the characteristics [...] Read more.

In this paper, we propose a Doppler-spectrum feature-based human–vehicle classification scheme for an FMCW (frequency-modulated continuous wave) radar sensor. We introduce three novel features referred to as the scattering point count, scattering point difference, and magnitude difference rate features based on the characteristics of the Doppler spectrum in two successive frames. We also use an SVM (support vector machine) and BDT (binary decision tree) for training and validation of the three aforementioned features. We measured the signals using a 24-GHz FMCW radar front-end module and a real-time data acquisition module and extracted three features from a walking human and a moving vehicle in the field. We then repeatedly measured the classification decision rate of the proposed algorithm using the SVM and BDT, finding that the average performance exceeded 99% and 96% for the walking human and the moving vehicle, respectively. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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22 pages, 8098 KiB

Open AccessArticle

Multi-Network Asynchronous TDOA Algorithm Test in a Simulated Maritime Scenario

by Ciro Gioia, Francesco Sermi and Dario Tarchi

Sensors 2020, 20(7), 1842; https://doi.org/10.3390/s20071842 - 26 Mar 2020

Cited by 5 | Viewed by 3961

Abstract

In the last few years, the number of applications relying on position of vessels at sea has grown significantly. Usually, these applications exploit information provided by the Automatic Identification System (AIS). Unfortunately, the cooperative nature of AIS makes it vulnerable to different types [...] Read more.

In the last few years, the number of applications relying on position of vessels at sea has grown significantly. Usually, these applications exploit information provided by the Automatic Identification System (AIS). Unfortunately, the cooperative nature of AIS makes it vulnerable to different types of attack. Therefore, especially for critical applications, the veracity of the position information reported in the AIS message needs to be verified. Several techniques can be adopted to this end. This paper presents a mathematical extension of the traditional Time Difference Of Arrival (TDOA) localisation technique allowing merging TDOA measurement from synchronous and non-synchronous receivers. This technique was tested in a simulated scenario, where the position of a moving target was estimated using different configurations of the receivers network. The robustness of the proposed algorithm with respect to the traditional one is demonstrated. The proposed approach, which is derived form satellite applications, is not limited to the AIS signals or to the maritime domain, and it can be adopted to estimate the position of any radiofrequency transmitter, by employing a suitable number of non-synchronous receivers. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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26 pages, 17746 KiB

Open AccessArticle

Implementing Autonomous Driving Behaviors Using a Message Driven Petri Net Framework

by Joaquín López, Pablo Sánchez-Vilariño, Rafael Sanz and Enrique Paz

Sensors 2020, 20(2), 449; https://doi.org/10.3390/s20020449 - 13 Jan 2020

Cited by 11 | Viewed by 4622

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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20 pages, 4469 KiB

Open AccessArticle

Automatic Waypoint Generation to Improve Robot Navigation Through Narrow Spaces

by Francisco-Angel Moreno, Javier Monroy, Jose-Raul Ruiz-Sarmiento, Cipriano Galindo and Javier Gonzalez-Jimenez

Sensors 2020, 20(1), 240; https://doi.org/10.3390/s20010240 - 31 Dec 2019

Cited by 28 | Viewed by 7440

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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18 pages, 8040 KiB

Open AccessArticle

Direction of Arrival Estimation of GPS Narrowband Jammers Using High-Resolution Techniques

by Mohamed Moussa, Abdalla Osman, Mohamed Tamazin, Michael J. Korenberg and Aboelmagd Noureldin

Sensors 2019, 19(24), 5532; https://doi.org/10.3390/s19245532 - 14 Dec 2019

Cited by 7 | Viewed by 4364

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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15 pages, 3474 KiB

Open AccessArticle

Beam Search Algorithm for Ship Anti-Collision Trajectory Planning

by Joanna Karbowska-Chilinska, Jolanta Koszelew, Krzysztof Ostrowski, Piotr Kuczynski, Eric Kulbiej and Piotr Wolejsza

Sensors 2019, 19(24), 5338; https://doi.org/10.3390/s19245338 - 04 Dec 2019

Cited by 12 | Viewed by 3567

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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20 pages, 5431 KiB

Open AccessArticle

A Robust Cubature Kalman Filter with Abnormal Observations Identification Using the Mahalanobis Distance Criterion for Vehicular INS/GNSS Integration

by Bingbing Gao, Gaoge Hu, Xinhe Zhu and Yongmin Zhong

Sensors 2019, 19(23), 5149; https://doi.org/10.3390/s19235149 - 25 Nov 2019

Cited by 23 | Viewed by 3493

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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22 pages, 13748 KiB

Open AccessArticle

Assessment of the Accuracy of Determining the Angular Position of the Unmanned Bathymetric Surveying Vehicle Based on the Sea Horizon Image

by Krzysztof Naus, Łukasz Marchel, Piotr Szymak and Aleksander Nowak

Sensors 2019, 19(21), 4644; https://doi.org/10.3390/s19214644 - 25 Oct 2019

Cited by 5 | Viewed by 2788

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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14 pages, 3012 KiB

Open AccessArticle

Method of Evaluating the Positioning System Capability for Complying with the Minimum Accuracy Requirements for the International Hydrographic Organization Orders

by Mariusz Specht

Sensors 2019, 19(18), 3860; https://doi.org/10.3390/s19183860 - 06 Sep 2019

Cited by 21 | Viewed by 3459

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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Review

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17 pages, 2450 KiB

Open AccessReview

Analysis of GNSS, Hydroacoustic and Optoelectronic Data Integration Methods Used in Hydrography

by Oktawia Lewicka, Mariusz Specht, Andrzej Stateczny, Cezary Specht, David Brčić, Alen Jugović, Szymon Widźgowski and Marta Wiśniewska

Sensors 2021, 21(23), 7831; https://doi.org/10.3390/s21237831 - 25 Nov 2021

Cited by 12 | Viewed by 2682

Abstract

The integration of geospatial data in hydrography, performed using different measurement systems, involves combining several study results to provide a comprehensive analysis. Each of the hydroacoustic and optoelectronic systems is characterised by a different spatial reference system and the method for technical implementation [...] Read more.

The integration of geospatial data in hydrography, performed using different measurement systems, involves combining several study results to provide a comprehensive analysis. Each of the hydroacoustic and optoelectronic systems is characterised by a different spatial reference system and the method for technical implementation of the measurement. Therefore, the integration of hydrographic data requires that problems in selected fields of electronics, geodesy and physics (acoustics and optics) be solved. The aim of this review is to present selected fusion methods applying the data derived from Global Navigation Satellite System (GNSS), Real Time Kinematic (RTK) measurements, hydrographic surveys, a photogrammetric pass using unmanned vehicles and Terrestrial Laser Scanning (TLS) and compare their accuracy. An additional goal is the evalution of data integration methods according to the International Hydrographic Organization (IHO) S-44 standard. The publication is supplemented by implementation examples of the integration of geospatial data in the Geographic Information System (GIS). The methods described indicate the lack of a uniform methodology for data fusion due to differences in both the spatial reference systems and the techniques used. However, the integration of hydroacoustic and optoelectronic data allows for high accuracy geospatial data to be obtained. This is confirmed by the methods cited, in which the accuracy of integrated geospatial data was in the order of several centimetres. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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49 pages, 4674 KiB

Open AccessReview

Survey of Datafusion Techniques for Laser and Vision Based Sensor Integration for Autonomous Navigation

by Prasanna Kolar, Patrick Benavidez and Mo Jamshidi

Sensors 2020, 20(8), 2180; https://doi.org/10.3390/s20082180 - 12 Apr 2020

Cited by 45 | Viewed by 10895

Abstract

This paper focuses on data fusion, which is fundamental to one of the most important modules in any autonomous system: perception. Over the past decade, there has been a surge in the usage of smart/autonomous mobility systems. Such systems can be used in [...] Read more.

This paper focuses on data fusion, which is fundamental to one of the most important modules in any autonomous system: perception. Over the past decade, there has been a surge in the usage of smart/autonomous mobility systems. Such systems can be used in various areas of life like safe mobility for the disabled, senior citizens, and so on and are dependent on accurate sensor information in order to function optimally. This information may be from a single sensor or a suite of sensors with the same or different modalities. We review various types of sensors, their data, and the need for fusion of the data with each other to output the best data for the task at hand, which in this case is autonomous navigation. In order to obtain such accurate data, we need to have optimal technology to read the sensor data, process the data, eliminate or at least reduce the noise and then use the data for the required tasks. We present a survey of the current data processing techniques that implement data fusion using different sensors like LiDAR that use light scan technology, stereo/depth cameras, Red Green Blue monocular (RGB) and Time-of-flight (TOF) cameras that use optical technology and review the efficiency of using fused data from multiple sensors rather than a single sensor in autonomous navigation tasks like mapping, obstacle detection, and avoidance or localization. This survey will provide sensor information to researchers who intend to accomplish the task of motion control of a robot and detail the use of LiDAR and cameras to accomplish robot navigation. Full article

(This article belongs to the Special Issue Sensors and System for Vehicle Navigation)

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