Ultrasonic Based Heading Estimation for Aiding Land Vehicle Navigation in GNSS Denied Environment

Moussa, Mohamed; Moussa, Adel; El‐Sheimy, Naser

doi:10.5194/isprs-archives-xlii-1-315-2018

Cited by 8 publications

(6 citation statements)

References 15 publications

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“…Additionally, the execution time for processing raw sensor data (collected over 100 seconds) is 0.58 seconds, demon-strating good real-time performance. Another method with excellent real-time performance was reported in [58]. To further enhance the availability of ultrasonic-based methods in GPS-denied environments, a navigation estimation system is designed.…”

Section: Ultrasonic-based Self-localization Methodsmentioning

confidence: 99%

A Survey of Vehicle Localization: Performance Analysis and Challenges

Shan,

Cabani,

Chafouk

2023

IEEE Access

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Vehicle localization plays a crucial role in ensuring the safe operation of autonomous vehicles and the development of intelligent transportation systems (ITS). However, there is insufficient effort to compare the performance and challenges of different vehicle localization algorithms. This paper aims to address this gap by analyzing the comprehensive performance of existing advanced vehicle localization techniques and discussing their challenges. Firstly, we analyze the self-localization methods based on active and passive sensors. The results show that, the light detection and ranging (LiDAR) and vision-based techniques can reach high accuracy. However, they have high computational complexity. And only using the inertial measurement unit (IMU), global positioning system (GPS), radar, and ultrasonic sensors may not realize localization result with high accuracy. Then, we discuss V2X-based cooperative methods and analyze the multi-sensor based localization techniques and compare the comprehensive performance among all methods. Although the artificial intelligence (AI) techniques can effectively enhance the efficiency of vision-based localization algorithms, the high computational complexity still should be considered. In addition, since the IMU, GPS, radar, and ultrasonic sensors have good performance in terms of the availability, scalability, computational complexity, and cost-effectiveness, they can be used as auxiliary sensors to achieve good comprehensive performance through data fusion techniques. Finally, we propose the challenges of different techniques and look forward to future work.

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Section: Ultrasonic-based Self-localization Methodsmentioning

confidence: 99%

A Survey of Vehicle Localization: Performance Analysis and Challenges

Shan,

Cabani,

Chafouk

2023

IEEE Access

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“…However, short detection distance and sensitivity to environmental temperature, humidity and dust all limit the wide application of ultrasonic sensor in AV positioning [55], [56]. Moussa et al [57] used the EKF algorithm to achieve an ultrasonic-based assisted navigation solution. This solution uses the ultrasonic sensor as the primary sensor for positioning when GPS fails to limit the drift of the vehicle position and enhances the robustness of the system.…”

Section: Ultrasonic-based Localisationmentioning

confidence: 99%

Real-Time Performance-Focused Localization Techniques for Autonomous Vehicle: A Review

Lü

Smart

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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Real-time, accurate, and robust localisation is critical for autonomous vehicles (AVs) to achieve safe, efficient driving, whilst real-time performance is essential for AVs to achieve their current position in time for decision making. To date, no review paper has quantitatively compared the real-time performance between different localisation techniques based on various hardware platforms and programming languages and analysed the relations among localisation methodologies, real-time performance and accuracy. Therefore, this paper discusses the state-of-the-art localisation techniques and analyses their overall performance in AV application. For further analysis, this paper firstly proposes a localisation algorithm operations capability (LAOC)-based equivalent comparison method to compare the relative computational complexity of different localisation techniques; then, it comprehensively discusses the relations among methodologies, computational complexity, and accuracy. Analysis results show that the computational complexity of localisation approaches differs by a maximum of about times, whilst accuracy varies by about 100 times. Vision-and data fusion-based localisation techniques have about 2-5 times potential for improving accuracy compared with lidar-based localisation. Lidar-and vision-based localisation can reduce computational complexity by improving image registration method efficiency. Data fusion-based localisation can achieve better real-time performance compared with lidar-and vision-based localisation because each standalone sensor does not need to develop a complex algorithm to achieve its best localisation potential. Vehicle-toeverything (V2X) technology can improve positioning robustness. Finally, the potential solutions and future orientations of AVs' localisation based on the quantitative comparison results are discussed.

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“…Ultrasonic sensors are typically used for obstacle avoidance [ 22 ] in land vehicles. However, [ 23 ] used the ultrasonic sensor as an aiding sensor by providing velocity and change of heading updates [ 24 ] to the navigation filter. Nevertheless, the sensor installment process and the estimated velocity and the heading change precision are the major drawbacks when using ultrasonic in land vehicle navigation.…”

Section: Introductionmentioning

confidence: 99%

Optical and Mass Flow Sensors for Aiding Vehicle Navigation in GNSS Denied Environment

Moussa

Zahran

Mostafa

et al. 2020

Sensors

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Nowadays, autonomous vehicles have achieved a lot of research interest regarding the navigation, the surrounding environmental perception, and control. Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) is one of the significant components of any vehicle navigation system. However, GNSS has limitations in some operating scenarios such as urban regions and indoor environments where the GNSS signal suffers from multipath or outage. On the other hand, INS standalone navigation solution degrades over time due to the INS errors. Therefore, a modern vehicle navigation system depends on integration between different sensors to aid INS for mitigating its drift during GNSS signal outage. However, there are some challenges for the aiding sensors related to their high price, high computational costs, and environmental and weather effects. This paper proposes an integrated aiding navigation system for vehicles in an indoor environment (e.g., underground parking). This proposed system is based on optical flow and multiple mass flow sensors integrations to aid the low-cost INS by providing the navigation extended Kalman filter (EKF) with forward velocity and change of heading updates to enhance the vehicle navigation. The optical flow is computed for frames taken using a consumer portable device (CPD) camera mounted in the upward-looking direction to avoid moving objects in front of the camera and to exploit the typical features of the underground parking or tunnels such as ducts and pipes. On the other hand, the multiple mass flow sensors measurements are modeled to provide forward velocity information. Moreover, a mass flow differential odometry is proposed where the vehicle change of heading is estimated from the multiple mass flow sensors measurements. This integrated aiding system can be used for unmanned aerial vehicles (UAV) and land vehicle navigations. However, the experimental results are implemented for land vehicles through the integration of CPD with mass flow sensors to aid the navigation system.

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Ultrasonic Based Heading Estimation for Aiding Land Vehicle Navigation in GNSS Denied Environment

Cited by 8 publications

References 15 publications

A Survey of Vehicle Localization: Performance Analysis and Challenges

A Survey of Vehicle Localization: Performance Analysis and Challenges

Real-Time Performance-Focused Localization Techniques for Autonomous Vehicle: A Review

Optical and Mass Flow Sensors for Aiding Vehicle Navigation in GNSS Denied Environment

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