scholarly journals Steering Angle Assisted Vehicular Navigation Using Portable Devices in GNSS-Denied Environments

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1618 ◽  
Author(s):  
Mohamed Moussa ◽  
Adel Moussa ◽  
Naser El-Sheimy
Keyword(s):  
Low Cost ◽  
Measurement Unit ◽  
Steering Wheel ◽  
Portable Devices ◽  
Steering Angle ◽  
Navigation Solution ◽  
Land Vehicle ◽  
Land Vehicle Navigation ◽  
Novel Approach ◽  
Vehicle Acceleration

Recently, land vehicle navigation, and especially by the use of low-cost sensors, has been the object of a huge level of research interest. Consumer Portable Devices (CPDs) such as tablets and smartphones are being widely used by many consumers all over the world. CPDs contain sensors (accelerometers, gyroscopes, magnetometer, etc.) that can be used for many land vehicle applications such as navigation. This paper presents a novel approach for estimating steering wheel angles using CPD accelerometers by attaching CPDs to the steering wheel. The land vehicle change of heading is then computed from the estimated steering wheel angle. The calculated change of heading is used to update the navigation filter to aid the onboard Inertial Measurement Unit (IMU) through the use of an Extended Kalman Filter (EKF) in GNSS-denied environments. Four main factors that may affect the steering wheel angle accuracy are considered and modeled during steering angle estimations: static onboard IMU leveling, inclination angle of the steering wheel, vehicle acceleration, and vehicle inclination. In addition, these factors are assessed for their effects on the final result. Therefore, three methods are proposed for steering angle estimation: non-compensated, partially-compensated, and fully-compensated methods. A road experimental test was carried out using a Pixhawk (PX4) navigation system, iPad Air, and the OBD-II interface. The average Root Mean Square Error (RMSE) of the change of heading estimated by the proposed method was 0.033 rad/s. A navigation solution was estimated while changes of heading and forward velocity updates were used to aid the IMU during different GNSS signal outages. The estimated navigation solution is enhanced when applying the proposed updates to the navigation filter by 91% and 97% for 60 s and 120 s of GNSS signal outage, respectively, compared to the IMU standalone solution.

scholarly journals INVESTIGATION OF DIFFERENT LOW-COST LAND VEHICLE NAVIGATION SYSTEMS BASED ON CPD SENSORS AND VEHICLE INFORMATION

2020 ◽  
Vol V-1-2020 ◽  
pp. 189-197
Author(s):  
M. Moussa ◽  
A. Moussa ◽  
M. Elhabiby ◽  
N. El-Sheimy
Keyword(s):  
Inertial Sensor ◽  
Low Cost ◽  
Integrated System ◽  
Steering Wheel ◽  
Vehicle Navigation ◽  
Portable Devices ◽  
Navigation Systems ◽  
Land Vehicle ◽  
Land Vehicle Navigation ◽  
Vehicle Information

Abstract. Recently, many companies and research centres have been working on research and development of navigation technologies for self-driving cars. Many navigation technologies were developed based on the fusion of various sensors. However, most of these techniques used expensive sensors and consequently increase the overall cost of such cars. Therefore, low-cost sensors are now a rich research topic in land vehicle navigation. Consumer Portable Devices (CPDs) such as smartphones and tablets are being widely used and contain many sensors (e.g. cameras, barometers, magnetometers, accelerometers, gyroscopes, and GNSS receivers) that can be used in the land vehicle navigation applications.This paper investigates various land vehicle navigation systems based on low-cost self-contained inertial sensors in CPD, vehicle information and on-board sensors with a focus on GNSS denied environment. Vehicle motion information such as forward speed is acquired from On-Board Diagnosis II (OBD-II) while the land vehicle heading change is estimated using CPD attached to the steering wheel. Additionally, a low-cost on-board GNSS/inertial integrated system is also employed. The paper investigates many navigation schemes such as different Dead Reckoning (DR) systems, Reduced Inertial Sensor System (RISS) based systems, and aided loosely coupled GNSS/inertial integrated system.An experimental road test is performed, and different simulated GNSS signal outages were applied to the data. The results show that the modified RISS system based on OBD-II velocity, onboard gyroscopes, accelerometers, and CPD-based heading change provides a better navigation estimation than the typical RISS system for 90s GNSS signal outage. On the other hand, typical inertial aided with CPD heading change, OBD-II velocity updates, and Non-Holonomic Constraint (NHC) provide the best navigation result.

scholarly journals ULTRASONIC BASED HEADING ESTIMATION FOR AIDING LAND VEHICLE NAVIGATION IN GNSS DENIED ENVIRONMENT

2018 ◽  
Vol XLII-1 ◽  
pp. 315-322 ◽  
Author(s):  
M. Moussa ◽  
A. Moussa ◽  
N. El-Sheimy
Keyword(s):  
Low Cost ◽  
Ultrasonic Sensor ◽  
The Body ◽  
Navigation Solution ◽  
Land Vehicles ◽  
Land Vehicle Navigation ◽  
Novel Approach ◽  
Constant Distance ◽  
Heading Estimation ◽  
Wooden Surface

<p><strong>Abstract.</strong> This paper introduces a novel approach for land vehicles navigation in GNSS denied environment by aiding the Inertial Navigation System (INS) with a very low-cost ultrasonic sensor using Extended Kalman Filter (EKF) to bound its drift during GNSS blockage through a heading change update to enhance the navigation estimation.</p><p>The ultrasonic sensor is mounted on the body of the car facing the direction of the car motion and behind the front right wheel, a wooden surface is mounted on the car body on the other side of this wheel with a constant distance between the sensor and this surface. The ultrasonic sensor measures this range as long as the car moving straight. When orientation changes, the ultrasonic sensor senses the range to the front right wheel. The relation between the range and the estimated GNSS/INS change of heading during GNSS availability is estimated through a linear regression model. During GNSS signal outage, the ultrasonic sensor provides heading change update to the INS standalone navigation solution.</p><p>Experimental road tests were performed, and the results show that the navigation states estimation using the proposed aiding is improved compared with INS standalone navigation solution during GNSS signal outage. For multiple GNSS outages of 60<span class="thinspace"></span>seconds, the inclusion of the proposed update reduced the position RMSE to around 80<span class="thinspace"></span>% of its value when using the non-holonomic constraints and velocity update only.</p>

scholarly journals Feasibility Study of Multi Inertial Measurement Unit

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 74 ◽  
Author(s):  
Ariel Larey ◽  
Eliel Aknin ◽  
Itzik Klein
Keyword(s):  
Inertial Measurement Unit ◽  
Inertial Sensors ◽  
Low Cost ◽  
Software Tool ◽  
Experimental Results ◽  
Measurement Unit ◽  
Outlier Rejection ◽  
Inertial Measurement ◽  
Navigation Solution ◽  
Sensory Data

An inertial measurement unit (IMU) typically has three accelerometers and three gyroscopes. The output of those inertial sensors is used by an inertial navigation system to calculate the navigation solution–position, velocity and attitude. Since the sensor measurements contain noise, the navigation solution drifts over time. When considering low cost sensors, multiple IMUs can be used to improve the performance of a single unit. In this paper, we describe our designed 32 multi-IMU (MIMU) architecture and present experimental results using this system. To analyze the sensory data, a dedicated software tool, capable of addressing MIMUs inputs, was developed. Using the MIMU hardware and software tool we examined and evaluated the MIMUs for: (1) navigation solution accuracy (2) sensor outlier rejection (3) stationary calibration performance (4) coarse alignment accuracy and (5) the effect of different MIMUs locations in the architecture. Our experimental results show that 32 IMUs obtained better performance than a single IMU for all testcases examined. In addition, we show that performance was improved gradually as the number of IMUs was increased in the architecture.

scholarly journals Implementation and Analysis of Tightly Coupled Global Navigation Satellite System Precise Point Positioning/Inertial Navigation System (GNSS PPP/INS) with Insufficient Satellites for Land Vehicle Navigation

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4305 ◽  
Author(s):  
Yue Liu ◽  
Fei Liu ◽  
Yang Gao ◽  
Lin Zhao
Keyword(s):  
Low Cost ◽  
Satellite System ◽  
Single Frequency ◽  
Vehicle Navigation ◽  
Land Vehicle ◽  
Land Vehicle Navigation ◽  
Gps Satellites ◽  
Tightly Coupled ◽  
Gnss Measurements ◽  
Global Navigation Satellite

This paper implements and analyzes a tightly coupled single-frequency global navigation satellite system precise point positioning/inertial navigation system (GNSS PPP/INS) with insufficient satellites for land vehicle navigation using a low-cost GNSS receiver and a microelectromechanical system (MEMS)-based inertial measurement unit (IMU). For land vehicle navigation, it is inevitable to encounter the situation where insufficient satellites can be observed. Therefore, it is necessary to analyze the performance of tightly coupled integration in a GNSS-challenging environment. In addition, it is also of importance to investigate the least number of satellites adopted to improve the performance, compared with no satellites used. In this paper, tightly coupled integration using low-cost sensors with insufficient satellites was conducted, which provided a clear view of the improvement of the solution with insufficient satellites compared to no GNSS measurements at all. Specifically, in this paper single-frequency PPP was implemented to achieve the best performance, with one single-frequency receiver. The INS mechanization was conducted in a local-level frame (LLF). An extended Kalman filter was applied to fuse the two different types of measurements. To be more specific, in PPP processing, the atmosphere errors are corrected using a Saastamoinen model and the Center for Orbit Determination in Europe (CODE) global ionosphere map (GIM) product. The residuals of atmosphere errors are not estimated to accelerate the ambiguity convergence. For INS error mitigation, velocity constraints for land vehicle navigation are adopted to limit the quick drift of a MEMS-based IMU. Field tests with simulated partial and full GNSS outages were conducted to show the performance of tightly coupled GNSS PPP/INS with insufficient satellites: The results were classified as long-term (several minutes) and short-term (less than 1 min). The results showed that generally, with GNSS measurements applied, although the number of satellites was not enough, the solution still could be improved, especially with more than three satellites observed. With three GPS satellites used, the horizontal drift could be reduced to a few meters after several minutes. The 3D position error could be limited within 10 m in one minute when three GPS satellites were applied. In addition, a field test in an urban area where insufficient satellites were observed from time to time was also conducted to show the limited solution drift.

GPS-based Land Vehicle Navigation System Assisted by a Low-Cost Gyro-Free INS Using Neural Network

2004 ◽  
Vol 57 (3) ◽  
pp. 417-428 ◽  
Author(s):  
Jau-Hsiung Wang ◽  
Yang Gao
Keyword(s):  
Neural Network ◽  
Navigation System ◽  
Urban Areas ◽  
Low Cost ◽  
Vehicle Navigation ◽  
Navigation Systems ◽  
Land Vehicle ◽  
Land Vehicle Navigation ◽  
Artificial Neural Network Ann ◽  
Signal Fading

GPS-based land vehicle navigation systems are subject to signal fading in urban areas and require aid from other enabling sensors. A low-cost gyro-free inertial navigation system (INS) without accumulated attitude errors and complicated initializations could be an effective solution to the problem. This paper investigates a Constrained Navigation Algorithm (CNA) and the Artificial Neural Network (ANN) technique to compensate velocity output from a gyro-free INS. The vehicle's heading will be calibrated by a full circle test so that the magnetometer's bias and scale factor error could be removed. Experiments with a vehicle driven over level terrain have been conducted to assess the performance of the compensated gyro-free INS solutions. The effect of the architecture of Neural Network on prediction performance has also been discussed as well as the applicability of the proposed solution to land vehicle navigation with GPS outages.

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