scholarly journals Performance Analysis of GNSS/INS Loosely Coupled Integration Systems under Spoofing Attacks

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4108 ◽  
Author(s):  
Rui Xu ◽  
Mengyu Ding ◽  
Ya Qi ◽  
Shuai Yue ◽  
Jianye Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Detection Method ◽  
Satellite System ◽  
Measurement Unit ◽  
Integration System ◽  
Loosely Coupled ◽  
Integration Algorithms ◽  
Gnss Measurements ◽  
Global Navigation Satellite ◽  
Physical Features

The loosely coupled integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) have been widely used to improve the accuracy, robustness and continuity of navigation services. However, the integration systems possibly affected by spoofing attacks, since integration algorithms without spoofing detection would feed autonomous INSs with incorrect compensations from the spoofed GNSSs. This paper theoretically analyzes and tests the performances of GNSS/INS loosely coupled integration systems with the classical position fusion and position/velocity fusion under typical meaconing (MEAC) and lift-of-aligned (LOA) spoofing attacks. Results show that the compensations of Inertial Measurement Unit (IMU) errors significantly increase under spoofing attacks. The compensations refer to the physical features of IMUs and their unreasonable increments likely result from the spoofing-induced inconsistency of INS and GNSS measurements. Specially, under MEAC attacks, the IMU error compensations in both the position-fusion-based system and position/velocity-fusion-based system increase obviously. Under LOA attacks, the unreasonable compensation increments are found from the position/velocity-fusion-based integration system. Then a detection method based on IMU error compensations is tested and the results show that, for the position/velocity-fusion-based integration system, it can detect both MEAC and LOA attacks with high probability using the IMU error compensations.

scholarly journals Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment

2019 ◽  
Vol 11 (4) ◽  
pp. 442 ◽  
Author(s):  
Zhen Li ◽  
Junxiang Tan ◽  
Hua Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Point Clouds ◽  
Calibration Method ◽  
Satellite System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Self Calibration ◽  
Global Navigation Satellite ◽  
Mean Square Errors ◽  
Scanning Systems

Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.

scholarly journals ADAPTIVE STRATEGY-BASED TIGHTLY-COUPLED INS/GNSS INTEGRATION SYSTEM AIDED BY ODOMETER AND BAROMETER

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 881-888 ◽  
Author(s):  
Y. C. Tien ◽  
Y. L. Chen ◽  
K. W. Chiang
Keyword(s):  
Experimental Validation ◽  
Fundamental System ◽  
Adaptive Strategy ◽  
Measurement Model ◽  
Satellite System ◽  
Integration System ◽  
Loosely Coupled ◽  
Navigation Algorithm ◽  
Tightly Coupled ◽  
Global Navigation Satellite

<p><strong>Abstract.</strong> Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) integration system have been widely applied in recent years. Unfortunately, it sometimes malfunctions and the performance heavily deteriorates, especially in urban area where signals from satellites may be blocked or reflected by modern buildings. In multipath or Non Light-of-sight (NLOS) environment, incorrect signal results in poor observability of GNSS measurement model in Kalman Filter (KF). For purpose of addressing the issue, we proposed an adaptive strategy-based tightly-coupled INS/GNSS integration system aided by odometer and barometer, targeting to mitigate the error from poor observability. In this method, tightly-coupled (TC) scheme is implemented as the fundamental system in order to increase the reliability and stability. TC is more suitable than Loosely-coupled (LC), the traditional scheme, in urban navigation because it requires less visible GNSS measurement and it overcomes the disadvantage of LC, and further enhances the navigation result. Furthermore, aiding sensors such as odometer and barometer are integrated in this system as well, serving as velocity and height constraints respectively. Since the precision of GNSS positioning depends on the properties of the environment, measurement model of KF must work adaptively. Thus, innovation-based Adaptive Scaled Estimation (IASE) and Residual-based Adaptive Scaled Estimation (RASE), are also implemented to improve navigation performance in this paper. Finally, from the experimental validation, the proposed adaptive sensor-fusion navigation algorithm significantly enhanced the performance. The improvement was approximate 80% compared with the pure TC scheme; the RMSE can reach 6m in 3D and 2.5&amp;thinsp;m in vertical.</p>

scholarly journals Feasibility of Mobile Laser Scanning towards Operational Accurate Road Rut Depth Measurements

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1180
Author(s):  
Aimad El Issaoui ◽  
Ziyi Feng ◽  
Matti Lehtomäki ◽  
Eric Hyyppä ◽  
Hannu Hyyppä ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Laser Scanning ◽  
Satellite System ◽  
Measurement Unit ◽  
High Definition ◽  
Depth Measurement ◽  
Laser Scanners ◽  
Fully Automatic ◽  
Global Navigation Satellite ◽  
Automatic Algorithm

This paper studied the applicability of the Roamer-R4DW mobile laser scanning (MLS) system for road rut depth measurement. The MLS system was developed by the Finnish Geospatial Research Institute (FGI), and consists of two mobile laser scanners and a Global Navigation Satellite System (GNSS)-inertial measurement unit (IMU) positioning system. In the study, a fully automatic algorithm was developed to calculate and analyze the rut depths, and verified in 64 reference pavement plots (1.0 m × 3.5 m). We showed that terrestrial laser scanning (TLS) data is an adequate reference for MLS-based rutting studies. The MLS-derived rut depths based on 64 plots resulted in 1.4 mm random error, which can be considered adequate precision for operational rutting depth measurements. Such data, also covering the area outside the pavement, would be ideal for multiple road environment applications since the same data can also be used in applications, from high-definition maps to autonomous car navigation and digitalization of street environments over time and in space.

scholarly journals Sensitivity to Time Delays in VDM-Based Navigation

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 11 ◽  
Author(s):  
Gabriel Laupré ◽  
Mehran Khaghani ◽  
Jan Skaloud
Keyword(s):  
Time Delays ◽  
Inertial Measurement Unit ◽  
Time Frame ◽  
Satellite System ◽  
Measurement Unit ◽  
Control Input ◽  
Aerial Vehicle ◽  
Aerial Platforms ◽  
Global Navigation Satellite ◽  
Vehicle Dynamic Model

A recently proposed navigation methodology for aerial platforms based on the vehicle dynamic model (VDM) has shown promising results in terms of navigation autonomy. Its practical realization requires that control inputs are related to the same absolute time frame as inertial measurement unit (IMU) data and all other observations when available (e.g., global navigation satellite system (GNSS) position, barometric altitude, etc.). This study analyzes the (non-) tolerances of possible delays in control-input command with respect to navigation performance on a fixed-wing unmanned aerial vehicle (UAV). Multiple simulations using two emulated trajectories based on real flights reveal the vital importance of correct time-tagging of servo data while that of motor data turned out to be tolerable to a considerably large extent.

scholarly journals IMU Signal Generator Based on Dual Quaternion Interpolation for Integration Simulation

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2721 ◽  
Author(s):  
Ke Liu ◽  
Wenqi Wu ◽  
Kanghua Tang ◽  
Lei He
Keyword(s):  
Inertial Measurement Unit ◽  
Satellite System ◽  
Measurement Unit ◽  
Dual Quaternion ◽  
Integration Algorithm ◽  
Analytic Integration ◽  
Quaternion Interpolation ◽  
Update Rate ◽  
Global Navigation Satellite ◽  
Analytical Expressions

This paper focuses on the problem of high-update-rate and high accuracy inertial measurement unit signal generation. In order to be in accordance with the vehicle’s kinematic and dynamic characteristics as well as the characteristics of pseudorange of post-processed global navigation satellite system and their rate measurements, a novel dual quaternion interpolation and analytic integration algorithm based on actual flight data is proposed. The proposed method can simplify the piecewise analytical expressions of angular rates, angular increments and specific force integral increments. Norm corrections are adopted as constraint conditions to guarantee the accuracy of the signals. Numerical simulations are conducted to validate the method’s performance.

scholarly journals A New Triple Filtering Algorithm and Its Application for Aerial GNSS/INS-Integrated Direct Georeferencing System

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qusen Chen ◽  
Leilei Li ◽  
Keyi Xu ◽  
Xiangdong An ◽  
Yu Wu
Keyword(s):  
Inertial Measurement Unit ◽  
Satellite System ◽  
Integrated System ◽  
Measurement Unit ◽  
Strong Nonlinearity ◽  
Filtering Algorithm ◽  
Stochastic Error ◽  
Aerial Photogrammetry ◽  
High Dynamic ◽  
Global Navigation Satellite

A global navigation satellite system and inertial navigation system- (GNSS/INS-) integrated system is employed to provide direct georeferencing (DG) in aerial photogrammetry. However, GNSS/INS suffers from stochastic error, strong nonlinearity, and weak observability problems in high dynamic or less maneuver scenarios. In this paper, we proposed a new triple filtering algorithm for aerial GNSS/INS integration. The new algorithm implements filtering in the sequence of forward, backward, and forward directions. Each filter is initialized by a previous filter to get a quick convergence, and the final result is combination of the last two filtering to smooth error. The proposed triple filtering strategy avoids inaccuracy in the 1st forward filtering when the system has not reached convergence. Moreover, it facilitates engineering implementation because backward filtering can employ the same equations with forward filtering. To assess stochastic error of the inertial measurement unit, the Allan variance method is used and abbreviated stochastic model is built. A real aerial testing is conducted, and the result indicates that DG can achieve horizontal accuracy of 5 cm by the proposed algorithm, which has 63% improvement compared to standard extended Kalman filter.

scholarly journals Radar and Visual Odometry Integrated System Aided Navigation for UAVS in GNSS Denied Environment

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2776 ◽  
Author(s):  
Mostafa Mostafa ◽  
Shady Zahran ◽  
Adel Moussa ◽  
Naser El-Sheimy ◽  
Abu Sesay
Keyword(s):  
Navigation System ◽  
Visual Odometry ◽  
Satellite System ◽  
Integrated System ◽  
Measurement Unit ◽  
Integrated Navigation ◽  
Positioning Accuracy ◽  
Integrated Navigation System ◽  
Gnss Measurements ◽  
Global Navigation Satellite

Drones are becoming increasingly significant for vast applications, such as firefighting, and rescue. While flying in challenging environments, reliable Global Navigation Satellite System (GNSS) measurements cannot be guaranteed all the time, and the Inertial Navigation System (INS) navigation solution will deteriorate dramatically. Although different aiding sensors, such as cameras, are proposed to reduce the effect of these drift errors, the positioning accuracy by using these techniques is still affected by some challenges, such as the lack of the observed features, inconsistent matches, illumination, and environmental conditions. This paper presents an integrated navigation system for Unmanned Aerial Vehicles (UAVs) in GNSS denied environments based on a Radar Odometry (RO) and an enhanced Visual Odometry (VO) to handle such challenges since the radar is immune against these issues. The estimated forward velocities of a vehicle from both the RO and the enhanced VO are fused with the Inertial Measurement Unit (IMU), barometer, and magnetometer measurements via an Extended Kalman Filter (EKF) to enhance the navigation accuracy during GNSS signal outages. The RO and VO are integrated into one integrated system to help overcome their limitations, since the RO measurements are affected while flying over non-flat terrain. Therefore, the integration of the VO is important in such scenarios. The experimental results demonstrate the proposed system’s ability to significantly enhance the 3D positioning accuracy during the GNSS signal outage.

scholarly journals Inventory of Locations of Old Mining Works Using LiDAR Data: A Case Study in Slovakia

2021 ◽  
Vol 13 (12) ◽  
pp. 6981
Author(s):  
Marcela Bindzarova Gergelova ◽  
Slavomir Labant ◽  
Jozef Mizak ◽  
Pavel Sustek ◽  
Lubomir Leicher
Keyword(s):  
Satellite System ◽  
Precise Determination ◽  
Lidar Data ◽  
Positional Accuracy ◽  
Current Form ◽  
Mining History ◽  
Mining Works ◽  
Gnss Measurements ◽  
Global Navigation Satellite

The concept of further sustainable development in the area of administration of the register of old mining works and recent mining works in Slovakia requires precise determination of the locations of the objects that constitute it. The objects in this register have their uniqueness linked with the history of mining in Slovakia. The state of positional accuracy in the registration of objects in its current form is unsatisfactory. Different database sources containing the locations of the old mining works are insufficient and show significant locational deviations. For this reason, it is necessary to precisely locate old mining works using modern measuring technologies. The most effective approach to solving this problem is the use of LiDAR data, which at the same time allow determining the position and above-ground shape of old mining works. Two localities with significant mining history were selected for this case study. Positional deviations in the location of old mining works among the selected data were determined from the register of old mining works in Slovakia, global navigation satellite system (GNSS) measurements, multidirectional hill-shading using LiDAR, and accessible data from the open street map. To compare the positions of identical old mining works from the selected database sources, we established differences in the coordinates (ΔX, ΔY) and calculated the positional deviations of the same objects. The average positional deviation in the total count of nineteen objects comparing documents, LiDAR data, and the register was 33.6 m. Comparing the locations of twelve old mining works between the LiDAR data and the open street map, the average positional deviation was 16.3 m. Between the data sources from GNSS and the registry of old mining works, the average positional deviation of four selected objects was 39.17 m.

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