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 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 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 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 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 Compressed pseudo-SLAM: pseudorange-integrated compressed simultaneous localisation and mapping for unmanned aerial vehicle navigation

2021 ◽  
pp. 1-13
Author(s):  
Jonghyuk Kim ◽  
Jose Guivant ◽  
Martin L. Sollie ◽  
Torleiv H. Bryne ◽  
Tor Arne Johansen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Computational Cost ◽  
Satellite System ◽  
Measurement Unit ◽  
Electronic Systems ◽  
Computationally Efficient ◽  
Global Correlation ◽  
Aerial Vehicle ◽  
Correlation Information ◽  
Global Navigation Satellite

Abstract This paper addresses the fusion of the pseudorange/pseudorange rate observations from the global navigation satellite system and the inertial–visual simultaneous localisation and mapping (SLAM) to achieve reliable navigation of unmanned aerial vehicles. This work extends the previous work on a simulation-based study [Kim et al. (2017). Compressed fusion of GNSS and inertial navigation with simultaneous localisation and mapping. IEEE Aerospace and Electronic Systems Magazine, 32(8), 22–36] to a real-flight dataset collected from a fixed-wing unmanned aerial vehicle platform. The dataset consists of measurements from visual landmarks, an inertial measurement unit, and pseudorange and pseudorange rates. We propose a novel all-source navigation filter, termed a compressed pseudo-SLAM, which can seamlessly integrate all available information in a computationally efficient way. In this framework, a local map is dynamically defined around the vehicle, updating the vehicle and local landmark states within the region. A global map includes the rest of the landmarks and is updated at a much lower rate by accumulating (or compressing) the local-to-global correlation information within the filter. It will show that the horizontal navigation error is effectively constrained with one satellite vehicle and one landmark observation. The computational cost will be analysed, demonstrating the efficiency of the method.

scholarly journals A Novel Monitoring Navigation Method for Cold Atom Interference Gyroscope

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 222 ◽  
Author(s):  
Lin Zhang ◽  
Wei Gao ◽  
Qian Li ◽  
Runbing Li ◽  
Zhanwei Yao ◽  
...  
Keyword(s):  
Navigation System ◽  
Inertial Measurement Unit ◽  
Cold Atom ◽  
Measurement Unit ◽  
Simulation Test ◽  
Filtering Technique ◽  
High Dynamic ◽  
Novel Design ◽  
Navigation Method

The implementation principle of a typical three-pulse cold atom interference gyroscope is introduced in this paper. Based on its configuration and current research status, the problems of cold atom interference gyro are pointed out. The data-rate is insufficient, and it is difficult to achieve high dynamic measurement. Then, based on these two limitations, a novel design of the monitoring navigation system of the cold atom interference gyroscope (CAIG) and an intermediate-grade inertial measurement unit (IMU) was proposed to obtain the long-term position result without GPS signals, such as the Inertial Navigation System (INS) in underwater vehicles. While the CAIG was used as the external gyro, the bias of IMU and the misalignment angle between the CAIG-frame and the IMU-frame are obtained through filtering technique. The simulation test and field test demonstrated the improvements of the long-term positioning accuracy of the INS.

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