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 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 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 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 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 Methodology for the Correction of the Spatial Orientation Angles of the Unmanned Aerial Vehicle Using Real Time GNSS, a Shoreline Image and an Electronic Navigational Chart

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2810
Author(s):  
Krzysztof Naus ◽  
Piotr Szymak ◽  
Paweł Piskur ◽  
Maciej Niedziela ◽  
Aleksander Nowak
Keyword(s):  
Real Time ◽  
Spatial Orientation ◽  
Orientation Angle ◽  
Satellite System ◽  
Angle Measurement ◽  
Angle Correction ◽  
Lidar Measurements ◽  
Aerial Vehicle ◽  
Marine Applications ◽  
Global Navigation Satellite

Undoubtedly, Low-Altitude Unmanned Aerial Vehicles (UAVs) are becoming more common in marine applications. Equipped with a Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) receiver for highly accurate positioning, they perform camera and Light Detection and Ranging (LiDAR) measurements. Unfortunately, these measurements may still be subject to large errors-mainly due to the inaccuracy of measurement of the optical axis of the camera or LiDAR sensor. Usually, UAVs use a small and light Inertial Navigation System (INS) with an angle measurement error of up to 0.5∘ (RMSE). The methodology for spatial orientation angle correction presented in the article allows the reduction of this error even to the level of 0.01∘ (RMSE). It can be successfully used in coastal and port waters. To determine the corrections, only the Electronic Navigational Chart (ENC) and an image of the coastline are needed.

scholarly journals Wind Gust Measuring at Low Altitude Using An Unmanned Aerial System

2021 ◽  
Author(s):  
Alton Yeung
Keyword(s):  
Turbulence Models ◽  
Satellite System ◽  
Data System ◽  
Measurement Unit ◽  
Wind Gust ◽  
Wind Gusts ◽  
Low Altitude ◽  
And Performance ◽  
Global Navigation Satellite ◽  
Aerial Platform

A small unmanned aerial vehicle (UAV) was developed with the specific objective to explore atmospheric wind gusts at low altitudes within the atmospheric boundary layer (ABL). These gusts have major impacts on the flight characteristics and performance of modern small unmanned aerial vehicles. Hence, this project was set to investigate the power spectral density of gusts observed at low altitudes by measuring the gusts with an aerial platform. The small UAV carried an air-data system including a fivehole probe that was adapted for this specific application. The air-data system measured the local wind gusts with an accuracy of 0.5 m/s by combining inputs from a five-hole probe, an inertial measurement unit, and Global Navigation Satellite System (GNSS) receivers. Over 20 flights were performed during the development of the aerial platform. Airborne experiments were performed to collect gust data at low altitudes between 50 m and 100 m. The result was processed into turbulence spectrum and the measurements were compared with the MIL-HDBK-1797 von K´arm´an turbulence model and the results have shown the model underpredicted the gust intensities experienced by the flight vehicle. The anisotropic properties of low-altitude turbulence were also observed when analyzing the measured gusts spectra. The wind and gust data collected are useful for verifying the existing turbulence models for low-altitude flights and benefit the future development of small UAVs in windy environment.

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