scholarly journals A cross product calibration method for micro-electro mechanical system gyroscope in unmanned aerial vehicle attitude determination system

2020 ◽  
pp. 002029402094494
Author(s):  
Yongjun Wang ◽  
Zhi Li ◽  
Xiang Li
Keyword(s):  
Mechanical System ◽  
Unmanned Aerial Vehicle ◽  
Attitude Determination ◽  
Low Cost ◽  
Integral Form ◽  
Calibration Method ◽  
Micro Electro Mechanical System ◽  
Cross Product ◽  
Integrated Navigation ◽  
Aerial Vehicle

This paper presents a novel calibration method for micro-electro mechanical system gyroscope in attitude measurement system of small rotor unmanned aerial vehicles. This method is based on an observation vector and its cross product, which is especially valuable for the in-field calibration without the aid of external equipment. By analysing the error model of the tri-axial gyroscope, the principle of calibration is proposed. Compared with other algorithms, numerical simulations are performed to evaluate the effectiveness of integral form of the cross product calibration method. Experiment on the hex-rotor unmanned aerial vehicle platform shows that the proposed method has great advantages in low-cost integrated navigation system.

A Reliable Multi-Sensor Navigation System for an Unmanned Aerial Vehicle Realized through Integration of SINS with GPS, CNS and Doppler Radar

2013 ◽  
Vol 392 ◽  
pp. 312-318 ◽  
Author(s):  
Muhammad Ushaq ◽  
Fang Jian Cheng
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Navigation System ◽  
Doppler Radar ◽  
Low Cost ◽  
Inertial Navigation ◽  
Traffic Monitoring ◽  
Integrated Navigation ◽  
Low Weight ◽  
Aerial Vehicle ◽  
Local Filters

Contemporary importance of the unmanned aerial vehicle (UAV) both for military and civilian applications has prompted vigorous research related with guidance, navigation and control of these vehicles. The potential civilian uses for small low-cost UAVs are various like reconnaissance, surveillance, rescue and search, remote sensing, traffic monitoring, destruction appraisal of natural disasters, etc. One of the most crucial parts of UAVs missions is accurate navigation of the vehicle, i.e. the real time determination of its position, velocity and attitude. Generally highly accurate Strap down Inertial Navigation Systems (SINS) are too heavy to be flown on UAVs. Moreover highly accurate SINS are also highly expensive. Therefore the low-cost and low weight MEMS based SINS with a compromised precision are the viable option for navigation of UAVs. The errors in position, velocity, and attitude solutions provided by the MEMS based SINS grow unboundedly with the passage of time. To contain these growing errors, integrated navigation is the resolution. Complementary characteristics SINS and external non-inertial navigation aids like Global Positioning System (GPS), Celestial Navigation System (CNS) and Doppler radar make the integrated navigation system an appealing and cost effective solution. The non-inertial sensors providing navigation fixes must have low weight and volume to be suitable for UAV application. In this research work GPS, CNS and Doppler radar are used as external navigation aids for SINS. The navigation solutions of all contributing systems are fused using Federated Kalman Filter (FKF). Three local filters are employed for SINS/GPS, SINS/CNS and SINS/Doppler integration and subsequently information from all three local filters is fused to acquire a global solution. Moreover adaptive and fault tolerant filtering scheme has also been implemented in each local filter to isolate or accommodate any undesirable error or noise. Simulation for the presented architecture has validated the effectiveness of the scheme, by showing a substantial precision improvement in the solutions of position, velocity and attitude.

Design of a low-cost attitude determination GPS/INS integrated navigation system

GPS Solutions ◽  
2005 ◽  
Vol 9 (4) ◽  
pp. 294-311 ◽  
Author(s):  
Dong-Hwan Hwang ◽  
Sang Heon Oh ◽  
Sang Jeong Lee ◽  
Chansik Park ◽  
Chris Rizos
Keyword(s):  
Navigation System ◽  
Attitude Determination ◽  
Low Cost ◽  
Integrated Navigation ◽  
Integrated Navigation System

Calibration of a micro-electro mechanical system-based accelerometer for vehicle navigation

2018 ◽  
Vol 233 (2) ◽  
pp. 554-560 ◽  
Author(s):  
A Ghaffari ◽  
A Khodayari ◽  
S Nosoudi ◽  
S Arefnezhad
Keyword(s):  
Mechanical System ◽  
Clustering Algorithm ◽  
Moving Objects ◽  
Inertial Sensors ◽  
Low Cost ◽  
Micro Electro Mechanical System ◽  
Subtractive Clustering ◽  
Measured Velocity ◽  
Preliminary Model ◽  
Dynamic Errors

Micro-electro mechanical system-based inertial sensors have broad applications in moving objects including in vehicles for navigation purposes. The low-cost micro-electro mechanical system sensors are normally subject to high dynamic errors such as linear or nonlinear bias, misalignment errors and random noises. In the class of low cost sensors, keeping the accuracy at a reasonable range has always been challenging for engineers. In this paper, a novel method for calibrating low-cost micro-electro mechanical system accelerometers is presented based on soft computing approaches. The method consists of two steps. In the first step, a preliminary model for error sources is presented based on fuzzy subtractive clustering algorithm. This model is then improved using adaptive neuro-fuzzy systems. A Kalman filter is also used to calculate the vehicle velocity and its position based on calibrated measured acceleration. The performance of the presented approach has been validated in the simulated and real experimental driving scenarios. The results show that this method can improve the accuracy of the accelerometer output, measured velocity and position of the vehicle by 79.11%, 97.63% and 99.28%, in the experimental test, respectively. The presented procedure can be used in collision avoidance and emergency brake assist systems.

scholarly journals Suitability of a Non-Dispersive Infrared Methane Sensor Package for Flux Quantification Using an Unmanned Aerial Vehicle

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4705 ◽  
Author(s):  
Adil Shah ◽  
Joseph Pitt ◽  
Khristopher Kabbabe ◽  
Grant Allen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Mole Fraction ◽  
Low Cost ◽  
Methane Flux ◽  
Gain Factor ◽  
Measured Signal ◽  
Allan Deviation ◽  
Methane Sensor ◽  
Aerial Vehicle ◽  
Flux Quantification

Point-source methane emission flux quantification is required to help constrain the global methane budget. Facility-scale fluxes can be derived using in situ methane mole fraction sampling, near-to-source, which may be acquired from an unmanned aerial vehicle (UAV) platform. We test a new non-dispersive infrared methane sensor by mounting it onto a small UAV, which flew downwind of a controlled methane release. Nine UAV flight surveys were conducted on a downwind vertical sampling plane, perpendicular to mean wind direction. The sensor was first packaged in an enclosure prior to sampling which contained a pump and a recording computer, with a total mass of 1.0 kg. The packaged sensor was then characterised to derive a gain factor of 0.92 ± 0.07, independent of water mole fraction, and an Allan deviation precision (at 1 Hz) of ±1.16 ppm. This poor instrumental precision and possible short-term drifts made it non-trivial to define a background mole fraction during UAV surveys, which may be important where any measured signal is small compared to sources of instrumental uncertainty and drift. This rendered the sensor incapable of deriving a meaningful flux from UAV sampling for emissions of the order of 1 g s−1. Nevertheless, the sensor may indeed be useful when sampling mole fraction enhancements of the order of at least 10 ppm (an order of magnitude above the 1 Hz Allan deviation), either from stationary ground-based sampling (in baseline studies) or from mobile sampling downwind of sources with greater source flux than those observed in this study. While many methods utilising low-cost sensors to determine methane flux are being developed, this study highlights the importance of adequately characterising and testing all new sensors before they are used in scientific research.

scholarly journals Simulation of UAV Systems

10.14311/754 ◽  
2005 ◽  
Vol 45 (4) ◽  
Author(s):  
P. Kaňovský ◽  
L. Smrcek ◽  
C. Goodchild
Keyword(s):  
Dynamical System ◽  
Unmanned Aerial Vehicle ◽  
Low Cost ◽  
Design Tool ◽  
Inertial System ◽  
Principal Function ◽  
Low Weight ◽  
High Bandwidth ◽  
Aerial Vehicle ◽  
Selection Of

The study described in this paper deals with the issue of a design tool for the autopilot of an Unmanned Aerial Vehicle (UAV) and the selection of the airdata and inertial system sensors. This project was processed in cooperation with VTUL a PVO o.z. [1]. The feature that distinguishes the autopilot requirements of a UAV (Figs. 1, 7, 8) from the flight systems of conventional manned aircraft is the paradox of controlling a high bandwidth dynamical system using sensors that are in harmony with the low cost low weight objectives that UAV designs are often expected to achieve. The principal function of the autopilot is flight stability, which establishes the UAV as a stable airborne platform that can operate at a precisely defined height. The main sensor for providing this height information is a barometric altimeter. The solution to the UAV autopilot design was realised with simulations using the facilities of Matlab® and in particular Simulink®[2]. 

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