Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "MEMS Inertial Measurement Unit" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Low-cost navigation and guidance systems for Unmanned Aerial Vehicles. Part 1: Vision-based and integrated sensors
Autorzy:
Sabatini, R.
Bartel, C.
Kaharkar, A.
Shaid, T.
Rodriguez, L.
Zammit-Mangion, D.
Jia, H.
Powiązania:
https://bibliotekanauki.pl/articles/320426.pdf
Data publikacji:
2012
Wydawca:
Polskie Forum Nawigacyjne
Tematy:
Vision-Based Navigation
integrated navigation system
MEMS Inertial Measurement Unit
unmanned aerial vehicle
Low-cost Navigation Sensors
Opis:
In this paper we present a new low-cost navigation system designed for small size Unmanned Aerial Vehicles (UAVs) based on Vision-Based Navigation (VBN) and other avionics sensors. The main objective of our research was to design a compact, light and relatively inexpensive system capable of providing the Required Navigation Performance (RNP) in all phases of flight of a small UAV, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensor integrated architecture. Various existing techniques for VBN were compared and the Appearance-Based Approach (ABA) was selected for implementation. Feature extraction and optical flow techniques were employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and body rates. Additionally, we addressed the possible synergies between VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors, as well as the aiding from Aircraft Dynamics Models (ADMs). In particular, by employing these sensors/models, we aimed to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) was developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UAV platform in real-time. Two different integrated navigation system architectures were implemented. The first used VBN at 20 Hz and GPS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also included the ADM (computations performed at 100 Hz) to provide augmentation of the attitude channel. Simulation of these two modes was accomplished in a significant portion of the AEROSONDE UAV operational flight envelope and performing a variety of representative manoeuvres (i.e., straight climb, level turning, turning descent and climb, straight descent, etc.). Simulation of the first integrated navigation system architecture (VBN/IMU/GPS) showed that the integrated system can reach position, velocity and attitude accuracies compatible with CAT-II precision approach requirements. Simulation of the second system architecture (VBN/IMU/GPS/ADM) also showed promising results since the achieved attitude accuracy was higher using the ADM/VBS/IMU than using VBS/IMU only. However, due to rapid divergence of the ADM virtual sensor, there was a need for frequent re-initialisation of the ADM data module, which was strongly dependent on the UAV flight dynamics and the specific manoeuvring transitions performed.
Źródło:
Annual of Navigation; 2012, No. 19, part 2; 71-98
1640-8632
Pojawia się w:
Annual of Navigation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Efficiency of MEMS inertial sensors used in low-dynamics application
Autorzy:
Szumski, A.
Eissfeller, B.
Powiązania:
https://bibliotekanauki.pl/articles/117053.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
Positioning, Navigation and Timing (PNT)
Fiber Optic Gyroscopes (FOG)
Microelectromechanical Systems (MEMS)
gyrocompassing
Inertial Measurement Unit (IMU)
inertial systems
Inertial Navigation Systems (INS)
Allan standard deviation
Opis:
The analysis presents the performance of navigation application driven with MEMS and FOG inertial sensors. The inertial sensors were working under conditions simulating a potential robotic mission, which reduce accuracy of some of the navigation applications. Empirical results of the test confirm degradation of the navigation system performance in the presented demanding mission. Influence of the testing conditions and of the inertial sensor technology is presented and discussed in the paper.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2017, 11, 2; 221-226
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Data Integration from GPS and Inertial Navigation Systems for Pedestrians in Urban Area
Autorzy:
Bikonis, K.
Demkowicz, J.
Powiązania:
https://bibliotekanauki.pl/articles/115987.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
Inertial Measurement Unit (IMU)
Urban Area
inertial navigation system (INS)
Global Positioning System GPS
extended Kalman filter (EKF)
pedestrian trajectory
Micro Electro Mechanical Systems (MEMS)
Integration of Navigation
Opis:
The GPS system is widely used in navigation and the GPS receiver can offer long-term stable absolute positioning information. The overall system performance depends largely on the signal environments. The position obtained from GPS is often degraded due to obstruction and multipath effect caused by buildings, city infrastructure and vegetation, whereas, the current performance achieved by inertial navigation systems (INS) is still relatively poor due to the large inertial sensor errors. The complementary features of GPS and INS are the main reasons why integrated GPS/INS systems are becoming increasingly popular. GPS/INS systems offer a high data rate, high accuracy position and orientation that can work in all environments, particularly those where satellite availability is restricted. In the paper integration algorithm of GPS and INS systems data for pedestrians in urban area is presented. For data integration an Extended Kalman Filter (EKF) algorithm is proposed. Complementary characteristics of GPS and INS with EKF can overcome the problem of huge INS drifts, GPS outages, dense multipath effect and other individual problems associated with these sensors.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2013, 7, 3; 401-406
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies