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Pregled bibliografske jedinice broj: 523435

Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS


Hrgetić, Mario; Deur, Joško; Pavković, Danijel; Barber, Phil
Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS // Proceedings of 2011 SAE International Congress and Exposition
Detroit (MI), 2011. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 523435 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS

Autori
Hrgetić, Mario ; Deur, Joško ; Pavković, Danijel ; Barber, Phil

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of 2011 SAE International Congress and Exposition / - Detroit (MI), 2011

Skup
SAE 2011 International Congress and Exposition

Mjesto i datum
Detroit (MI), Sjedinjene Američke Države, 12.04.2011. - 14.04.2011

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
sideslip; estimation; GPS; inertial; sensor fussion; Kalman filter

Sažetak
This paper presents an adaptive extended Kalman filter(EKF)-based sideslip angle estimator, which utilizes a sensor fusion concept that combines the high-rate inertial sensors measurements with the low-rate GPS velocity measurements. The sideslip angle estimation is based on a vehicle kinematic model relying on the lateral accelerometer and yaw rate gyro measurements. The vehicle velocity measurements from lowcost, single antenna GPS receiver are used for compensation of potentially large drift-like estimation errors caused by inertial sensors offsets. Adaptation of EKF state covariance matrix ensures a fast convergence of inertial sensors offsets estimates, and consequently a more accurate sideslip angle estimate. By using a detailed simulation analysis, it is found out that the main sources of estimation errors include inaccuracies of pre-estimated vehicle longitudinal velocity obtained from nondriven wheel speed sensors, the GPS velocity signal latency, and the road bank-related disturbances. Several compensation methods are proposed to suppress the influence of these errors.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Strojarstvo



POVEZANOST RADA


Projekti:
120-0361621-1896 - MODELIRANJE I UPRAVLJANJE HIBRIDNIM VOZILIMA (Petrić, Joško, MZOS ) ( CroRIS)
120-1201773-1771 - Regulacija i estimacija dinamike vozila (Deur, Joško, MZOS ) ( CroRIS)

Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb

Profili:

Avatar Url Mario Hrgetić (autor)

Avatar Url Joško Deur (autor)

Avatar Url Danijel Pavković (autor)


Citiraj ovu publikaciju:

Hrgetić, Mario; Deur, Joško; Pavković, Danijel; Barber, Phil
Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS // Proceedings of 2011 SAE International Congress and Exposition
Detroit (MI), 2011. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Hrgetić, M., Deur, J., Pavković, D. & Barber, P. (2011) Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS. U: Proceedings of 2011 SAE International Congress and Exposition.
@article{article, author = {Hrgeti\'{c}, Mario and Deur, Jo\v{s}ko and Pavkovi\'{c}, Danijel and Barber, Phil}, year = {2011}, keywords = {sideslip, estimation, GPS, inertial, sensor fussion, Kalman filter}, title = {Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS}, keyword = {sideslip, estimation, GPS, inertial, sensor fussion, Kalman filter}, publisherplace = {Detroit (MI), Sjedinjene Ameri\v{c}ke Dr\v{z}ave} }
@article{article, author = {Hrgeti\'{c}, Mario and Deur, Jo\v{s}ko and Pavkovi\'{c}, Danijel and Barber, Phil}, year = {2011}, keywords = {sideslip, estimation, GPS, inertial, sensor fussion, Kalman filter}, title = {Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS}, keyword = {sideslip, estimation, GPS, inertial, sensor fussion, Kalman filter}, publisherplace = {Detroit (MI), Sjedinjene Ameri\v{c}ke Dr\v{z}ave} }




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