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Wyszukujesz frazę "robust positioning" wg kryterium: Temat


Wyświetlanie 1-5 z 5
Tytuł:
A cooperative positioning algorithm for DSRC enabled vehicular networks
Autorzy:
Efatmaneshnik, M.
Kealy, A.
Alam, N.
Dempster, A.
Powiązania:
https://bibliotekanauki.pl/articles/129825.pdf
Data publikacji:
2011
Wydawca:
Stowarzyszenie Geodetów Polskich
Tematy:
DSRC
Vanet
cooperative positioning
ranging
time of arrival
CRLB
Kalman filtering
robust positioning
pozycjonowanie
godzina przyjazdu
filtracja Kalmana
Opis:
Many of the safety related applications that can be facilitated by Dedicated Short Range Communications (DSRC), such as vehicle proximity warnings, automated braking (e.g. at level crossings), speed advisories, pedestrian alerts etc., rely on a robust vehicle positioning capability such as that provided by a Global Navigation Satellite System (GNSS). Vehicles in remote areas, entering tunnels, high rise areas or any high multipath/ weak signal environment will challenge the integrity of GNSS position solutions, and ultimately the safety application it underpins. To address this challenge, this paper presents an innovative application of Cooperative Positioning techniques within vehicular networks. CP refers to any method of integrating measurements from different positioning systems and sensors in order to improve the overall quality (accuracy and reliability) of the final position solution. This paper investigates the potential of the DSRC infrastructure itself to provide an intervehicular ranging signal that can be used as a measurement within the CP algorithm. In this paper, time-based techniques of ranging are introduced and bandwidth requirements are investigated and presented. The robustness of the CP algorithm to inter-vehicle connection failure as well as GNSS dropouts is also demonstrated using simulation studies. Finally, the performance of the Constrained Kalman Filter used to integrate GNSS measurements with DSRC derived range estimates within a typical VANET is described and evaluated.
Źródło:
Archiwum Fotogrametrii, Kartografii i Teledetekcji; 2011, 22; 117-129
2083-2214
2391-9477
Pojawia się w:
Archiwum Fotogrametrii, Kartografii i Teledetekcji
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of square Msplit estimation in determination of vessel position in coastal shipping
Autorzy:
Zienkiewicz, M. H.
Czaplewski, K.
Powiązania:
https://bibliotekanauki.pl/articles/260266.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
robust estimation
maritime navigation
Msplit estimation
positioning
Opis:
The main aim of this paper is to assess the possibility of using non-conventional geodetic estimation methods in maritime navigation. The research subject of this paper concerns robust determination of vessel’s position using a method of parameters estimation in the split functional model (Msplit estimation). The studies performed will help in finding out if and in which situations the application of Msplit estimation as the method for determining vessel’s position is beneficial from the perspective of navigation safety. The results obtained were compared with the results of traditional estimation methods, i.e. least squares method and robust M-estimation.
Źródło:
Polish Maritime Research; 2017, 2; 3-12
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Improved classification robust Kalman filtering method for precise point positioning
Autorzy:
Zhang, Qieqie
Zhao, Long
Zhou, Jianhua
Powiązania:
https://bibliotekanauki.pl/articles/220468.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Kalman filter
classification robust
equivalent weight function
precise point positioning
Opis:
The accuracy and reliability of Kalman filter are easily affected by the gross errors in observations. Although robust Kalman filter based on equivalent weight function models can reduce the impact of gross errors on filtering results, the conventional equivalent weight function models are more suitable for the observations with the same noise level. For Precise Point Positioning (PPP) with multiple types of observations that have different measuring accuracy and noise levels, the filtering results obtained with conventional robust equivalent weight function models are not the best ones. For this problem, a classification robust equivalent weight function model based on the t-inspection statistics is proposed, which has better performance than the conventional equivalent weight function models in the case of no more than one gross error in a certain type of observations. However, in the case of multiple gross errors in a certain type of observations, the performance of the conventional robust Kalman filter based on the two kinds of equivalent weight function models are barely satisfactory due to the interaction between gross errors. To address this problem, an improved classification robust Kalman filtering method is further proposed in this paper. To verify and evaluate the performance of the proposed method, simulation tests were carried out based on the GPS/BDS data and their results were compared with those obtained with the conventional robust Kalman filtering method. The results show that the improved classification robust Kalman filtering method can effectively reduce the impact of multiple gross errors on the positioning results and significantly improve the positioning accuracy and reliability of PPP.
Źródło:
Metrology and Measurement Systems; 2019, 26, 2; 267-281
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robustness analysis of super-robust and adaptive algorithm of input shaping
Autorzy:
Gniadek, M.
Powiązania:
https://bibliotekanauki.pl/articles/377177.pdf
Data publikacji:
2015
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
adaptive input shaping
super-robust input shaping
crane positioning
oscillation avoidance
Opis:
Many mechanical systems are characterized by flexible joints. One of the main problems in control of this kind of devices are the mechanical oscillations. To avoid the problem of vibrations the input shaping method might be used. For the systems with variable parameters the standard methods of simple input shaping are insufficient and non-robust. More complicated algorithms, exemplary super-robust, can be used, but have negative influence on the regulation time. The alternative method is an adaptive algorithm of input shaping. Both methods are compared on the crane system with variable load mass and line length. The algorithms of system parameter changing are executed with variable speed. The research was made in Matlab/Simulink environment.
Źródło:
Poznan University of Technology Academic Journals. Electrical Engineering; 2015, 83; 195-202
1897-0737
Pojawia się w:
Poznan University of Technology Academic Journals. Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of Improved Robust Kalman Filter in Data Fusion for PPP/INS Tightly Coupled Positioning System
Autorzy:
Li, Z.
Yao, Y.
Wang, J.
Gao, J.
Powiązania:
https://bibliotekanauki.pl/articles/221374.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
PPP/INS tightly coupled positioning
robust filter
IGG scheme
Mahalanobis distance
Opis:
A robust Kalman filter improved with IGG (Institute of Geodesy and Geophysics) scheme is proposed and used to resist the harmful effect of gross error from GPS observation in PPP/INS (precise point positioning/inertial navigation system) tightly coupled positioning. A new robust filter factor is constructed as a three-section function to increase the computational efficiency based on the IGG principle. The results of simulation analysis show that the robust Kalman filter with IGG scheme is able to reduce the filter iteration number and increase efficiency. The effectiveness of new robust filter is demonstrated by a real experiment. The results support our conclusion that the improved robust Kalman filter with IGG scheme used in PPP/INS tightly coupled positioning is able to remove the ill effect of gross error in GPS pseudorange observation. It clearly illustrates that the improved robust Kalman filter is very effective, and all simulated gross errors added to GPS pseudorange observation are successfully detected and modified.
Źródło:
Metrology and Measurement Systems; 2017, 24, 2; 289-301
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

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