Send-on-delta sampling strategies for vehicle position tracking

Author(s):  
Miguel Diaz-Cacho ◽  
Joao F. Pereira ◽  
Emma Delgado ◽  
Antonio Barreiro
Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 939 ◽  
Author(s):  
Safa Ouerghi ◽  
Rémi Boutteau ◽  
Xavier Savatier ◽  
Fethi Tlili

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4126 ◽  
Author(s):  
Taeklim Kim ◽  
Tae-Hyoung Park

Detection and distance measurement using sensors is not always accurate. Sensor fusion makes up for this shortcoming by reducing inaccuracies. This study, therefore, proposes an extended Kalman filter (EKF) that reflects the distance characteristics of lidar and radar sensors. The sensor characteristics of the lidar and radar over distance were analyzed, and a reliability function was designed to extend the Kalman filter to reflect distance characteristics. The accuracy of position estimation was improved by identifying the sensor errors according to distance. Experiments were conducted using real vehicles, and a comparative experiment was done combining sensor fusion using a fuzzy, adaptive measure noise and Kalman filter. Experimental results showed that the study’s method produced accurate distance estimations.


2003 ◽  
Vol 62 (2) ◽  
pp. 121-129 ◽  
Author(s):  
Astrid Schütz ◽  
Franz Machilek

Research on personal home pages is still rare. Many studies to date are exploratory, and the problem of drawing a sample that reflects the variety of existing home pages has not yet been solved. The present paper discusses sampling strategies and suggests a strategy based on the results retrieved by a search engine. This approach is used to draw a sample of 229 personal home pages that portray private identities. Findings on age and sex of the owners and elements characterizing the sites are reported.


2017 ◽  
Vol 10 (4) ◽  
pp. 325
Author(s):  
Angie Julieth Valencia Castañeda ◽  
Mauricio Felipe Mauledoux Monroy ◽  
Oscar Fernando Avilés Sánchez ◽  
Paola Andrea Niño Suarez ◽  
Edgar Alfredo Portilla Flores

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