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Auflistung nach Autor:in "Govaers, Felix"

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  • Konferenzbeitrag
    Out-of-sequence data processing for track-before-detect using dynamic programming
    (INFORMATIK 2011 – Informatik schafft Communities, 2011) Govaers, Felix; Yang, Rong; Lai, Hoe Chee; Teow, Loo Nin; Ng, Gee Wah; Koch, Wolfgang
    In the recent past, tracking applications increasingly develop towards distributed sensor scenarios. In many cases, such schemes must cope with low observable targets in cluttered environments. Furthermore, such a setup suffers from communication delays and timely delayed sensor data. However, Track-before-Detect methodologies are not suitable for processing time delayed data yet. In this paper, we propose a new extension to a Dynamic Programming Algorithm (DPA) approach for Trackbefore-Detect in distributed sensor systems. This extension enables the DPA to process time delayed sensor data directly. Such delay might appear because of varying delays in the installed communication links. The extended DPA is identical to the recursive standard DPA in case of all sensor data appear in the timely correct order. In an experimental study, we show that the derived algorithm can compensate all occurring time delays very well.
  • Konferenzbeitrag
    Position tracking in urban environments using linear constraints and bias pseudo measurements
    (INFORMATIK 2010. Service Science – Neue Perspektiven für die Informatik. Band 2, 2010) Niewiejska, Julia; Govaers, Felix; Aschenbruck, Nils
    In many GPS-Sensor based tracking applications, the obtained measurements suffer from time a correlated bias. This is due to shadowing and multipath scattering of the wireless GPS signals. In this paper, we applicate a Schmidt-Kalman Filter (SKF) in order to improve the tracking process of ground vehicles on roads. We investigate possibilities to integrate bias measurements obtained from road information into the position tracking filter. To this end, we assume a digital map is given which contains road information for the observed region. The estimated position by the sensor data is projected onto the road as a hard constraint. This enables us to detect and to eliminate regular sensor bias by extending the estimate state of the target by an estimate of the sensor bias.
  • Konferenzbeitrag
    Rao-blackwellized particle filter for security surveillance
    (Informatik 2009 – Im Focus das Leben, 2009) Govaers, Felix; Wieneke, Monika