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2011

Road Intensity Based Mapping Using Radar Measurements With a Probability Hypothesis Density Filter

9 years 8 months ago
Road Intensity Based Mapping Using Radar Measurements With a Probability Hypothesis Density Filter
Abstract—Mapping stationary objects is essential for autonomous vehicles and many autonomous functions in vehicles. In this contribution the probability hypothesis density (PHD) filter framework is applied to automotive imagery sensor data for constructing such a map, where the main advantages are that it avoids the detection, the data association and the track handling problems in conventional multiple-target tracking, and that it gives a parsimonious representation of the map in contrast to grid based methods. Two original contributions address the inherent complexity issues of the algorithm: First, a data clustering algorithm is suggested to group the components of the PHD into different clusters, which structures the description of the prior and considerably improves the measurement update in the PHD filter. Second, a merging step is proposed to simplify the map representation in the PHD filter. The algorithm is applied to multi-sensor radar data collected on public roads, and...
Christian Lundquist, Lars Hammarstrand, Fredrik Gu
Added 15 May 2011
Updated 15 May 2011
Type Journal
Year 2011
Where TSP
Authors Christian Lundquist, Lars Hammarstrand, Fredrik Gustafsson
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