CPL - Chalmers Publication Library
| Utbildning | Forskning | Styrkeområden | Om Chalmers | In English In English Ej inloggad.

Road intensity based mapping using radar measurements with a probability hypothesis density filter

C. Lundquist ; Lars Hammarstrand (Institutionen för signaler och system, Signalbehandling) ; F. Gustafsson
IEEE Transactions on Signal Processing (1053-587X). Vol. 59 (2010), 4, p. 1397 - 1408.
[Artikel, refereegranskad vetenskaplig]

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 the resulting map is shown to well describe the environment as a human perceives it.

Nyckelord: Clustering , Gaussian mixture , PHD , mapping , probability hypothesis density , road edge estimation



Den här publikationen ingår i följande styrkeområden:

Läs mer om Chalmers styrkeområden  

Denna post skapades 2011-12-22. Senast ändrad 2014-11-27.
CPL Pubid: 150869

 

Läs direkt!


Länk till annan sajt (kan kräva inloggning)


Institutioner (Chalmers)

Institutionen för signaler och system, Signalbehandling

Ämnesområden

Transport
Signalbehandling

Chalmers infrastruktur