TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Schuster, Michael
A1  - Reuter, Johannes
A1  - Wanielik, Gerd
T1  - Probabilistic data association for tracking extended targets under clutter using random matrices
T2  - 18th International Conference on Information Fusion (Fusion), 6-9 July 2015, Washington, DC, USA
N2  - The use of random matrices for tracking extended objects has received high attention in recent years. It is an efficient approach for tracking objects that give rise to more than one measurement per time step. In this paper, the concept of random matrices is used to track surface vessels using highresolution automotive radar sensors. Since the radar also receives a large number of clutter measurements from the water, for the data association problem, a generalized probabilistic data association filter is applied. Additionally, a modification of the filter update step is proposed to incorporate the Doppler velocity measurements. The presented tracking algorithm is validated using Monte Carlo Simulation, and some performance results with real radar data are shown as well.
KW  - target tracking
KW  - Doppler radar
KW  - filtering theory
KW  - marine engineering
KW  - marine navigation
Y1  - 2015
UR  - http://ieeexplore.ieee.org/document/7266663/
SN  - 978-0-9824-4386-6
SB  - 978-0-9824-4386-6
N1  - Volltextzugriff für Hochschulangehörige via Datenbank IEEE Xplore
SP  - 961
EP  - 968
ER  -