DocumentCode :
1894365
Title :
Joint spatial- and Doppler-based ego-motion estimation for automotive radars
Author :
Barjenbruch, Michael ; Kellner, Dominik ; Klappstein, Jens ; Dickmann, Juergen ; Dietmayer, Klaus
Author_Institution :
Inst. of Meas., Ulm Univ., Ulm, Germany
fYear :
2015
fDate :
June 28 2015-July 1 2015
Firstpage :
839
Lastpage :
844
Abstract :
An ego-motion estimation method based on the spatial and Doppler information obtained by an automotive radar is proposed. The estimation of the motion state vector is performed in a density-based framework. Compared to standard vehicle odometry the approach is capable to estimate the full two dimensional motion state with three degrees of freedom. The measurement of a Doppler radar sensor is represented as a mixture of Gaussians. This mixture is matched with the mixture of a previous measurement by applying the appropriate egomotion transformation. The parameters of the transformation are found by the optimization of a suitable join metric. Due to the Doppler information the method is very robust against disturbances by moving objects and clutter. It provides excellent results for highly nonlinear movements. Real world results of the proposed method are presented. The measurements are obtained by a 77GHz radar sensor mounted on a test vehicle. A comparison using a high-precision inertial measurement unit with differential GPS support is made. The results show a high accuracy in velocity and yaw-rate estimation.
Keywords :
automobiles; driver information systems; motion estimation; radar imaging; traffic engineering computing; Doppler information; Doppler radar sensor measurement; Doppler-based ego-motion estimation; Gaussian mixture; automotive radars; density-based framework; motion state vector estimation; spatial information; spatial-based ego-motion estimation; vehicle odometry; velocity estimation; yaw-rate estimation; Current measurement; Doppler effect; Estimation; Radar; Standards; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2015 IEEE
Conference_Location :
Seoul
Type :
conf
DOI :
10.1109/IVS.2015.7225789
Filename :
7225789
Link To Document :
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