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Randomized Evolution Model for Multi Hypothesis Kalman Filter

: Handke, Sebastian Thomas; Gehlen, Joshua


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Aerospace and Electronic Systems Society -AESS-:
Symposium on Sensor Data Fusion: Trends, Solutions, Applications, SDF 2019 : Bonn, Germany, October 15-17, 2019
Piscataway, NJ: IEEE, 2019
ISBN: 978-1-7281-5086-4 (Print)
ISBN: 978-1-7281-5085-7
Symposium on Sensor Data Fusion - Trends, Solutions, Applications (SDF) <13, 2019, Bonn>
Conference Paper
Fraunhofer FKIE ()

A new randomized approach for highly maneuvering targets based on multi hypothesis tracking is presented. The acceleration range - a parameter in current evolution models is used to design various motion models. The approach randomises this parameter to cover a wider range of maneuver characteristics. Simulation shows that the performance of the new method results in a more reliable track continuity.