Articles | Volume 14
https://doi.org/10.5194/ars-14-31-2016
https://doi.org/10.5194/ars-14-31-2016
28 Sep 2016
 | 28 Sep 2016

Virtual sensor models for real-time applications

Nils Hirsenkorn, Timo Hanke, Andreas Rauch, Bernhard Dehlink, Ralph Rasshofer, and Erwin Biebl

Abstract. Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.

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Short summary
Increased complexity and severity of future driver assistance systems demand extensive testing and validation. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The method is widely applicable and able to adapt to complex behavior. As exemplary implementation, a model of an automotive radar system, using a high precision measurement system, is presented.