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Semi-Markov Process Based Localization Using Radar in Dynamic Environments.

, , , , and . ITSC, page 423-429. IEEE, (2015)

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Dynamic level of detail 3D occupancy grids for automotive use., , , and . Intelligent Vehicles Symposium, page 269-274. IEEE, (2010)A Feature-Based Approach for Group-Wise Grid Map Registration., , , , and . ITSC, page 511-516. IEEE, (2015)Probabilistic modeling of sensor properties in generic fusion systems for modern driver assistance systems., , , and . Intelligent Vehicles Symposium, page 760-765. IEEE, (2010)OAFuser: Online Adaptive Extended Object Tracking and Fusion using automotive Radar Detections., , , , , , and . MFI, page 303-309. IEEE, (2020)Road User Detection on Polarimetric Pre-CFAR Radar Data Level., , , , and . IEEE Robotics Autom. Lett., 8 (6): 3558-3565 (June 2023)A Machine Learning Approach for Radar Based Height Estimation., , , and . ITSC, page 2364-2370. IEEE, (2018)Motion Classification and Height Estimation of Pedestrians Using Sparse Radar Data., , , , and . SDF, page 1-6. IEEE, (2018)RoughCough - A new image registration method for radar based vehicle self-localization., , , , and . FUSION, page 1533-1541. IEEE, (2015)Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification?, , , , , and . FUSION, page 1-8. IEEE, (2020)Polarimetric Covariance Gridmaps for Automotive Self-Localization., , , and . FUSION, page 1-8. IEEE, (2020)