Abstract: Techniques are provided for extended object tracking using RADAR return points only. The techniques include receiving the return points from at least one RADAR sensor of the vehicle. One or more clusters based on or from the return points are generated. An estimated position and velocity of each of the one or more clusters is computed. A Recursive Least Squares (RLS) based algorithm is proposed to estimate the instantaneous velocity of a cluster in real-time that allows for accurate track-cluster association, removes the need to perform computationally expensive non-linear state updates, and allows for the estimation of the true velocity even in frames with a large amount of clutter. If it is determined that the one or more clusters are associated with an existing object track, the existing object track is updated using at least the respective positions of the one or more clusters associated with the existing object track.

Abstract: Techniques are provided for extended object tracking using RADAR return points only. The techniques include receiving the return points from at least one RADAR sensor of the vehicle. One or more clusters based on or from the return points are generated. An estimated position and velocity of each of the one or more clusters is computed. A Recursive Least Squares (RLS) based algorithm is proposed to estimate the instantaneous velocity of a cluster in real-time that allows for accurate track-cluster association, removes the need to perform computationally expensive non-linear state updates, and allows for the estimation of the true velocity even in frames with a large amount of clutter. If it is determined that the one or more clusters are associated with an existing object track, the existing object track is updated using at least the respective positions of the one or more clusters associated with the existing object track.

Abstract: Techniques are provided for extended object tracking using RADAR return points only. The techniques include receiving the return points from at least one RADAR sensor of the vehicle. One or more clusters based on or from the return points are generated. An estimated position and velocity of each of the one or more clusters is computed. A Recursive Least Squares (RLS) based algorithm is proposed to estimate the instantaneous velocity of a cluster in real-time that allows for accurate track-cluster association, removes the need to perform computationally expensive non-linear state updates, and allows for the estimation of the true velocity even in frames with a large amount of clutter. If it is determined that the one or more clusters are associated with an existing object track, the existing object track is updated using at least the respective positions of the one or more clusters associated with the existing object track.