Template matching for radar-based orientation and position estimation in automotive scenarios

Future high-resolution radars enable new functionalities in advanced driver assistance systems, relying on fast and reliable extraction of properties of vehicles on the road. A critical property for the prediction of trajectories and the assessment of potentially dangerous situations is that of the actual motion-the velocity vector and yaw rate-of observed objects. In this paper, an approach to distinguish linear from non-linear motions as well as estimating the yaw rate using only a single radar sensor is presented and evaluated via measurements.

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An RLS-Based Instantaneous Velocity Estimator for Extended Radar Tracking

Gosala

Meng²

2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Radar sensors have become an important part of the perception sensor suite due to their long range and their ability to work in adverse weather conditions. However, several shortcomings such as large amounts of noise and extreme sparsity of the point cloud result in them not being used to their full potential. In this paper, we present a novel Recursive Least Squares (RLS) based approach to estimate the instantaneous velocity of dynamic objects in real-time that is capable of handling large amounts of noise in the input data stream. We also present an end-to-end pipeline to track extended objects in real-time that uses the computed velocity estimates for data association and track initialisation. The approaches are evaluated using several real-world inspired driving scenarios that test the limits of these algorithms. It is also experimentally proven that our approaches run in real-time with frame execution time not exceeding 30 ms even in dense traffic scenarios, thus allowing for their direct implementation on autonomous vehicles.

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Template matching for radar-based orientation and position estimation in automotive scenarios

Cited by 5 publications

References 2 publications

Direction of Movement Estimation of Cyclists with a High-Resolution Automotive Radar

Direction of Movement Estimation of Cyclists with a High-Resolution Automotive Radar

Instantaneous Actual Motion Estimation with a Single High-Resolution Radar Sensor

An RLS-Based Instantaneous Velocity Estimator for Extended Radar Tracking

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