No abstract

Automotive radar interference is an issue arising with the increasing amount of radar systems in automotive scenarios. Interference can influence the functionality of a radar system, e.g. decrease its detection capability. To ensure functionality in critical situations, interference countermeasures are applied. This paper proposes a countermeasure for chirp sequence modulated radars interfering one another estimating an interfering signals' parameters to afterwards reconstruct and remove the interference.

Abstract-The application of radar sensors for driver assistance systems and autonomous driving leads to an increasing probability of radar interferences. Those interferences degrade the detection capabilities and can cause sensor blindness. This paper uses a realistic road scenario to address the problems of a common countermeasure that simply removes interferenceaffected parts of time domain radar signals and thereby introduces a gap. The paper solves the problem with the application of a sparse sampling signal recovery algorithm that is also used for compressed sensing problems. It is shown that the signal recovery can clearly overcome the shortcomings of just removing interfered signal parts. In the end of the paper, the applicability of the used algorithm is verified with measured radar data.

No abstract

Interference between automotive radars decreases the sensors' detection capabilities. It is possible to use digital beamforming (DBF) in multi-antenna systems to reduce the power received from certain directions of arrival (DoA). If digital beamforming is used to mitigate the effect of an interferer, it is shown that it is not sufficient to cancel the DoA of an interferer alone, if an I-Q mixer is not present. Additionally, a second DoA must be blinded out. A DBF system which performs this task is presented. Experimental and simulated results support the mathematical derivation and show possible improvements with DBF.