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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.

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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.

For high-resolution direction of arrival estimation, a wide aperture is necessary. This can be achieved with multipleinput multiple-output (MIMO) radars, which offer a wide virtual aperture. However, the requirement of orthogonal transmit signals has to be satisfied for their operation. Although time division multiplexing (TDM) of the transmit elements is an orthogonality realization with low hardware effort, phase errors occur in nonstationary scenarios. This work briefly discusses the problem of the motion-induced phase errors and describes processing steps to mitigate them without additional effort. The proposed technique is demonstrated with simulation and measurement data.

It was reported for specific bats, that they use a certain scheme to shift the frequencies of their echo location calls to counteract interferences with conspecifics. As in road traffic, an increasing number of cars is equipped with radar sensors, there is also the problem of mutual interference. The available frequency bands are limited, so a randomized frequency hopping will not be the best solution. In this paper, we adapt the frequency hopping behavior of the bats reported in [1] to a radar system. We discuss the algorithm and show measurements of its performance in an anechoic chamber.

Radar sensors become typical components for automotive driver assistance systems and autonomous driving. The widespread use of this sensor type leads to an increasing risk of unwanted interferences. Those interferences can severely degrade the detection performance and cause sensor blindness. To overcome this problem, this paper describes a method to estimate and remove interfering signals in data of chirp sequence modulated radars. The estimation is derived theoretically and applied on simulation and measurement data.