Radar sensors offer enormous advantages as sensing devices for automated and autonomous driving. However, when multiple of such sensors are operated in a large number of cars, there is a high risk of the occurrence of mutual interference. In the currently widespread linearly frequency modulated sensors interference reduces the detection performance, especially for targets with a low radar cross section. In this paper the interference effects are suppressed with an adaptive beamforming scheme based on a mean square error minimization. The paper evaluates the algorithm with the help of a simulated and measured scenario, and discusses the occurring interference effects and the benefits of the beamforming approach
Mutual interference between automotive radars is a major obstacle currently faced by manufacturers i...
Abstract Mutual interference in automotive radar is expected to become a major issue owing to the ra...
Autonomous driving relies on a variety of sensors, especially radars, which have unique robustness u...
Radar has emerged as an important sensor for scenario perception in automated driving and surveillan...
In the coming years, automotive radar sensors will play a crucial role in the autonomous driving tas...
As driver assistance systems and autonomous driving are on the rise, radar sensors become a common d...
Automotive radar interference is an issue arising with the increasing amount of radar systems in au...
This paper presents a novel comparison of spatial suppression of interference in an automotive MIMO ...
The application of Doppler beam sharpening (DBS) for enhanced imagery in a multiple-input, multiple-...
Automotive radars play a very important role in reduction of traffic accidents and casualties by mak...
In the recent years the number of vehicles on the road equipped with radar sensors is increased, esp...
This paper presents a new approach to mitigating radar interference and focuses on the application o...
The application of radar sensors for driver assistance systems and autonomous driving leads to an in...
This thesis describes a blind beamforming technique for GPS receivers. It improves the performance o...
A methodology to estimate waveform parameters of unknown interfering signals and number of interferi...
Mutual interference between automotive radars is a major obstacle currently faced by manufacturers i...
Abstract Mutual interference in automotive radar is expected to become a major issue owing to the ra...
Autonomous driving relies on a variety of sensors, especially radars, which have unique robustness u...
Radar has emerged as an important sensor for scenario perception in automated driving and surveillan...
In the coming years, automotive radar sensors will play a crucial role in the autonomous driving tas...
As driver assistance systems and autonomous driving are on the rise, radar sensors become a common d...
Automotive radar interference is an issue arising with the increasing amount of radar systems in au...
This paper presents a novel comparison of spatial suppression of interference in an automotive MIMO ...
The application of Doppler beam sharpening (DBS) for enhanced imagery in a multiple-input, multiple-...
Automotive radars play a very important role in reduction of traffic accidents and casualties by mak...
In the recent years the number of vehicles on the road equipped with radar sensors is increased, esp...
This paper presents a new approach to mitigating radar interference and focuses on the application o...
The application of radar sensors for driver assistance systems and autonomous driving leads to an in...
This thesis describes a blind beamforming technique for GPS receivers. It improves the performance o...
A methodology to estimate waveform parameters of unknown interfering signals and number of interferi...
Mutual interference between automotive radars is a major obstacle currently faced by manufacturers i...
Abstract Mutual interference in automotive radar is expected to become a major issue owing to the ra...
Autonomous driving relies on a variety of sensors, especially radars, which have unique robustness u...