Interference and interference mitigation

Abstract

Recent improvements in self-driving technology emphasize the importance of sensors that are being used in vehicles. Achievements in integrated circuits and the semiconductor industry made the low-cost mass production of single-chip automotive radars possible. While other sensors exist, automotive radar acts as the digital eyes of self-driving vehicles due to its proven all-weather, day, and night capabilities, which makes the automotive radar one of the key elements for self-driving technology. Most of today's vehicles are already equipped with radar systems to improve situational awareness and road safety. Current mmWave automotive radar sensors share a spectrum space from 76 to 81 GHz [1, 2]. The increasing number of radar-equipped vehicles on the roads has already been an issue for the coexistence of multiple automotive radars in congested traffic because the unwanted radar signals generated by other radar - also known as interference - negatively affect the functionality of the radar systems by decreasing their sensing capability. Since a lot of equal or similar waveforms and transmission strategies are presently used in automotive radar applications, interference occurs between multiple radar units. This kind of interference may raise the noise floor and reduce the signal-to-noise ratio which degrades the probability of target detection. On the other hand, interference generated by other radar systems may cause (ghost) false targets that reduce the target tracking ability of the radar.Recent automotive radar systems are taking advantage of multiple-input multiple-output (MIMO) antenna arrays to provide the azimuth information of targets. Depending on the MIMO antenna configuration, it is also possible to exploit the azimuth and elevation information of the targets. While interference is mostly generated from other radars, there might be self-interference from the strong return signal reflected by the radome or induced by the mutual-coupling (spill-over) effect between transmitters and receivers. It is crucial to mitigate interference or reduce its effect because the objects with low radar cross sections (RCSs), such as pedestrians or cyclists, may not be detected or be completely lost during tracking. Therefore, interference leads to dangerous situations and becomes a bottleneck for driving assistance and autonomous vehicles. Especially in fully autonomous vehicles, where any human intervention will no longer be present, the dependability on the sensors is extremely high and there is no tolerance for sensing failures due to interference.In this chapter, we examine different types of automotive radar interference, their characteristics, and their effects on radar system performance, as well as provide a review of the current state of the art for interference mitigation techniques.