System Design of Advanced Multi-Beam and Multi-Range Automotive Radar

Abstract

As the number of vehicles on the road is increased, the incidence of traffic accident is gradually increased and the number of death on roads is also increased. Most accidents are due to carelessness of the driver. If the vehicle can actively recognize the dangerous situation and alert the driver to avoid accident, it will be a great help to the driver. As concern for safety and driver assistance increases, needs for driver assistance system (DAS) are consistently increasing. Moreover, with the grooming demand for autonomous driving, there has been paid a great attention to the incorporation of multiple sensors. Various sensors for safety and convenience are being introduced for automobiles. The detection performance of the automotive radar looks outstanding compared to other sensors such as Lidar, camera, and ultrasonic sensors, in poor weather conditions or environmental conditions of the roads. Among many applications using automotive radars, the adaptive cruise control (ACC) and the autonomous emergency braking (AEB) using forward looking radars are the most basic functions for safety and convenience. Using ACC and AEB functions, drivers can be guaranteed safety as well as convenience when visibility is poor under bad weather conditions. Generally, the radar system for ACC and AEB had been composed of singe longrange radar (LRR) and two of short-range radar (SRR) and the system cost was very expensive. However, the cost can be lowered by the concept of multi-beam, multirange (MBMR) radar which consist of integrated narrow long range beam and wide short range beam in a single radar sensor. In this dissertation, we propose an advanced MBMR radar for ACC and AEB using 77 GHz band and highly integrated RF ICs. The detection specifications are investii gated base on theoretical radar principles and effective design concepts are suggested to satisfy the specifications. We implemented an actually working forward looking MBMR radar and performed experiments to verify the detection performance. To overcome the limitation of radar hardware resources for cost-effective design, we propose novel signal processing schemes to recognize environment on roads which are regarded as impossible with automotive radar. Characteristics of an iron tunnel which deteriorate the detection performance of the radar are analyzed and a measure for the recognition is proposed. Moreover, the recognition method is expanded to harmonic clutters which are caused by man-made structures on roads containing periodic structures such as iron tunnels, guardrails, and sound-proof wall. The harmonic clutter suppression method is also proposed to enhance the quality of the received signal and improve the detection performance of the radar. All experiments are performed using the proposed MBMR radar to verify the detection performance and the usefulness of proposed signal processing methods for recognition and suppression of clutters on roads.