RADAR and Camera Sensor Data Fusion

Abstract

As demand for vehicle automation has expanded in the last few years, it has become imperative to more precisely recognize the position and speed of surrounding vehicles. Object detection has been recognized as an important feature of the advanced driving assistance system (ADAS). This also ensures the safety of vehicles and prevents accidents caused by the negligence of humans. Object detection with sensor data fusion has proved to be very effective. Obstacles can be detected and labeled with the help of RADAR, LIDAR, and camera. Every sensor has advantages and limitations. Limitations of one sensor can be overcome by another sensor. Sensors such as LIDAR, RADAR, and camera are used together in order to obtain optimum results contributing to better object detection in autonomous systems. The paper describes the fusion of data acquired by the two sensors RADAR (AWR1642BOOST) and a two-dimensional camera (LOGITECH C170). RADAR can achieve better results in distance calculation than camera, whereas camera can achieve better results in angle compared to RADAR. Similarly, RADAR works efficiently in poor weather conditions and lighting, whereas camera may not provide accurate results. The data acquired by both the sensors are fused in order to obtain better object detection and ensure accurate calculation of parameters of the object detected. Region of interest detection and Haar Cascade algorithms are implemented to get satisfactory results and has been implemented in real time.