# Stationary Target Identification in a Traffic Monitoring Radar System
## 1 Introduction  
To realize autonomous driving, an autonomous vehicle must be equipped with automotive sensors such as cameras, LiDARs, and radars. In recent years, the development of autonomous driving technology has been accelerating due to advances in sensors for vehicles. For autonomous driving, not only the development of automotive sensors, but also the construction of intelligent road infrastructure is necessary. One of the essential factors for building an intelligent transportation system (ITS) is to monitor the volume and flow of vehicles on the road, which is known as traffic management. If the road traffic information can be measured and delivered to each driver on the road, more efficient road management will be possible. In other words, by analyzing traffic conditions in real time, it is possible to manage road traffic efficiently and implement optimal signaling systems In addition, the ITS can help drivers choose efficient routes and shorten the time to reach their destination. The most frequently used system for the measurement of road traffic is a camera-based monitoring system [1; 2]. For instance, a high-definition camera-based ITS with wireless communications was proposed for traffic surveillance in [3]. Recently, several studies have been conducted to use radar sensors for road traffic monitoring in addition to the camera-based surveillance systems. For example,the Global System for Mobile Communication (GSM)-based passive radar to monitor the road traffic was introduced in [4; 5]. They suggested the possibility of using the GSM-based radar to detect the velocity of the vehicle. In [6], the authors presented a method for estimating the range, velocity, and angle information of vehicles using a 35 GHz interferometric traffic monitoring radar system. In addition, the feasibility of road surveillance using passive radar systems was suggested in [7]. Recently, a method for identifying multiple lanes by clustering detection points in each lane in a frequency-shift keying radar system was proposed in [8]. These radar-based road monitoring systems can compensate for the weaknesses of the camera-based road surveillance systems. For example, in the case of the camera-based method, the detection performance is severely deteriorated in a lightless environment. In addition, the camera-based methods have the disadvantage of being vulnerable in terms of privacy protection. On the other hand, if radar is used for road monitoring, it is also effective in terms of personal privacy protection because it does not take a picture of the driver. Moreover, using the intrinsic function of radar, estimating the distance to the target and the velocity of the target, we can also get more information than we can get with the camera sensor. For example, the velocity of the vehicle can be measured directly using radar, which can replace the speedometer. In addition, counting the number of vehicles passing through a specific section is also one of the functions that can be easily implemented with radar. In general, traffic monitoring radars are installed at specific points on viaducts or bridges to face multiple lanes, as shown in Figure 1.  
In this environment, the traffic monitoring radar continuously receives radar signals reflected from road structures, such as guardrails and median strips. Because these structures are usually made of steel, they strongly reflect radar signals, and the radar perceives them as meaningful targets. Some studies on the adverse effects of the presence of these road structures on the radar detection performance were presented in [9; 10; 11]. If such misinformation is transmitted to a driver on the road through ITS, this can lead to a dangerous situation for the driver. Therefore, a signal processing that allows the radar to recognize road structures by itself should be applied. The significant difference between road structures and vehicles is that the structures are fixed to the road.