Abstract
There are various sensor technologies used to obtain target information, such as camera-based position estimation methods, LiDAR, radar, and sensor fusion. Radar technology is capable of estimating long-distance targets and determining positions even in challenging environments, such as rain, snow, fog, and darkness. Sensor data provides position information such as speed, distance, azimuth, and elevation. This paper focuses on distance measurement among these position parameters. The method for acquiring distance information applies the linear limited minimum variance method to improve the signal-to-noise ratio of the received signal, remove interference, and estimate the distance from the radar to the target using the radar equation. Through simulation experiments, the transmission signal is generated by mixing the source signal and the interference signal, and the reception signal is input to the antenna. The target distance is estimated by removing signals other than the desired components from the received signal. The simulation results show that the signal-to-noise ratio is improved by removing the interference signal, and the target distance estimation accuracy is improved.