# A New Model for Human Running Micro-Doppler FMCW Radar Features
## 1 Introduction  
Human detection is a key area of autonomous vehicle safety research [1, 2, 3, 4]. Sensors are often used to sense human objects to avoid collisions and ensure safe driving behavior, such as cameras, LiDAR, and FMCW radar. The signal will be interfered with by other signal sources during the acquisition process [5, 6]. The visual sensor will also be affected by the light [7]. There will be various noises, spurs, and interferences when the radar sensor is working [8, 9]. The human target information will be seriously affected. The detection accuracy and algorithm performance will also be reduced [10, 11]. Furthermore, the hardware system and real measurement are costly [12], and large-scale actual measurement will be expensive [13]. Therefore, this work adopts simulation to detect human targets, which also provides assistance for subsequent interference simulation and anti-interference work. Human detection simulation relies on the human body model, and the most advanced human body model is based on vision [14, 15, 16, 17, 18, 19]. In the field of radar, there are also a variety of mannequins to simulate human walking movement [20, 21, 22, 23, 24]. The advanced mannequins are mostly used for 3D reconstruction, movie special effects, and action recognition. The visual human body model uses three-dimensional grids or voxels to describe the human body's surface and structure. The radar human body model uses electromagnetics and scattering theory to establish a mathematical physical model. The two models' representations are different. As a result, the visual solution is insufficient for the human target detection and echo analysis problem in the radar field. Therefore, a human body model based on radarmust be created. However, the existing radar human body model is only suitable for a specific type of walking motion and cannot be generalized to any desired motion. In short, the Doppler signals of complex human motion models, such as the running model, have not been simulated yet. A more realistic and simpler FMCW radar human motion model is lacking. Therefore, a human running model based on FMCW radar was proposed. The detection of human targets was completed by FMCW radar. The Doppler characteristics in radar echoes were analyzed. Human radar echoes have unique micro-Doppler signatures that are caused by the motion of different body parts [20,21,25]. The radar echo signal was modulated by movements of the hands and legs. The micro-Doppler's excitation frequency is about a sine wave. This unique modulation can be described by two parameters, amplitude and frequency. The regular pattern of body motion can be described finely by the micro-Doppler feature of the radar echo signal. The micro-Doppler features are observed with a joint time-frequency representation, such as short-time Fourier transform, and smooth pseudo Wigner-Ville distribution [20,21,26]. The generated Doppler spectrograms can be used to identify and classify different types of motion [27,28,29]. The Thalmann model [22] was simplified to describe the electromagnetic wave modulation of the human running movement. A human running model which is suitable for human micro-motion radar was proposed. Based on the human running model, the analytical expressions of the FMCW radar echoes were derived. The micro-Doppler characteristics of human running were analyzed. Finally, an FMCW radar measurement platform was built to validate the human running model. The main contributions of the proposed approach are summarized as follows. 1. A human running simulation model based on FMCW radar is proposed, which can achieve a real simulation of a running human body. In the field of FMCW radar, this model fills the gap in the complex human motion model and provides a theoretical model for studying the dynamic characteristics and radar response mechanisms. 2. The running Doppler signature of each body part is comprehensively analyzed in the verification platform.