# High-Speed Surface Property Recognition with a 140 GHz Frequency
## 2 Data Sampling Platforms  
To meet the demands of real-world applications, we fabricated a high-speed sampling platform, depicted in Figure 2a. This platform is designed to fulfill the dual criteria of rapid  
Figure 1: A schematic of high-speed scenarios, including handheld, vehicle-mounted, and unmanned aerial vehicle (UAV) scenarios. rotation and high precision, achieved through a fully automated programming-driven sampling system. Its core is a high-precision electrical control rotational stage powered by a 57-step stepper motor and governed by a worm gear structure. The motor, with a step angle of 1.8\({}^{\circ}\) and a mechanical transmission ratio of 1:180, confirms the rotational stage with a minimum rotation angle of 0.01\({}^{\circ}\). This makes its precision and alignment under the measurement requirements. The experimental setup involved affixing the receiver (Rx) onto the rotational stage via an extended rail, placing the rough surface sample at the rotational stage's epicenter, and situating the transmitter (Tx) at a 45 incident angle. We designed such a setup to emulate scenarios of collaborative perception to avoid the self-interference faced in independent perception [24; 25] such as a base station emitting perception signals that are reflected by sensed targets and received by terminals. The spatial arrangement had the transmitter and receiver positioned 36 cm and 38 cm away from the sample's geometric center, respectively. The transmission assembly comprised a signal generator (Ceyear 1465D), a frequency multiplier module (Ceyear 82406B), and a horn antenna. The signal generator (Ceyear 1465) has the capability to generate signals up to 20 GHz, which were then up-converted to the 110-170 GHz range using the Ceyear 82406D. The receiver employs an identical horn antenna to capture signals and forwards them to a power sensor (Ceyear 71718) for signal detection with a single sampling time of 50 ms. This setup allows us to analyze the variations in signal strength and pattern as influenced by different levels of surface roughness [26], enabling the correlation between the received power data and the physical texture characteristics of the surfaces. To enhance focusing, a lens with a 10 cm focal length was strategically positioned in front of Tx, aligning with the focal point. Throughout the sampling process, while Tx and the surface sample remained stationary, Rx embarked on a circular trajectory around the sample, instigating variations in reflection angles. Both Tx and Rx are fixed within a horizontal plane, which is not fully representative of practical situations where an elevation angle may be often present [26; 27]. However, for environ  
Figure 2: (**a**) An image of the data sampling platforms, including an electric rotational stage that drives Rx in a circular motion. The blue arrows indicate the range of motion for Rx, which includes variable speed regions of 20\({}^{\circ}\) each in the front and rear as well as a uniform speed region of 100\({}^{\circ}\) in the middle. (**b**) Surface samples created using a combination of metal materials, tools, and shapes, specifically employing brass, bronze, and aluminum to facilitate different degrees of surface roughness. mental sensing in the real world, we think that a near-zero elevation angle can be sufficient in most cases. The electrical control rotational stage was exercised through a serial port protocol, ensuring continuous motion data monitoring. Concurrently, LAN and SCPI protocols were deployed as interface protocols connecting the terahertz signal generator and power meter. Through the utilization of these protocols to transmit our predefined commands, control over both devices is facilitated. The amalgamation of these components was seamlessly orchestrated using Python 3.9, which facilitated interface calls, ensured time synchronization, governed sampling control, and oversaw data storage operations.