Dynamic Measurement with High Precision Using Frequency Agile Spatial Encoding Integrated FMCW LiDAR

In the field of industrial precision measurement, the localization and velocity information acquisition of moving targets still depend on short-term displacement measurements using instruments, such as laser trackers and total stations. Frequency-modulated continuous-wave (FMCW) laser measurement technology offers the advantage of achieving synchronized velocity-distance measurements. We present a frequency agile spatial encoding integrated FMCW LiDAR system scheme. This scheme is realized through the integration design of a primary optical path to simplify the structure and enhance interference resistance. Utilizing the benchmark peak generated by the coupling of an optical frequency comb (OFC) with FMCW laser as a reference, we accurately encode and reconstruct the target motion process, and each encoding point can reflect a subtle frequency change. This method projects velocity-distance information on the dynamic target onto agile frequency variations, which improves the measurement efficiency. Meanwhile, employing a Fizeau interferometric structure for the measurement setup reduces system errors. With this LiDAR system, the standard deviation of velocity measurements is less than 266 μm/s and the error is less than 240 μm/s in the experiment of low-speed target represented by a linear precision rail. For high-speed target measurements, exemplified by high-speed turntable with a linear velocity of up to 7.54 m/s, the standard deviation is only 367 μm/s, with the standard deviation of synchronous distance measurement result being less than 26 μm. Additionally, in simulated wide-area dynamic detection scenarios on an industrial robot platform, we demonstrated the system's capability to track and locate the equipment's entire operational state. Furthermore, when combined with advanced beam steering devices, it provides a technical foundation for compact, ultrahigh frame rate coherent LiDAR capable of three-dimensional dynamic detection in complex scenes.