High-performance method for simulating laser range profiles using a mechanism of GPU rasterization

Subject of study. This study focuses on the laser range profile (LRP) formed by the reflection of a laser pulse from an object in a light detection and ranging (LiDAR) system. Aim of study. The aim of this study is to develop a method for simulating LRPs of objects in LiDAR systems using graphics processing unit (GPU) rasterization. Method. To determine the LRP of a three-dimensional scene, object surfaces were subdivided into elementary patches that are projected onto screen pixels using the standard GPU rasterization pipeline. For each surface element, a pixel shader computed the reflective impulse response (RIR). The overall scene RIR was then obtained by constructing a weighted histogram. The scene LRP was calculated by convolving the scene RIR with the impulse response of the LiDAR system. Main results. A mathematical model of the LRP generated by a LiDAR system was developed. In addition, a method for computing the LRP of a scene composed of three-dimensional objects using GPU rasterization was proposed, and a corresponding software implementation algorithm was described. The adequacy of the model was verified by comparing simulation results for various objects with data acquired by other authors. Practical significance. The proposed method enables efficient simulation of LRPs for complex scenes, supports the investigation of LiDAR system performance under diverse conditions, facilitates the development of algorithms for processing scanning results, and allows the creation of databases for applying machine-learning techniques to LRP-based object recognition.