Simulating sonar devices requires modeling underwater acoustics, simultaneously rendering time-efficient data. Existing methods focus on a basic implementation of one sonar type, where most of the sound properties are disregarded. In this context, this work presents a multi-device sonar simulator capable of processing an underwater scene by a hybrid pipeline on GPU: Rasterization computes the primary intersections, while only the reflective areas are ray-traced. Our proposed system launches a few rays when compared to a full ray-based method, achieving a significant performance gain without quality loss in the final rendering. Resulting reflections are then characterized as two sonar parameters: Echo intensity and pulse distance. Underwater acoustic features, such as speckle noise, transmission loss, reverberation and material properties of observable objects are also computed in the final acoustic image. Visual and numerical performance assessments demonstrated the effectiveness of the proposed simulator to render underwater scenes in comparison to real sonar devices.

模拟声纳设备需要对水下声学建模，同时渲染省时的数据。现有的方法集中于一种声纳类型的基本实现，其中大多数声音属性被忽略。在这种情况下，这项工作提出了一种多设备声纳模拟器，该模拟器能够通过GPU上的混合管线处理水下场景：光栅化计算主要的相交点，而仅反射区域被光线追踪。与基于全光线的方法相比，我们提出的系统发射了几条光线，实现了显着的性能提升，而最终渲染中没有质量损失。然后将反射结果表征为两个声纳参数：回波强度和脉冲距离。水下声学特征，例如斑点噪声，传输损耗，最终声学图像中还会计算可观察对象的混响和材料属性。视觉和数字性能评估证明了与真实声纳设备相比，所提出的模拟器渲染水下场景的有效性。