Lidar System Architectures and Circuits

Abstract

3D imaging technologies are applied in numerous areas, including self-driving cars, drones, and robots, and in advanced industrial, medical, scientific, and consumer applications. 3D imaging is usually accomplished by finding the distance to multiple points on an object or in a scene, and then creating a point cloud of those range measurements. Different methods can be used for the ranging. Some of these methods, such as stereovision, rely on processing 2D images. Other techniques estimate the distance more directly by measuring the round-trip delay of an ultrasonic or electromagnetic wave to the object. Ultrasonic waves suffer large losses in air and cannot reach distances beyond a few meters. Radars and lidars use electromagnetic waves in radio and optical spectra, respectively. The shorter wavelengths of the optical waves compared to the radio frequency waves translates into better resolution, and a more favorable choice for 3D imaging. The integration of lidars on electronic and photonic chips can lower their cost, size, and power consumption, making them affordable and accessible to all the abovementioned applications. This review article explains different lidar aspects and design choices, such as optical modulation and detection techniques, and point cloud generation by means of beam-steering or flashing an entire scene. Popular lidar architectures and circuits are presented, and the superiority of the FMCW lidar is discussed in terms of range resolution, receiver sensitivity, and compatibility with emerging technologies. At the end, an electronic-photonic integrated circuit for a micro-imaging FMCW lidar is presented as an example.

The authors' abstract, as published at the source. IEEE Communications Magazine, 2017 · DOI ↗