Data-Driven Angular Jitter Estimator for Lidar

Remote sensing and imaging from space have been major components of numerous fields, from meteorology and climate studies to geological mapping and disaster management. Lidar technology, specifically, has presented a significant advantage because of its ability to provide precise, high-resolution 3D images. However, a challenge in space-based lidar imaging systems is the issue of angular jitter. This issue is worsened by the long distances involved in space-to-ground imaging, causing a blurring effect that hampers the quality and clarity of the obtained images. Previous strategies to counteract the blurring effects of angular jitter—like mechanical isolation, advanced IMUs, star trackers, and auxiliary passive optical sensors—are far from ideal. Not only do these solutions tend to increase the size, weight, power consumption, and cost of the entire satellite and imaging systems, they also have their limitations in completely eradicating the disruptions caused by angular jitter.

Technology Description

This specialized lidar imaging system is designed for use in satellite technology. It leverages recent advances in compact fiber lasers and single-photon-sensitive Geiger-mode detector arrays, enabling feasible space-based ground imaging. A unique feature of this system is its ability to compensate for the problem of angular jitter, which often disturbs the accuracy and clarity of space-based 3D lidar data because of the long distances involved. The system uses an innovative method of estimating the 2-axis jitter time series directly from the lidar data, in tandem with the estimation of a single-surface model of the ground to offset it. What sets this technology apart is its unique approach to mitigating the impact of angular jitter  without resorting to costly and cumbersome solutions like mechanical isolation, advanced IMUs, star trackers, or auxiliary passive optical sensors. By applying an Expectation Maximization process, the system enhances the signal and background detections while maximizing the joint posterior probability density of the jitter and surface states. This processing strategy results in reduced blurring equal to the optical diffraction limit.