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An Efficient 256-Track Beam Steering Lidar Using Wavelength-Tuning for Topography Swath Mapping from Space

  • Guangning Yang,
  • David J. Harding,
  • Jeffrey R. Chen,
  • Hui Li,
  • Erwan Mazarico,
  • Brooke Medley,
  • Mark A. Stephen,
  • Xiaoli Sun,
  • Wei Lu,
  • Kenji Numata,
  • Xiaozhen Xu,
  • Kenneth J. Ranson,
  • Philip W. Dabney,
  • James Mackinnon,
  • Hannah Tomio

摘要

We report development progress of a Concurrent Artificially-intelligent Spectrometry and Adaptive Lidar System (CASALS) for topography swath mapping from space. The beam scanning was demonstrated by fast wavelength tuning and grating dispersion, and near quantum limited performance was measured at 1550 nm. A 1040 nm CASALS prototype is being developed for Earth science. The laser is rapidly tuned across 13 nm and carved into 2-ns pulses to scan 256 tracks. At the grating-spectrometer-based receiver, returns from each track are filtered spatially and spectrally and imaged onto a HgCdTe APD-array. The detected signals are time-division-multiplexed to only two high-speed analog-to-digital converters and range-gated to reduce data volume. The design can be adapted for gapless sub-meter resolution lunar swath mapping at 1550 nm. 3D imaging of landing site with 4 M footprints per second is enabled by inserting a 4-Hz 2D steering mirror. The lidar can also perform navigation measurements up to 100 km.