Full-Waveform LIDAR Recovery at Sub-Nyquist Rates
| dc.contributor.advisor | Creusere, Charles D. | en_US |
| dc.contributor.author | Castorena, Juan | |
| dc.date.accessioned | 2015-10-14T16:44:44Z | en |
| dc.date.available | 2015-10-14T16:44:44Z | en |
| dc.date.issued | 2013-10 | en |
| dc.identifier.issn | 0884-5123 | en |
| dc.identifier.issn | 0074-9079 | en |
| dc.identifier.uri | http://hdl.handle.net/10150/579674 | en |
| dc.description | ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV | en_US |
| dc.description.abstract | Third generation LIDAR full-waveform (FW) based systems collect 1D FW signals of the echoes generated by laser pulses of wide bandwidth reflected at the intercepted objects to construct depth profiles along each pulse path. By emitting a series of pulses towards a scene using a predefined scanning patter, a 3D image containing spatial-depth information can be constructed. Unfortunately, acquisition of a high number of wide bandwidth pulses is necessary to achieve high depth and spatial resolutions of the scene. This implies the collection of massive amounts of data which generate problems for the storage, processing and transmission of the FW signal set. In this research, we explore the recovery of individual continuous-time FW signals at sub-Nyquist rates. The key step to achieve this is to exploit the sparsity in FW signals. Doing this allows one to sub-sample and recover FW signals at rates much lower than that implied by Shannon's theorem. Here, we describe the theoretical framework supporting recovery and present the reader with examples using real LIDAR data. | |
| dc.description.sponsorship | International Foundation for Telemetering | en |
| dc.language.iso | en_US | en |
| dc.publisher | International Foundation for Telemetering | en |
| dc.relation.url | http://www.telemetry.org/ | en |
| dc.rights | Copyright © held by the author; distribution rights International Foundation for Telemetering | en_US |
| dc.subject | LIDAR | en |
| dc.subject | full-waveform | en |
| dc.subject | sub-Nyquist sampling | en |
| dc.subject | overlapping windows | en |
| dc.title | Full-Waveform LIDAR Recovery at Sub-Nyquist Rates | en_US |
| dc.type | text | en |
| dc.type | Proceedings | en |
| dc.contributor.department | New Mexico State University | en |
| dc.identifier.journal | International Telemetering Conference Proceedings | en |
| dc.description.collectioninformation | Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection. | en_US |
| refterms.dateFOA | 2018-08-18T16:46:22Z | |
| html.description.abstract | Third generation LIDAR full-waveform (FW) based systems collect 1D FW signals of the echoes generated by laser pulses of wide bandwidth reflected at the intercepted objects to construct depth profiles along each pulse path. By emitting a series of pulses towards a scene using a predefined scanning patter, a 3D image containing spatial-depth information can be constructed. Unfortunately, acquisition of a high number of wide bandwidth pulses is necessary to achieve high depth and spatial resolutions of the scene. This implies the collection of massive amounts of data which generate problems for the storage, processing and transmission of the FW signal set. In this research, we explore the recovery of individual continuous-time FW signals at sub-Nyquist rates. The key step to achieve this is to exploit the sparsity in FW signals. Doing this allows one to sub-sample and recover FW signals at rates much lower than that implied by Shannon's theorem. Here, we describe the theoretical framework supporting recovery and present the reader with examples using real LIDAR data. |
