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Prediction of topographic and bathymetric measurement performance of airborne low-SNR lidar systems

Posted on:2010-06-16Degree:Ph.DType:Dissertation
University:University of FloridaCandidate:Cossio, TristanFull Text:PDF
GTID:1448390002973385Subject:Engineering
Abstract/Summary:
Low signal-to-noise ratio (LSNR) lidar (light detection and ranging) is an alternative paradigm to traditional lidar based on the detection of return signals at the single photoelectron level. The objective of this work was to predict low altitude (600 m) LSNR lidar system performance with regards to elevation measurement and target detection capability in topographic (dry land) and bathymetric (shallow water) scenarios.;A modular numerical sensor model has been developed to provide data for further analysis due to the dearth of operational low altitude LSNR lidar systems. This simulator tool is described in detail, with consideration given to atmospheric effects, surface conditions, and the effects of laser phenomenology. Measurement performance analysis of the simulated topographic data showed results comparable to commercially available lidar systems, with a standard deviation of less than 12 cm for calculated elevation values. Bathymetric results, although dependent largely on water turbidity, were indicative of meter-scale horizontal data spacing for sea depths less than 5 m.;The high prevalence of noise in LSNR lidar data introduces significant difficulties in data analysis. Novel algorithms to reduce noise are described, with particular focus on their integration into an end-to-end target detection classifier for both dry and submerged targets (cube blocks, 0.5 m to 1.0 m on a side). The key characteristic exploited to discriminate signal and noise is the temporal coherence of signal events versus the random distribution of noise events. Target detection performance over dry earth was observed to be robust, reliably detecting over 90% of targets with a minimal false alarm rate. Comparable results were observed in waters of high clarity, where the investigated system was generally able to detect more than 70% of targets to a depth of 5 m.;The results of the study show that CATS, the University of Florida's LSNR lidar prototype, is capable of high fidelity (decimeter-scale) coverage of the topographic zone with limited applicability to shallow waters less than 5 m deep. To increase the spatial-temporal contrast between signal and noise events, laser pulse rate is the optimal system characteristic to improve in future LSNR lidar units.
Keywords/Search Tags:Lidar, LSNR, Noise, System, Signal, Performance, Topographic, Detection
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