13 May 2016 Real-time, mixed-mode computing architecture for waveform-resolved lidar systems with total propagated uncertainty
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Abstract
We have developed a prototype real-time computer for a bathymetric lidar capable of producing point clouds attributed with total propagated uncertainty (TPU). This real-time computer employs a “mixed-mode” architecture comprised of an FPGA, CPU, and GPU. Noise reduction and ranging are performed in the digitizer’s user-programmable FPGA, and coordinates and TPU are calculated on the GPU. A Keysight M9703A digitizer with user-programmable Xilinx Virtex 6 FPGAs digitizes as many as eight channels of lidar data, performs ranging, and delivers the data to the CPU via PCIe. The floating-point-intensive coordinate and TPU calculations are performed on an NVIDIA Tesla K20 GPU. Raw data and computed products are written to an SSD RAID, and an attributed point cloud is displayed to the user. This prototype computer has been tested using 7m-deep waveforms measured at a water tank on the Georgia Tech campus, and with simulated waveforms to a depth of 20m. Preliminary results show the system can compute, store, and display about 20 million points per second.
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Robert L. Ortman, Robert L. Ortman, Domenic A. Carr, Domenic A. Carr, Ryan James, Ryan James, Daniel Long, Daniel Long, Matthew R. O'Shaughnessy, Matthew R. O'Shaughnessy, Christopher R. Valenta, Christopher R. Valenta, Grady H. Tuell, Grady H. Tuell, } "Real-time, mixed-mode computing architecture for waveform-resolved lidar systems with total propagated uncertainty", Proc. SPIE 9832, Laser Radar Technology and Applications XXI, 98320H (13 May 2016); doi: 10.1117/12.2224264; https://doi.org/10.1117/12.2224264
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