Name
Abstract | ||
|---|---|---|
Light Detection and Ranging (LIDAR) plays an important role in remote sensing because of its ability to provide high-resolution measurements of 3D structure. For time-sensitive airborne missions, fast onboard processing of LIDAR data is desired and yet difficult to achieve with traditional embedded CPU solutions due to the computational requirements. FPGAs have the potential to speed up processing by employing multi-level parallelism, but their use in LIDAR processing has typically been limited to data capture due to the difficulties associated with efficiently migrating LIDAR processing algorithms to FPGAs. We demonstrate two equivalent FPGA designs for coordinate calculation of LIDAR data written using different languages (VHDL and MATLAB-based AccelDSP), comparing their performance and productivity. For the VHDL design, a ~14× speedup is obtained over an Opteron processor on a Cray XD1 system. In addition, a recently proposed performance prediction methodology is employed, and the accuracy of its pre-implementation predictions is analyzed. |
Year | Venue | Keywords |
|---|---|---|
2008 | ERSA | data capture,real time,high resolution,remote sensing |
Field | DocType | Citations |
Field-programmable gate array,Real-time computing,Lidar,Ranging,Automatic identification and data capture,VHDL,Lidar data,Performance prediction,Geography,Embedded system,Speedup | Conference | 6 |
PageRank | References | Authors |
0.58 | 4 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kuei-tsung Shih | 1 | 6 | 0.58 |
| Arjun Balachandran | 2 | 6 | 0.58 |
| Karthik Nagarajan | 3 | 77 | 7.23 |
| Brian Holland | 4 | 92 | 7.81 |
| Clint Slatton | 5 | 79 | 18.56 |
| Alan D. George | 6 | 6 | 0.58 |