Tech Briefs

Data Acquisition and Processing Software — DAPS

DAPS was designed to support the DAWN-AIR project participating in the Genesis and Rapid Intensification Processes (GRIP) hurricane campaign. It controls the data acquisition system consisting of a scanner that directs the lidar beam, an inertial navigation system/GPS (INS/GPS) unit for monitoring aircraft motion, a DSP module, and serial and video modules while acquiring and processing lidar data in real time. DAPS was optimized to meet the project requirement: acquiring and processing more than 550,000 samples per second. DAPS was capable of managing such extensive computational loads without experiencing a single incident of crash or system failure during the entire 130 flight hours of the GRIP mission.

The latest wind profiling algorithm accurately estimates the horizontal wind speed and direction. It is robust enough to identify abrupt changes in the horizontal wind parameters that are difficult to be detected by other conventional methods. Some of the unique features of DAPS and the latest data processing algorithm are as follows:

1. DAPS can operate both in real time and offline while performing full tasks faster than 10 Hz of execution rate.
2. DAPS has informative data displays such as the Doppler shift and the power distribution of line of sights, horizontal and vertical wind profiles, and color-coded history displays of wind profiles. It also displays important user inputs and real-time GPS data.
3. DAPS is smart software that is capable of automatic error correction and calibration of the scanner and the digitizer.
4. DAPS is robust and is capable of longhaul operations without an incident of system error or crash.
5. The latest wind profiling algorithm can produce robust horizontal wind parameters.
6. The algorithm has smart routines to increase the signal-to-noise ratio and effective INS/GPS data interpretation and application.
7. The algorithm runs at the minimal error resolution of 1 m/s in wind speed with 512-FFT.

This work was done by Jeffrey Beyon of Langley Research Center. LAR-18033-1