Speaker
Description
The increasing need for miniaturised climate observation instruments on stratospheric balloons and research
aircraft, combined with increasingly complex measurement tasks, higher data rates, and the growing preva-
lence of low-cost nanosatellite missions, drives the need for a new generation of reliable control and processing
units. These units must minimize mass, volume, and power consumption while supporting real-time data
processing, reduction, and compression.
A modular and programmable data acquisition and processing platform was developed. This platform can
handle two different sensors and provides the basis for real-time preprocessing of the captured sensor data
with subsequent data reduction, e.g., through pixel binning and/or data compression. In a first application,
the preprocessing of 2D infrared detector data from a Michelson interferometer was implemented. From
images of 48x128 pixels and a frame rate of approximately 5000 fps, more than 6400 interferograms must be
processed in parallel. In a first step, level 0 processing - consisting of non-linearity correction, spectral off-axis
calibration, and resampling of the data - was implemented in VHDL. The optimal parameters for the interpo-
lation kernel, the abscissa calculation, and the data formats were analyzed in advance using a Python model.
This contribution highlights the parameter analysis, functional VHDL blocks, and resource utilization. Initial
results demonstrate the accuracy and efficiency of the VHDL implementation, confirming the platform’s
suitability for high-speed, real-time preprocessing in compact, low-power environments.
| Minioral | No |
|---|---|
| IEEE Member | No |
| Are you a student? | No |