Fast calibration during and after data acquisition
Before the measurement data can be analyzed, they must be calibrated. This normally happens after the data acquisition, but can also happen during the process, e.g. if certain events in the data need to be reacted to immediately.
There are also cases where the data rate is so high that not all data can be stored. In order to find out which part of the data most probably contains no signals and therefore does not need to be stored, the calibration must already be carried out during data acquisition. Since high data rates do not allow complex calculations, the algorithms for calibration must be highly optimized and tailored to the problem.
Sometimes the calibration parameters must also be determined from the data itself, in the worst case during data acquisition.
In the following, an algorithm is presented that determines the baseline (zero line) without any model during data acquisition. At any time only the current data point and all previous data points are known.
Robust baseline estimation
One problem in signal processing is a variable baseline. The RABE (Robust Adaptive Baseline Estimation) algorithm, developed by 256.systems, estimates the baseline during data acquisition so that it can be subtracted immediately. Outliers, jumps, and trends are identified and handled separately so that they do not distort the baseline estimate.
Example:
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This and other robust and fast calibration algorithms can be provided by 256.systems.