DINO Calibration

The mapping of DINO power back to amplitude of the oscillation is frequency dependent. So the following procedure must be repeated for a range of frequencies.

Procedure

1. Generate a floating point random noise frame to simulate a clean bias. This array should have pst/sst more columns than the final image size, where pst and sst are the parallel and serial shift times, so that each element in the array represents an equal time interval during readout.

2. Generate a floating point, continuous oscillation vector of a given amplitude and of length (X+(pst/sst))*Y, where X and Y are the number of columns and rows in the final image. This vector represents noise induced during readout time.

3. Sum the two arrays element by element. This calculation is done in floating point arithmetic to prevent loss of precision.

4. Digitize the result of the addition by converting it to an integer type.

5. Trim the result to the proper image size by extracting elements zero to X-1 from each row.

6. Hand off this image to DINO for processing.

7. Record the frequency and amplitude of the input signal and frequency and power identified by DINO.

8. Repeat these steps for a range of amplitudes.

Results

A second order polynomial was fit to the data compiled for each detector and frequency.

Fit = a0 + a1 x + a2 x²

The results are organized in the following table:

HRC	WFC
60 Hz	153 Hz
larger format: GIF | PostScript	larger format: GIF | PostScript
420 Hz	460 Hz
larger format: GIF | PostScript	larger format: GIF | PostScript