Please look at the following below links which may help you in your analysis:

https://iopscience.iop.org/article/10.1088/1361-6501/ab24a1/pdf

Thanks

That kind of depends on what the data looks like, but I think a simple copy-paste approach is your best bet. combining the two output files into one.

The things you should consider before doing this are:

1. Is the data really from the same sample? Did you take the exact same material and measure twice, because sample-to-sample differences can occur (depending on what you measure)

2. Is the data, roughly, in the same scale? If not it may be wise to normalize before combining

I have to ask - why would you want to combine both into one spectrum? Wouldn't it make more sense just to provide both?

You have two major options

First

Just concatenate the matrix A and B. But to do this you need to normalize background to ensure rigth signal offset between detectors.

Second

Extract first 20 principal components from sensor A and sensor B, concatenate and go for machine learning/chemometrics analysis.