You mean like a signal added to combat / detect aliasing? I'm not sure how that would work. I know HP did something like this, but they did it by introducing a known jitter into the time base. I don't think it could work by merely adding a signal, you need to interact with the incoming signal in the time domain to do something about aliasing. I have no experience with these older CCD-based ones, but the later TDS'es from the 90s could do aliasing. The time base jitter thing was probably patented by HP.
Yeah, this is a well known technique for boosting resolution.
For example: You add a dithering signal which can be processed out. If the signal has the right properties (for example, random but evenly distributed noise bounded to one LSB), you can then average out multiple samples to get more effective resolution than the ADC has. The additional number of bits scales something like 2^n samples, although if you don’t take sufficient samples this mainly just reduces your SNR. It also requires a periodic input.
However you can also pull similar tricks in the time domain or using simultaneous sampling with multiple ADCs. You can also interleave slower ADCs with a phase shift. This produces stitching artifacts unless you average them out though because ADCs generally are not well matched at the limits. You can bin or calibrate this out somewhat if you can characterize the error.
You can do a similar thing in the frequency domain if the ADC sample window is narrow enough but it has arguably the worst artifacts. Lo-pass the first ADC around N/2. The second ADC use a bandpass from N/2 upto N. The third is N upto 3N/2 etc… but the fourier transform will have a bunch of junk at the stitching points.
Or you can take the sampling scope approach using a fast but low sample rate ADC and many triggers.
I’ve seen most of these done on commercial instruments if you dig into the settings. Some of them you can see in normal operation (like the stitching in the frequency domain).
But I think the other poster was suggesting the first case applies - if you think about it there are certain periodic signals you can add instead of a random signal. That has the advantage of limiting SNR degradation and can also be filtered out easier/ detected i n the data.
