I have two radios sampling simultaneously, and I am trying to time-align their two signals (they will always start sampling at slightly different times with random delays due to hardware differences). I have a circuit that automatically switches between the antennas and nothing at a set interval, and I'm trying to use the transitions between signal and silence to determine how to time-align the two signals. I tried using cross correlation to find the shift between the two signals, but it's not getting the correct alignment (it's very off). I suspected it was due to the signals being too noisy, so I smoothed them both and tried to make their amplitudes similar, but it still didn't get the right alignment.

Here's a screenshot of an example of the two signals. The image is zoomed in to the region where the circuit switches the radios from nothing to the antennas, and I would like to align the two signals such that these transitions match up.

[![Two signals](https://i.stack.imgur.com/UttXA.png)](https://i.stack.imgur.com/UttXA.png)

EDIT:
Here are text files of two more signals that I'm trying to align:
[s0.txt](https://drive.google.com/file/d/1IK_DQ_-a_y167FAfhZyOyaozfweM692y/view?usp=sharing) [s1.txt](https://drive.google.com/file/d/17ucoLobzC5Yk3mi6GxogNpyjN7hnrg8I/view?usp=sharing). When they're aligned, they look like this:

[![enter image description here](https://i.stack.imgur.com/uuds1.png)](https://i.stack.imgur.com/uuds1.png) 

(note that these are not the same signals in the previous picture). I found the optimal delay to be 1069 for the first signal. I used other methods to find the delay (described in a comment below), but I would like to reproduce this result using cross correlation as I believe it will prove to be more reliable / precise.