@Kent Dawson yeah this is actually a pretty solid use case for the barometer — for low-altitude work it can genuinely complement GNSS vertical, especially since GNSS height accuracy is typically 2-3x worse than horizontal and gets noisy below maybe 10-15m AGL.
The thing to be aware of is that raw barometric altitude has a slow drift problem tied to weather — ambient pressure shifts over a flight session as fronts move through, so if you just set a ground reference at takeoff and fly for 20+ minutes, you can accumulate meaningful error. The standard approach is to treat it as a relative altitude sensor rather than absolute — you calibrate to ground level at the start, use it for short-term precision and rate-of-change (which it's great at, especially with the 18Hz-ish update rate you're getting), and let GNSS handle the longer-term absolute reference.
For a fusion approach, a simple complementary filter works surprisingly well — barometer handles the fast vertical dynamics and high-frequency noise rejection, GNSS keeps it honest over time on the absolute value. If you want to get more rigorous about it, a Kalman filter with both as inputs and maybe the accelerometer Z-axis from the IMU as the third input is the proper way to do it, and you've got all those sensors on the one board which makes that pretty clean to implement.
Biggest practical gotcha: if your platform generates any heat near the sensor, you'll see pressure drift from temperature effects — worth checking if the readings stay stable while motors are running versus stationary.
