Slap a MEMS gyroscope on that bad boy. https://www.vectornav.com/resources/inertial-navigation-prim...
That's actually quite doable. The problem is that when the environment changes you will drift and then it becomes very hard to distinguish between actual heading changes and external influences. But if you can make a full spin you can (usually!) obtain magnetic North again. For drones this is a problem because they will drift and spin all the time. When you're on the ground and you have encoders on your axis you can do a lot better than with a drone.
RTK GPS is very nice to have but may not always be available (GPS itself may not always be available). I have some stuff in the works just for that. It does well in the lab but I still have (serious) problems in the field.
gps also won't give you orientation really anyway, and indeed, is mostly outdoors, and rtk is needed for this resolution but also rather inaccessible to amateurs.
If you're working on indoor navigation, that's very cool, when I used to do it, in my context it was easier because we controlled the environment of the robots (markers on walls of a known colour type stuff). We also explored passive radar type arrangements for picking up wifi repeaters, but it became complicated to eg. ignore bluetooth.
Though in the case of this video, the wii sensor bar style approach seems fine, assuming you control reflections
It's insanely complex stuff, I've had to do a lot of re-studying math and this whole project has given me more respect than I already had for the engineers behind modern positioning systems.