It scales differently, though. The precise MEA is calculated once (in each direction) no matter how many data points you're aiming with. If you're trying to use 500 data points and aiming with DVs, that's 500 projections for out of bounds checking.
Diamond's 1v1 gun used to use DVs, but I saw a big jump in accuracy when I finally caved and switched to GFs. Still use 'em in melee, though, and think they're very cool.
Imagine 2 DVs, one trying to go as far as possible clockwise and the other counter-clockwise. Ignoring walls, the resulting angles will match asin(8.0/Vb). But when near walls, if we adjust those 2 DVs, like wall sticks are adjusted in wall smoothing, we get a more accurate MEA, using non-iterative trigonometry only.
I looked at this, the problem it has is that it doesn't take into account that as the angle changes the wave will hit sooner. You could account for this I guess, but the iterative predictive methods are fast enough, I think.
Something like non-iterative linear targeting can account for varied bullet travel times. But the resulting code will probably be very bulky, like most non-iterative methods.
Well, I didn't use a noniterative method and I actually don't know how I could, but I now use a "binary search" for attack angles to get a precise MEA that doesn't take heading or velocity into account. I may make a page for it with diagrams, but for now you would just need to look at the code to see what I mean.
I modeled the problem as 2 intersecting circunferences (bot moving and bullet moving) and 1 intersecting line (wall). There are at most 2 points where the 3 intersect. Then repeating it for all 4 walls for 8 escape points. Add the 2 escape points from classic MEA (ignoring walls) for 10 escape points. Do some out of bounds checking on all points and then find which remaining 2 gives the widest MEA.
There are some loops but they are fixed and independent from bullet travel time. Making it very cheap to calculate.
I can post the algorithm later.