 Quote by whiskeygirl
Ok, so I'm trying to find the vectors v1 and v2 that point from the positions to a sighting. It says the form must be in <a,±1,b> form, and calculations to 3 significant digits. Position 1: (3500, 450, 800) and the sighting is 30° south of west, and 0.83° above the horizontal. Position 2: (200, 1650, 600) and the sighting is due south, 4.70° above the horizontal.
I honestly have no idea where to start, but I was thinking maybe it would be something along the lines of the magnitude of position 1 which is 3,618.356, and do that multiplied by cos30°, and then sin30°, then I'm not sure what to do with the 0.83* above the horizontal part. But, I'm not sure.
Help please!
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If a = (3500,450,600) and b = (200,1650,600) and if p = first sight-line vector (defined by the first angles you gave) and if q = second sight-line vector, you get two lines in 3-space. These are L1: x1(s) =a + s*p and L2: x2(t) = b + t*q, where s and t are scalars. As s and t range over the real line, x1 and x2 trace out two lines, which are the estimated sightlines that pass through the object you want to locate. The intersection of these lines gives the position of the object; this will happen if the three simultaneous equations a1+s*p1 = b1 + t*q1, a2+s*p2 = b2+t*q2 and a3+s*p3 = b3+t*q3 have a consistent solution (s,t).
However, because of experimental (measurement) errors and roundoff, the two estimated lines L1 and L2 may not intersect in practice. In that case it makes sense to find the two points (one on L1 and the other on L2) that are as close as possible to one another, that is, to minimize the distance ||x1(s) - x2(t)||. That gives an unconstrained optimization problem in s and t. If the resulting two points are very close together (using some definition of 'very close') then it makes some kind of sense to use a point close to them (for example, one of them, or their average, or something similar) as your estimate of the object's location.
RGV