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Function minimization in LV

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i am currently facing the following problem:

i have coordinates of points lying on a 2D plane, the coordinates are collected in two different reference frames which are rotated by an angle which is not exactly known.

i would like to extract the angle by minimization of a function built on the basis of the point coordinates and the rotation parameter, to be minimized with respect to the rotation parameter (simple chi2 built on the metric distance).

being a non-linear function in the rotation angle parameter, i feel i should use the non-linear levenberg Marquardt fit routines (under LV 7.1 professional).

However, these function require a set of 1D independent variables, while i have a 2D independent variable set.

to complicate, even the translation beween the two frames is not exactly known, so the parameter space is three dimensional (but this should not be a problem in principle).

Anybody that has an idea if i could retrieve packages/examples that do the job, or if there are ways to cheat the fitting routine? i wonder if the function should have derivatives in the independent variables set.

thanks indeed,

Best Regards

Piero Zucchelli

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