SIP is a simplified bivariate (x,y or u,v in pairs) polynomial, reduced to terms where p+q <= order (A order or B order). A and B coefficients are generated, for each axis separately (A for x and B for y, but using BOTH input coordinates for correction calculation), by least squares fit to expected true coordinates (yielded from catalog). This is achieved in AN by using libraries, like GSL and CBLAS, but anyone can do the same in Matlab/Octave, or Python+NumPy. Kudos to Dustin, for a really great implementation in AN.
Here is 2008. paper that describes the concept:
https://fits.gsfc.nasa.gov/registry/sip/SIP_distortion_v1_0.pdf
BR,
DD