Spherical near to far field transformation

AI Thread Summary
Transforming an antenna's nearfield pattern measured in spherical coordinates (f(theta, phi)) to obtain the farfield pattern involves complex mathematical techniques. The challenge lies in the spherical coordinate system, which differs from the 2D Fourier transform used in planar measurements. Participants in the discussion emphasize the need for specialized methods or algorithms tailored for spherical data. Suggestions include exploring spherical harmonics or numerical integration techniques to facilitate the transformation. Overall, the conversation highlights a gap in accessible resources for this specific transformation process.
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Hi all,

Suppose I have measured an antenna's nearfield pattern and have a set of data f(theta, phi), where theta and phi are spherical coordinates, at a distance r from the antenna (we'll assume that the antenna is a point source to make it easier). How would I go about transforming this data to get the antenna's farfield pattern? I've tried searching the net for this but haven't found anything useful for spherical measurements. I understand that planar measurements use a 2D Fourier transform but the spherical coordinates complicate things a bit.

FYI, I have a degree in mathematics but it's been a while now so I might be a little rusty. :smile:
 
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I hate to bump a post, but does anyone have any thoughts or ideas?
 

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