I am trying to use fourier transform based approach for near field to farfield transformation of E-fields. I have my sampling plane in xy with following coordinates -120mm <X<120mm and -120mm<Y<120mm. My operating frequency is 2.5 GHz to 4GHz. I have taken fourier transform for the E-field complex data and have converted my FFT indices into wavenumbers. In order to do the Near field to farfield transformation, I have to then interpolate the FFT values to the stationary observation points in spherical coordinates. So, i used interp2 function to do this. The following is my code for this interpolation.

Ex_interp(:,:,i)= interp2(Fx_grid1, Fy_grid1, Exff_z0(:,:,i), kx(:,:,i), ky(:,:,i), ‘spline’,0);
Ey_interp(:,:,i)= interp2(Fx_grid1, Fy_grid1, Eyff_z0(:,:,i), kx(:,:,i), ky(:,:,i), ‘spline’,0);

i= number of frequecies in my code. The Fx grid1 and Fy grid are the wavenumbers in cartesian coordinates already in gridded format. Their size is 1024 x 1024. (FFT size=1024). The kx and ky are the observation points in cartesian coordinates calculated from the spherical coordinates. The code works for me and it gives a farfield which closely matches the data from a Electromagnetic solver. But, the catch is that it matches only at lower frequencies, and as the frequency increases, the spline fit is giving me lot of inflections in my antenna beam pattern. I beleive this is related to the interpolation error. Because, when i change the interpolation type to ‘cubic’ it gives lot of ripples in my beam pattern. So, basically with the different types of interplation the final beam varies drastically at higher frequencies. I did not find any method better than spline in interp2 function. I do not know how to solve this issue. Are there any other methods available for 2D interpolation where we can also control the spline fitting parameters? Looking for some suggestions here.. I am new to these interpolation techniques, so i am not able to understand the problem completely here.I am trying to use fourier transform based approach for near field to farfield transformation of E-fields. I have my sampling plane in xy with following coordinates -120mm <X<120mm and -120mm<Y<120mm. My operating frequency is 2.5 GHz to 4GHz. I have taken fourier transform for the E-field complex data and have converted my FFT indices into wavenumbers. In order to do the Near field to farfield transformation, I have to then interpolate the FFT values to the stationary observation points in spherical coordinates. So, i used interp2 function to do this. The following is my code for this interpolation.

Ex_interp(:,:,i)= interp2(Fx_grid1, Fy_grid1, Exff_z0(:,:,i), kx(:,:,i), ky(:,:,i), ‘spline’,0);
Ey_interp(:,:,i)= interp2(Fx_grid1, Fy_grid1, Eyff_z0(:,:,i), kx(:,:,i), ky(:,:,i), ‘spline’,0);

i= number of frequecies in my code. The Fx grid1 and Fy grid are the wavenumbers in cartesian coordinates already in gridded format. Their size is 1024 x 1024. (FFT size=1024). The kx and ky are the observation points in cartesian coordinates calculated from the spherical coordinates. The code works for me and it gives a farfield which closely matches the data from a Electromagnetic solver. But, the catch is that it matches only at lower frequencies, and as the frequency increases, the spline fit is giving me lot of inflections in my antenna beam pattern. I beleive this is related to the interpolation error. Because, when i change the interpolation type to ‘cubic’ it gives lot of ripples in my beam pattern. So, basically with the different types of interplation the final beam varies drastically at higher frequencies. I did not find any method better than spline in interp2 function. I do not know how to solve this issue. Are there any other methods available for 2D interpolation where we can also control the spline fitting parameters? Looking for some suggestions here.. I am new to these interpolation techniques, so i am not able to understand the problem completely here. I am trying to use fourier transform based approach for near field to farfield transformation of E-fields. I have my sampling plane in xy with following coordinates -120mm <X<120mm and -120mm<Y<120mm. My operating frequency is 2.5 GHz to 4GHz. I have taken fourier transform for the E-field complex data and have converted my FFT indices into wavenumbers. In order to do the Near field to farfield transformation, I have to then interpolate the FFT values to the stationary observation points in spherical coordinates. So, i used interp2 function to do this. The following is my code for this interpolation.

Ex_interp(:,:,i)= interp2(Fx_grid1, Fy_grid1, Exff_z0(:,:,i), kx(:,:,i), ky(:,:,i), ‘spline’,0);
Ey_interp(:,:,i)= interp2(Fx_grid1, Fy_grid1, Eyff_z0(:,:,i), kx(:,:,i), ky(:,:,i), ‘spline’,0);

i= number of frequecies in my code. The Fx grid1 and Fy grid are the wavenumbers in cartesian coordinates already in gridded format. Their size is 1024 x 1024. (FFT size=1024). The kx and ky are the observation points in cartesian coordinates calculated from the spherical coordinates. The code works for me and it gives a farfield which closely matches the data from a Electromagnetic solver. But, the catch is that it matches only at lower frequencies, and as the frequency increases, the spline fit is giving me lot of inflections in my antenna beam pattern. I beleive this is related to the interpolation error. Because, when i change the interpolation type to ‘cubic’ it gives lot of ripples in my beam pattern. So, basically with the different types of interplation the final beam varies drastically at higher frequencies. I did not find any method better than spline in interp2 function. I do not know how to solve this issue. Are there any other methods available for 2D interpolation where we can also control the spline fitting parameters? Looking for some suggestions here.. I am new to these interpolation techniques, so i am not able to understand the problem completely here. fft, image processing, antenna, interpolation, curve fitting, function, mathematics MATLAB Answers — New Questions

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