I measure a network's transfer function using a network analyzer and therefore have a set of complex data points, representing the network's gain and phase. I wish to fit a continuous, rational transfer function to my measured data to create a model of my network. To find a discrete-time model, there is the "Frequency Domain Least Squares" algorithm:
Several months ago, I found a PDF which presented a very similar method to estimate a continuous transfer function, but I don't remember where it is nor do I remember its name. I only remember that it was also a simple least squares algorithm as in the above link. Does someone have a hint for this?
Update: Meanwhile I was able to recover the paper I mentioned. It is called 'Practical Transfer Function Estimation and its Application to Wide Frequency Range Representation of Transformers'. In my application, I am not dealing with a transformer but with some other passive electrical network involving RLC components, and I try to fit a transfer function to that. The network analyzer gives me some complex data for logarithmically spaced frequencies. I tried to use the method presented in the paper, but since my frequencies range from several Hz to several 100 MHz, the algorithm is unable to converge because the matrix A involves \$\omega\$, \$\omega^2\$, \$\omega^3\$ and so on - which leads to an ill-conditioned equation system, and therefore it cannot be solved. I wonder whether there are better algorithms than this, or whether this algorithm could be used, though, perhaps with some pre-processing of my frequency data.
Link to the paper I mentioned: https://ieeexplore.ieee.org/document/252689