Superresolution techniques for time-domain measurements with a network analyzer

Superresolution techniques for time delay estimation are proposed and applied to frequency-domain data measured with a network analyzer. A MUSIC (multiple signal classification) algorithm preprocessed by spatial smoothing is used. The spatial smoothing preprocessing is performed to destroy signal coherence, and the decorrelation performance is examined in detail. The expression which gives an individual response is given. Using this expression, it is possible to eliminate unwanted signals that appear as ripples in the frequency domain. Experimental results show that the frequency bandwidth required by the MUSIC algorithm to resolve distinct time-domain responses and eliminate unwanted signals is much narrower than that required by the FFT (fast Fourier transform). Thus, the MUSIC algorithm is applicable to the time-domain measurements with the network analyzer and has much higher resolution capability than the conventional FFT techniques. The MUSIC algorithm is one of the most promising methods of enhancing the accuracy of measurement for narrowband devices such as antennas