The effects of phase errors on the super spatially variant apodization algorithm

The effects of phase errors on the one-dimensional Super Spatially Variant Apodization (SSVA) spectral analysis algorithm developed in [I] and [4] were analyzed. The resolution and noise suppression capabilities of the new algorithm were also analyzed. The algorithm was implemented using the C programming language. The analysis used quadratic, third order, and fourth order Legendre polynomials to determine the performance of the SSVA algorithm on phase errors. Special signals were generated and used to determine the resolution, the noise suppression capabilities, and the detectability oft4e SSVA algoritlm1. The results of using the SSVA algorithm were compared with the results of using other techniques of spectral analysis, such as windowing and the SV A algorithm. C programs were developed to implement the windowing technique and the SV A algorithm. For windowing, the Taylor amplitude weighting window was used. Plots of the performance characteristics of the SSV A algorithm on signals with quadratic, third order, and fourth order errors were generated for different center-to-end degrees of phase errors. Plots of the performance characteristics of the SV A algorithm on signals with phase errors were also included for comparison.