|Institution:||San Diego State University|
|Full text PDF:||http://hdl.handle.net/10211.3/137643|
Spectral correlators enable the imaging of an observed region of space in the radio frequency spectrum. However, certain solar phenomena cannot be observed from Earth because their electromagnetic signatures cannot penetrate the Earth's ionosphere. Therefore, they must be observed from space with a satellite-mounted spectral correlator. Such a space-based instrument would be subject to power consumption constraints. With a strategic selection of its channelizer component, the spectral correlator may be designed to consume minimal power. This thesis presents and evaluates the workload of three channelizer architectures: one based on a cascaded integrator-comb (CIC) filter, one based on a cascade of half band filters, and one based on a polyphase filter bank (PFB). Each architecture is presented as its simulation in MATLAB under separate stimulation by an impulse and a pair of tones. Its processing time for an entire spectrum is also measured by the simulation,which provides a benchmark for the workload analysis. Workload analysis is expressed as the number of operations required to deliver output samples with respect to sample rate reductions accompanying the bandwidth reduction process. Presentation and evaluation of the PFB-based architecture suggests that a reduction in its workload is possible via optimization of its inverse fast Fourier transform(IFFT). Conventionally, the IFFT is implemented with the Cooley-Tukey algorithm. While the divide-and-conquer approach of this algorithm provides significant economy over direct calculation of the inverse discrete Fourier transform (IDFT), the IFFT can be further optimized by the use of the Good-Thomas algorithm. Unlike the Cooley-Tukey algorithm, the Good-Thomas algorithm does not use twiddle factors, which provides further workload reduction. The files containing the code for these simulations are on a DVD. The DVD, an appendix to the thesis, is available for viewing at the Media Center of Library & Information Access.