Robust techniques in array signal processing
Lei Lei · 2009
Array signal processing, which collects and combines signals from an array, can obtain high spatial discrimination and an adaptive response that a single sensor can not achieve.Various array processing techniques were developed to enhance signalto-noise ratio or to estimate the temporal or spatial characteristics of the observed signal in harsh environments.In practical array systems, however, some of the assumptions on the environment, sources, or array can be wrong or imprecise.Such environmental imperfections and array uncertainties will cause a mismatch between the nominal and actual data vector, which leads to a degraded performance.The impaired effects are especially fatal for adaptive beamformers.In this thesis, we analyzed the degraded performance of the data-independent and adaptive arrays using a perturbation model.Some analytical expressions of the performance measures, e.g., the expected beampattern and the expected SINR (signal-to-noise-plus-interference-ratio) using the proposed perturbation model are derived and discussed.This is helpful in understanding how the perturbations affect the performance of arrays qualitatively and quantitatively.xi