Improving the threshold performance of higher-order direction finding methods via pseudorandomly generated estimator banks

Abstract

A recently reported estimator bank approach (see IEEE SP Lett., vol.4, p.54, 1997) is extended below to the fourth-order direction finding algorithms. The essence of our approach is to exploit "parallel" underlying eigenstructure based estimators for removing the outliers and improving the direction finding performance in the threshold domain. The pseudorandomly generated weighted fourth-order MUSIC estimators are exploited as underlying techniques for estimator bank. Motivated by the superior performance and reduced computational complexity of beamspace and root modifications of the second-order eigenstructure techniques, beamspace root implementations of fourth-order MUSIC and fourth-order estimator bank are developed. Simulations show dramatical improvements of the threshold performance.