Improved Weighted Least Squares Algorithm for Hybrid AOA and TDOA Localization

Abstract

This paper develops a new hybrid AOA and TDOA localization algorithm. The most promising hybrid AOA and TDOA localization algorithm currently available is a weighted least squares (WLS) estimator, in which the AOA measurements are multiplied by the TDOA measurements, yielding a product of five noise terms. However, only the first-order noise terms are kept in the formulation of the WLS algorithm. In other words, the second- and higher-order noise terms are neglected, which results in a significant performance degradation. We develop an improved WLS algorithm, in which the AOA measurements are added to the TDOA measurements, lowering the highest order of the noise term products to two. Consequently, the performance is improved because a less number of noise terms are neglected.