Portland State University. Department of Electrical Engineering
Date of Publication
Master of Science (M.S.) in Electrical Engineering
Algorithms, Signal detection, Multisensor data fusion
1 online resource (vii, 89 p.)
This thesis presents the unified bias analysis of subspace-based DOA estimation algorithms in terms of physical parameters such as source separation, signal coherence, number of senors and snapshots. The analysis reveals the direct relationship between the performance of the DOA algorithms and signal measurement conditions. Insights into different algorithms are provided. Based upon previous first-order subspace perturbations, second-order subspace perturbations are developed which provide basis for bias analysis and unification. Simulations verifying the theoretical bias analysis are presented.
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Lu, Yang, "Unified Bias Analysis of Subspace-Based DOA Estimation Algorithms" (1993). Dissertations and Theses. Paper 4613.