Estimation near "Zero Information" points: angle-of-arrival near the endfire
Eran Bashan, Amir Weiss, Yaakov Bar‐Shalom · IEEE Transactions on Aerospace and Electronic Systems · 2007
We examine large-sample properties of the maximum- likelihood estimator (MLE) in the vicinity of points where the Fisher information measure (FIM) equals zero. Under mild regularity conditions the MLE is asymptotically efficient and therefore lower bounded by the Cramer-Rao lower bound (CRLB) [5], which diverges for such points. When a linear sensor array is used for angle-of-arrival (AOA) estimation, the CRLB diverges as the AOA approaches pi/2. We provide new results characterizing the MLE performance in the AOA problem.