On the Deterministic CRB for DOA Estimation in Unknown Noise Fields Using Sparse Sensor Arrays
Abstract:
The Cramer-Rao bound (CRB) plays an important role in direction of arrival (DOA) estimation because it is always used as a benchmark for comparison of the different proposed estimation algorithms. In this correspondence, using well-known techniques of global analysis and differential geometry, four necessary conditions for the maximum of the log-likelihood function are derived, two of which seem to be new. The CRB is derived for the general class of sensor arrays composed of multiple arbitrary widely separated subarrays in a concise way via a coordinate free form of the Fisher Information. The result derived in [1] is confirmed. «
The Cramer-Rao bound (CRB) plays an important role in direction of arrival (DOA) estimation because it is always used as a benchmark for comparison of the different proposed estimation algorithms. In this correspondence, using well-known techniques of global analysis and differential geometry, four necessary conditions for the maximum of the log-likelihood function are derived, two of which seem to be new. The CRB is derived for the general class of sensor arrays composed of multiple arbitrary w... »
Keywords:
array signal processing, differential geometry, direction-of-arrival estimation, matrix algebra, maximum likelihood estimation, sensor arraysCramer-Rao bound, DOA estimation, Fisher information matrices, deterministic CRB, differential geometry, direction of arrival estimation, log-likelihood function, maximum likelihood function, sparse sensor arrays, unknown noise fields