Abstract
The direction of arrival (DOA) and amplitude-phase (AP) of source signal can be estimated through array signal processing, while the process of information acquisition has not been described by information theory yet. In this study, the authors propose a novel spatial information theory framework to describe the DOA and AP estimation process. Firstly, they give a sensor array system model, where the spatial information is defined mathematically. Furthermore, in a single source scenario, the derivations of theoretical expression and an asymptotic upper bound for DOA information are presented. It also proves that the AP information accords with Shannon channel capacity when the source follows complex-Gaussian distribution. In addition, when in an uncorrelated multi-sources scenario, the AP information is the sum of that of each source for Gaussian distributed sources. Finally, they propose a definition of entropy error to evaluate the information acquisition capability of a sensor array. Numerical results verify that the entropy error is consistent with mean square error and approaches Cramer–Rao bound in high signal-to-noise ratio. It also verifies the correctness of theoretical derivation and shows that the spatial information can be employed as an evaluation index to quantitatively analyse the system performance which has significant guidance.
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