Information Measures and Performance Bounds for Array Processors.
COLORADO STATE UNIV FORT COLLINS DEPT OF ELECTRICAL ENGINEERING
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Information measures and performance bounds are derived for frequency-domain linear array processors deployed in homogeneous Gaussian random fields. J-divergence, a measure of the net information rate of an array, is shown to be a useful measure of how effectively detection and resolution functions can be performed in optimum and conventional array processing structures. In a detection context, J-divergence becomes a detection index that can be interpreted in terms of array gain and output signal-noise ratio. Comparisons between the divergence of optimum and conventional processors indicate, for example, that optimum processing can provide on the order of 13 dB gain over conventional processing when trying to detect a 20 dB signal in the presence of a 20 dB interference located within the Rayleigh limit of the array.