Modular floating decimal point operations for antenna array adaptation
Abstract
An adaptive signal processing algorithm for antenna arrays is proposed with modular floating decimal point arithmematic operations usable when vector and matrix arrays are of common order and ensuring stable and efficient interference suppression at almost the same hardware cost as for fixed arithmetic. The interference suppression factor depends on calculation sequences and site of rounding, and on sample size which can be kept yp by retaining only real part of denominator with discard of errorproducing imaginary part and omission of rounding in summation of component scalar vector products since scaler multiplication of two vectors is base algorithm operation. A typical algorithm use is adaptive signal processing in phased antenna array after partial beam formation. The reflected signal envelope is assumed to have complex amplitude with zero mean normal distribution and random side lobe radiation pattern. Input signals are sampled by analogtodigital converters, whose output signal matissa is limited by input quantization step. Regularization factor increase leads to increase and stabilization of interference suppression factor, as sample size approximates and exceeds number of interference signals. When sample is small phased antenna array efficiency falls sharply where ideal machine arithmetic is approached as regularization factor increases to infinity. This is now the case with finite arithmetic so that regularized correlation matrix estimates are not needed.
 Publication:

USSR Rept Electron Elec Eng JPRS UEE
 Pub Date:
 April 1985
 Bibcode:
 1985RpEEE....R...5K
 Keywords:

 Algorithms;
 Antenna Arrays;
 Floating Point Arithmetic;
 Signal Processing;
 Analog To Digital Converters;
 Electromagnetic Interference;
 Electronic Filters;
 Simulation;
 Communications and Radar