Accession Number:

ADA106684

Title:

Research on Algorithms for Adaptive Antenna Arrays.

Descriptive Note:

Annual interim rept. Dec 79-Dec 80,

Corporate Author:

STANFORD UNIV CA

Report Date:

1981-08-01

Pagination or Media Count:

97.0

Abstract:

The fundamental efficiency of adaptive algorithms is analyzed. It is found that noise in the adaptive weights increases with convergence speed. This causes loss in mean-square-error performance. Efficiency is considered from the point of view of misadjustment versus speed of convergence. A new version of the LMS algorithm based on Newtons method is analyzed and shown to make maximally efficient use of real-time input data. The performance of this algorithm is not affected by eigenvalue disparity. Practical algorithms can be devised that closely approximate Newtons method. In certain cases, the steepest descent version of LMS performs as well as Newtons method. The efficiency of adaptive algorithms with nonstationary input environments is analyzed where signals, jammers, and background noises can be of a transient and nonstationary nature. A new adaptive filtering method for broadband adaptive beamforming is described which uses both poles and zeros in the adaptive signal filtering paths from the antenna elements to the final array output.

Subject Categories:

  • Electrical and Electronic Equipment
  • Theoretical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE