SYSTEM IMPROVEMENT USING SIGNAL-TO-NOISE RATIO ESTIMATION.

Abstract

This report presents the results of a study effort to determine the possibility of improving the performance of space vehicle tracking and detection systems by using signal-to-noise ratio (SNR) estimation of the received signal. Such SNR estimates can be used to adaptively control important system parameters whose design explicitly depends on SNR. The results of this investigation show, for certain types of systems, performance can indeed be substantially improved by SNR estimation. The analysis of the report is basically in two parts. In the first part consideration is given to the design and characteristics of a SNR estimator with emphasis on maximum likelihood estimation. In the second part, the characteristics of such estimators are used to assess the performance of systems that adapt to such estimates. In particular, it is shown that a space communication system can reliably accept or reject data based on a SNR estimate. It is also shown that a minimum mean square filter can be adequately adjusted by SNR estimates to reduce mean square errors significantly, and improve performance for tracking and detection operations. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 01, 1967
Accession Number
AD0820599

Entities

People

  • C. M. Thomas
  • R. M. Gagliardi

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Communication Systems
  • Detection
  • Estimators
  • Mathematics
  • Maximum Likelihood Estimation
  • Optimal Estimators
  • Space Communications
  • Spacecraft
  • Statistical Algorithms

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Image Processing and Computer Vision.

Technology Areas

  • Space