Using Correlation Equations for Localization

Abstract

The long-term goal of this research is to utilize time-domain information in auto-correlation and cross-correlation functions to locate sources in multipath environments. It is assumed that the bandwidths of the sources are sufficient to resolve some multipath at the receiver(s). The technique may be especially useful in cases in which it is difficult to generate a reliable model for the propagation of sound. The specific objective of this project is to utilize the time-domain information in auto- and cross-correlation functions to locate sources in experimental situations. To keep costs down, data have been collected from a terrestrial experiment with known locations of sources and receivers. The new algorithm yields estimates for the relative travel times and amplitudes of multipath transmission (Spiesberger, 1996; 1998). The difference in the arrival times of the first arrivals (which are straight paths) is used to locate sources using hyperbolic location techniques. Data were collected from 1 to 10 sources having wide bandwidths on 15 widely separated receivers. Data from the receivers were recorded on a digital tape recorder. The locations of the sources were estimated using the new algorithm, which combines the time-domain information in auto- and cross-correlation functions. Simulations will be used to estimate the efficacy of a new fourth moment function that is used with the correlation functions to estimate the relative travel times and amplitudes of multipath transmission.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1998
Accession Number
ADA552547

Entities

People

  • John L. Spiesberger

Organizations

  • Pennsylvania State University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Amplitude
  • Bandwidth
  • Cross Correlation
  • Environment
  • Equations
  • Information Operations
  • Mathematics
  • Multipath Transmission
  • Recording Systems
  • Shallow Water
  • Tape Recorders
  • Time Domain
  • Travel Time
  • Universities

Readers

  • Computer Vision.
  • Statistical inference.
  • Wave Propagation and Nonlinear Chaotic Dynamics.