Acoustic Detection and Tracking of a Class I UAS with a Small Tetrahedral Microphone Array

Abstract

An analysis of detection and tracking performance for a Class I unmanned aircraft system (UAS) measured with a small tetrahedral microphone array was performed. Detection and tracking algorithms were implemented using beamforming and adaptive Kalman filters. The performance of a coherent energy-based detection algorithm implemented with a delay and sum beamforming algorithm was assessed using receiver operation characteristics (ROC) curves. Angle tracking was implemented using an adaptive Kalman filter with input from a filter and sum beamforming algorithm. For good signal-to-interference-plus-noise ratios (SINR), the estimated azimuth angles had good agreement with ground truth data, but the estimated elevation angles were underestimated inaccurately by a scale factor.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2014
Accession Number
ADA610599

Entities

People

  • Geoffrey H. Goldman
  • Minas Benyamin

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Detection
  • Algorithms
  • Ambient Noise
  • Bandpass Filters
  • Detection
  • Detectors
  • Elevation
  • False Alarms
  • Filters
  • Frequency
  • Frequency Bands
  • Frequency Domain
  • Microphones
  • Power Spectra
  • Signal Processing
  • Spectra
  • Weighting Functions

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Radio communications and signal processing.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy