A Bayesian Approach to Predicting an Unknown Number of Targets Based on Sensor Performance

Abstract

Estimating remaining targets after some attempt has been made to detect an overall, unknown number of targets is critical to determining the potential threat associated with these remaining targets. This paper presents a Bayesian approach to calculate the distribution on the number of remaining targets given the sensor performance and the number of targets detected. For a single sensor, a closed form posterior distribution on remaining targets is derived. For multiple sensors, the corresponding posterior distribution is developed. A naive implementation of this calculation is shown to be computationally prohibitive, and an efficient means for performing the calculation is presented.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2006
Accession Number
ADA454747

Entities

People

  • Craig Carthel
  • Karna Bryan

Organizations

  • Centre for Maritime Research and Experimentation

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Bayesian Inference
  • Bayesian Networks
  • Binomials
  • Computational Complexity
  • Detection
  • Detectors
  • Equations
  • Information Operations
  • Kernel Functions
  • Law
  • Models
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference