Advancing Fully Adaptive Radar Concepts for Real-Time Parameter Adaption and Decision Making

Abstract

Cognitive or Fully Adaptive Radar (FAR) is an area of research that is inspired by biological systems and focuses on developing a radar system capable of autonomously adapting its characteristics to achieve a variety of different tasks such as improved environment sensing and spectral agility. The FAR framework implements a dynamic feedback loop (sense, learn, adapt) within a software defined radar (SDR) system and the environment that emulates a Perception Action Cycle (PAC). The implementation of the FAR framework on SDRs relies on solver-based optimization techniques for their action selection. However, with the increase of optimization complexity, there becomes a heavy impact on time to solution convergence, which limits real-time experimentation. Additionally, many "cognitive radars" lack a memory component resulting in repetitive optimization routines for similar /familiar perceptions. Using an existing model of the FAR framework, a neural network inspired refinement is made.

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Document Details

Document Type
Technical Report
Publication Date
Sep 17, 2020
Accession Number
AD1109155

Entities

People

  • Peter Jr John-baptiste

Organizations

  • Ohio State University

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Air Force Research Laboratories
  • Classification
  • Department Of Defense
  • Engineering
  • Governments
  • Information Operations
  • Machine Learning
  • Military Research
  • Neural Networks
  • Radar
  • Resource Management
  • Systems Biology
  • Target Tracking
  • United States

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Neural Network Machine Learning.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

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