Digital-At-Every-Element Radar Resource Allocation for Multi-Target Tracking

Abstract

A sensors performance is constrained by the amount of resources at its disposal and the utilization of those resources. A radar system, for example, has a limited amount of transmit power-aperture per unit time to track a multitude of targets. A typical approach when tracking multiple dynamic targets is to time interleave the update intervals until all the radar tasks are performed. The advent of more agile sensors, such as digital-at-every-element apertures, opens the possibility for dynamic sensor resource allocation strategies to achieve better tracking performance in target-dense, resource-constrained scenarios. With proper research into aperture allocation, such as the analysis provided in this dissertation, an all-digital radar can intelligently exploit the degrees of freedom offered by all-digital radars to increase tracking performance. In this dissertation, we investigate adaptive aperture allocation for tracking a large number of targets. The strategies are first introduced with a parallel, linear channel model, then increased in realism with a non-linear measurement model, and finally applied to a full tracking system. We derive various strategies for allocating power and aperture, and compare their performance based on tracking related metrics. Finally, we investigate the relationship be-tween the aperture allocation strategies and the target locations for multiple scenarios designed to represent the environment for a radar tracking system. This research provides groundbreaking strategies for optimal radar aperture allocation using the digital-at-every-element architectures to reduce the overall system uncertainty and decrease the uncertainty on a per-target basis. Integrating aperture allocation with the management of other degrees of freedom will increase multi-target tracking performance well beyond the current state of the art.

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Document Details

Document Type
Technical Report
Publication Date
Sep 10, 2019
Accession Number
AD1080034

Entities

People

  • David Lucking

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force Facilities
  • Algorithms
  • Cartesian Coordinates
  • Channel Models
  • Computational Complexity
  • Computational Science
  • Coordinate Systems
  • Detectors
  • Doppler Radar
  • Gaussian Distributions
  • Information Theory
  • Kalman Filters
  • Measurement
  • Monte Carlo Method
  • Multitarget Tracking
  • Power Distribution
  • Probability
  • Probability Distributions
  • Radar
  • Radar Tracking
  • Random Variables
  • Sensor Networks
  • Signal Processing
  • Target Tracking
  • Theses
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Phased Array Antenna Design.
  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design