Heuristic Approaches for Near-Optimal Placement of GPS-Based Multi-Static Radar Receivers in American Coastal Waters

Abstract

Narcotics smuggling across the Caribbean Sea is a growing concern for the United States Coast Guard. One vector for this illicit trafficking is via small aircraft. This thesis proposes a multi-static radar architecture using the Global Positioning System (GPS) constellation as a transmission source to detect these aircraft as they transit a detection fence. The system developed in this thesis relies on the forward-scatter phenomenon in which a radar shadow is cast by a target as it crosses in front of a transmitter, creating a measurable difference in the signal amplitude at the receiver. This thesis first develops a mathematical model parametrizing such a multi-static radar system. This model is then used to build a novel simulation, and output from the simulation is used as input in a vast set covering problem whose goal is both to determine the smallest number of sensors along with their locations in order to detect 100 of transiting aircraft, and to determine the near optimal location of a fixed number of sensors. The research proves the problem can be modeled, albeit at great computational expense. It further demonstrates that near optimal solutions can be generated with almost no computational expense using the geometric heuristic.

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Document Details

Document Type
Technical Report
Publication Date
Mar 26, 2020
Accession Number
AD1102507

Entities

People

  • Brandon J. Hufstetler

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Algorithms
  • Computational Science
  • Computer Programming
  • Detectors
  • Electromagnetic Radiation
  • Evolutionary Algorithms
  • Geographic Regions
  • Geography
  • Global Positioning Systems
  • Governments
  • Mathematical Models
  • Multistatic Radar
  • North America
  • Radar
  • Satellite Constellations

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Political Violence and Terrorism Studies.
  • Radar Systems Engineering.

Technology Areas

  • Space
  • Space - Space Objects