Sensor placement for ballistic missile localization using evolutionary algorithms

  • Rajagopalan R
  • Niu R
  • Mohan C
 et al. 
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Abstract

Efficient localization of a ballistic missile is an important task in missile defense problems. This paper formulates and solves the sensor placement problem for efficient estimation of the missile location. The first part of this paper develops a mathematical framework for the localization of the missile using multiple sensors based on Cramer-Rao lower bound (CRLB) analysis. We derive the Fisher information matrix to facilitate the evaluation of estimation accuracy. The second part of the paper presents an evolutionary algorithm for obtaining the sensor placements. Simulation results show that the evolutionary algorithm outperforms a greedy sensor placement algorithm and obtains sensor placements with very low estimation error.

Author-supplied keywords

  • Bayesian methods
  • Cramer-Rao lower bound
  • Estimation error
  • Evolutionary computation
  • Fisher information matrix
  • Maximum likelihood estimation
  • Missiles
  • Pollution measurement
  • Radar tracking
  • Sensor fusion
  • Sensor phenomena and characterization
  • Wireless sensor networks
  • ballistic missile localization
  • ballistics
  • evolutionary algorithms
  • evolutionary computation
  • greedy sensor placement algorithm
  • matrix algebra
  • missile defense problems
  • missiles
  • sensors

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Authors

  • Ramesh Rajagopalan

  • Ruixin Niu

  • Chilukuri K. Mohan

  • Pramod K. Varshney

  • Andrew L. Drozd

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