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A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network.

Ji She1, Fei Wang2, Jianjiang Zhou3

  • 1Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China. designnuaa@sina.com.

Sensors (Basel, Switzerland)
|December 24, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a new algorithm for radar networks to minimize transmitted power for target tracking. The method enhances low probability of intercept (LPI) performance by optimizing sensor selection and power allocation.

Keywords:
low probability of intercept (LPI)multiple-target trackingmutual information (MI)radar network

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Radar Systems

Background:

  • Radar networks offer advantages over traditional radar systems.
  • Low probability of intercept (LPI) performance is crucial for modern target tracking applications.

Purpose of the Study:

  • To propose a joint sensor selection and power allocation algorithm for multiple-target tracking in LPI radar networks.
  • To minimize total transmitted power while maintaining a required mutual information (MI) threshold for target estimation.

Main Methods:

  • Developed a joint optimization algorithm for sensor selection and power allocation.
  • Separated the non-convex optimization problem into power allocation and sensor selection subproblems.
  • Utilized the bisection method for power allocation and a low-complexity algorithm for sensor selection.

Main Results:

  • The proposed algorithm effectively minimizes the total transmitted power of the radar network.
  • Achieved significant reductions in transmitted power, enhancing LPI capabilities.
  • Demonstrated predictive calculation of mutual information based on target state estimation.

Conclusions:

  • The novel algorithm successfully balances sensor selection and power allocation for improved LPI target tracking.
  • The approach provides a computationally efficient method for optimizing radar network performance.
  • Reduced power transmission is key to enhancing the stealth characteristics of radar networks.