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Antenna Placement Optimization for Distributed MIMO Radar Based on a Reinforcement Learning Algorithm.

Jin Zhu1,2, Wenxu Liu2, Xiangrong Zhang3

  • 1School of Artificial Intelligence, Xidian University, Xi'an, 710071, China.

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|October 15, 2023
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Summary
This summary is machine-generated.

This study optimizes antenna placement for distributed multiple-input multiple-output (MIMO) radar systems. The new reinforcement learning method enhances system coverage area for targets with varying headings.

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Area of Science:

  • Radar Systems Engineering
  • Signal Processing
  • Artificial Intelligence in Defense

Background:

  • Distributed multiple-input multiple-output (MIMO) radar systems are crucial for target detection and tracking.
  • Optimizing antenna placement is essential for maximizing system coverage, especially with dynamic targets.
  • Traditional methods struggle with the complexities of varying target heading angles.

Purpose of the Study:

  • To address the antenna placement optimization problem in distributed MIMO radar systems for multiple target heading angles.
  • To develop an improved method for calculating system coverage area considering changing target headings.
  • To leverage reinforcement learning for effective antenna placement solutions.

Main Methods:

  • Mathematical modeling of antenna placement as a sequential decision problem.
  • Implementation of a reinforcement learning agent utilizing the long short-term memory (LSTM)-based proximal policy optimization (PPO) algorithm.
  • Development of an improved method for calculating radar system coverage area.

Main Results:

  • The proposed reinforcement learning approach effectively solves the antenna placement optimization problem.
  • The method demonstrates a significant enhancement in the achievable coverage area of the distributed MIMO radar system.
  • Experimental findings validate the efficacy of the LSTM-PPO based agent.

Conclusions:

  • The developed method provides a novel and effective solution for antenna placement optimization in distributed MIMO radar.
  • The approach offers a valuable reference for future research and development in radar system design.
  • Enhanced coverage area achieved through intelligent antenna placement contributes to improved radar performance.