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A MIMO Radar-Based DOA Estimation Structure Using Compressive Measurements.

Tao Chen1, Jian Yang2,3, Muran Guo4

  • 1College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China. chentao@hrbeu.edu.cn.

Sensors (Basel, Switzerland)
|November 2, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces compressive measurement-based MIMO (CM-MIMO) radar for efficient direction-of-arrival (DOA) estimation. It reduces system complexity and computational load by using compressive sensing, enhancing radar performance.

Keywords:
Cramér–Rao boundDOA estimationMIMO radarcompressive sensinginformation theory

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Area of Science:

  • Radar Systems Engineering
  • Signal Processing
  • Array Signal Processing

Background:

  • Traditional multiple-input multiple-output (MIMO) radar systems face challenges with high system complexity and computational burden.
  • Direction-of-arrival (DOA) estimation is crucial for radar applications, but existing methods can be resource-intensive.

Purpose of the Study:

  • To propose a novel compressive measurement-based MIMO (CM-MIMO) radar structure for reduced system complexity and computational load.
  • To analyze the estimation performance of the CM-MIMO radar using Cramér-Rao bound (CRB).
  • To develop an optimized measurement matrix for improved DOA estimation accuracy.

Main Methods:

  • Implementation of compressive sensing (CS) after matched filters in a MIMO radar system.
  • Derivation and analysis of the Cramér-Rao bound (CRB) for DOA estimation in the proposed CM-MIMO radar.
  • Application of the maximum mutual information criterion for optimizing the measurement matrix using prior DOA probability distributions.

Main Results:

  • The CM-MIMO radar effectively reduces system complexity and computational burden compared to conventional MIMO radar.
  • The derived CRB expression is applicable to conventional MIMO radar and works in under-determined cases.
  • An optimized measurement matrix significantly improves estimation performance by mitigating information loss associated with random matrices.

Conclusions:

  • The proposed CM-MIMO radar offers a computationally efficient and effective solution for DOA estimation.
  • Optimizing the measurement matrix using prior information enhances the accuracy of DOA estimation.
  • Numerical simulations validate the superiority of the proposed CM-MIMO radar structure.