<p>This paper discusses the problem of low-elevation target height estimation for multiple-input multiple-output (MIMO) radar in multipath environments. The beamspace compresses the data and is ideal for reducing the computational burden of elevation estimation. To obtain the height parameter of the target accurately, we propose a height estimation method based on a beamspace joint alternating iterative (BJAI) algorithm in MIMO radar. This method mainly converts the reduced-dimensional MIMO radar element space data into beamspace data and whitens them to improve the reliability. Then, a simplified model is used to obtain the initial value of the elevation, and we combine the reflection coefficient and the target elevation angle for alternate estimation. Finally, we calculate the target height using the obtained elevation information. Simulation results verify that the proposed algorithm has high estimation accuracy and strong robustness.</p>

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A height estimation method based on a beamspace joint alternating iterative algorithm in MIMO radar

  • Derui Tang,
  • Yongbo Zhao,
  • Shuaijie Zhang

摘要

This paper discusses the problem of low-elevation target height estimation for multiple-input multiple-output (MIMO) radar in multipath environments. The beamspace compresses the data and is ideal for reducing the computational burden of elevation estimation. To obtain the height parameter of the target accurately, we propose a height estimation method based on a beamspace joint alternating iterative (BJAI) algorithm in MIMO radar. This method mainly converts the reduced-dimensional MIMO radar element space data into beamspace data and whitens them to improve the reliability. Then, a simplified model is used to obtain the initial value of the elevation, and we combine the reflection coefficient and the target elevation angle for alternate estimation. Finally, we calculate the target height using the obtained elevation information. Simulation results verify that the proposed algorithm has high estimation accuracy and strong robustness.