共形FDA-MIMO雷达降维目标参数估计研究

陈慧; 田湘; 李子豪; 姜欣睿

doi:10.12000/JR21197

Reduced-dimension Target Parameter Estimation For Conformal FDA-MIMO Radar

DOI: 10.12000/JR21197

School of Information and Communication Engineering, University of Electronic Science andTechnology of China, Chengdu 611731, China

Funds: The National Natural Science Foundation of China (61571081), Sichuan Science and Technology Program (18ZDYF2551), Fundamental Research Funds for the Central Universities (ZYGX2018J005)

More Information

Author Bio:
CHEN Hui received the Ph.D. degree in the department of electronic engineering from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2013. Since January 2014, she has been with the School of Information Engineering and Communication, UESTC, where she is currently an Associate Professor. From November 2011 to May 2013, she was a visiting scholar at Columbia University, NY, USA. Her research interests include array signal processing, wireless communication and artificial intelligence

TIAN Xiang was born in Sichuan, China in 1998. She received the Bachelor Degree in 2020 from Chengdu University of Information Technology. She is pursuing the Master Degree in University of Electronic Science and Technology of China. Her major interests are conformal array and frequency inverse array

LI Zihao was born in Sichuan, China in 1996. He received the Master Degree in 2021 from University of Electronic Science and Technology of China. His major interests are conformal array and frequency diverse array radar

JIANG Xinrui was born in Shanxi, China in 1996. She received the Master Degree in 2021 from University of Electronic Science and Technology of China. She specializes in signal recognition, coding recognition and signal processing

Corresponding author: CHEN Hui, huichen0929@uestc.edu.cn

摘要

摘要:
频控阵多输入多输出(FDA-MIMO)雷达是一种具有距离-角度-时间依赖性波束模式且能够提高自由度的系统。该文将可实现降低空气动力学对载体影响、附着在载体表面的共形阵列引入到FDA-MIMO雷达中。首先创建共形FDA-MIMO测量模型，推导参数估计的克拉默-拉奥下界(CRLB)。为了避免传统三维多重信号分类算法(3D-MUSIC)三维搜索，提出一种降维多信号分类(RD-MUSIC)算法实现目标参数估计。仿真结果表明，该算法与3D-MUSIC算法相比，估计精度有所下降，但计算复杂度显著降低。此外，与3D-MUSIC算法相比，该算法具有更好的多目标距离估计性能。
- 共形阵 /
- 频控阵多输入多输出 /
- 参数估计 /
- 三维多重信号分类 /
- 降维多信号分类
Abstract:
Frequency Diverse Array (FDA) Multiple-Input Multiple-Output (MIMO) radar equipped with a FDA can possess beam patterns that are dependent on range, angle, and time, and it can increase the degree of freedom. This paper introduces a conformal array attached to the surface of the carrier, the array can reduce the aerodynamic impact on the carrier and reduce the cross section of the FDA-MIMO radar. First, the conformal FDA-MIMO measurement model is formulated, and a Cramér-Rao Lower Bound (CRLB) is derived to evaluate the parameter estimation performance. To avoid the three-dimensional search of the traditional three-dimensional MUltiple SIgnal Classification (3D-MUSIC) algorithm, a Reduced-Dimension MUltiple SIgnal Classification (RD-MUSIC) algorithm is proposed for parameter estimation. The simulation results demonstrate that the proposed algorithm has a slightly lower estimation accuracy than the 3D-MUSIC algorithm but a much lower computational complexity. In addition, the proposed algorithm has better range estimation performance for multiple targets than the 3D-MUSIC algorithm.
- Conformal array /
- FDA-MIMO /
- Parameter estimation /
- 3D-MUSIC /
- RD-MUSIC

HTML全文

Figure 1. Conformal FDA-MIMO radar

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Figure 2. Conformal FDA-MIMO semi conical receiving array

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Figure 3. Comparison of computational complexity under different scan spacing

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Figure 4. The parameter estimation probability of RD-MUSIC algorithm with different thresholds

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Figure 5. The RMSE versus snapshot for single target case

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Figure 6. The RMSE versus SNR for two targets case

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Figure 7. The RMSE versus snapshot for two targets case

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Figure 8. The RMSE versus snapshot for two targets case

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