Convolution Neural Network Enhanced MIMO Array Radar Imaging Based on Back Projection Algorithm
- Resource Type
- Conference
- Authors
- Ren, Jianfei; Kang, Le; Zhao, Siyuan; Liu, Yingxi; Zhang, Yuanpeng; Li, Kaiming
- Source
- 2021 CIE International Conference on Radar (Radar) Radar (Radar), 2021 CIE International Conference on. :94-97 Dec, 2021
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Computing and Processing
Fields, Waves and Electromagnetics
Geoscience
Robotics and Control Systems
Signal Processing and Analysis
Convolution
Neural networks
Imaging
Radar imaging
Distortion
Background noise
Distortion measurement
Enhanced imaging
Multiple-input-multiple-output (MIMO) radar
U-net
Spatial distortion correction
Denoising
- Language
- ISSN
- 2640-7736
The multiple-input-multiple-output (MIMO) array radar has plentiful application scenarios in the modern intelligent life. The back projection (BP) algorithm is widely used in MIMO array radar imaging for the superior imaging accuracy and generality of measurement configurations. However, the BP algorithm also bring the two-dimensional spatial distortion and background noise. To solve these problems, the U-Net network is introduced in MIMO array radar enhanced imaging in this paper. The experimental results of both random and fixed scatters show that the scatters are accurately reconstructed and positioned, the two-dimensional spatial distortion is corrected and the background noise is eliminated with the proposed method.