One-bit SAR Imaging Based on Perceptron Learning Algorithm with Bootstrap Method
- Resource Type
- Conference
- Authors
- Hu, Dongxing; Liu, Falin; Wang, Zheng; Guo, Yuanyue; Zhu, Hailiang
- Source
- 2021 International Conference on Microwave and Millimeter Wave Technology (ICMMT) Microwave and Millimeter Wave Technology (ICMMT),2021 International Conference on. :1-3 May, 2021
- Subject
- Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Microwave technology
Microwave integrated circuits
Quantization (signal)
Millimeter wave technology
Programmable logic arrays
Radar polarimetry
Microwave FET integrated circuits
- Language
The one-bit quantization with time-varying thresholds has been studied in the field of compressed sensing and SAR imaging. The Perceptron Learning Algorithm (PLA) uses a sign function as its activation function, and this is consistent with the one-bit quantization model. Therefore, one-bit SAR imaging based on PLA shows better imaging performance than the existing approach based on Logistic Regression Algorithm (LRA). Moreover, the bootstrap method is introduced into PLA to improve the imaging performance at low SNR. Experimental results validate the effectiveness of the proposed method.