Systems Engineering and Electronics ›› 2025, Vol. 47 ›› Issue (10): 3235-3250.doi: 10.12305/j.issn.1001-506X.2025.10.11

• Sensors and Signal Processing • Previous Articles    

Variance-fitting interpolation-based method for SAR image dataset expansion

Xuan LI1(), Qi GONG1(), Zi HE2,*(), Zhenhong FAN2(), Dazhi DING2()   

  1. 1. School of Electronic and Optical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
    2. School of Microelectronics,Nanjing University of Science and Technology,Nanjing 210094,China
  • Received:2024-07-01 Online:2025-10-25 Published:2025-10-23
  • Contact: Zi HE E-mail:lxuan0820@163.com;1441428166@qq.com;zihe@njust.edu.cn;zhfan@njust.edu.cn;dzding@njust.edu.cn

Abstract:

In response to the scarcity of synthetic aperture radar (SAR) datasets, the high computational, unstable training, and dependence on big data in generating adversarial network images, this paper proposes a variance-adaptive multi-azimuth SAR image interpolation method that exploits the inherent characteristics of different interpolation approaches to achieve horizontal-plane azimuth data augmentation. Experimental results demonstrate that the interpolation performance for co-polarized channels significantly outperforms cross-polarized channels, with a 32.7% reduction in root mean square error and a 2.8 dB improvement in peak signal-to-noise ratio. Notably, the method maintains high fidelity (radial integral similarity>0.994) even under level-5 sea state conditions. The effectiveness of the method is validated. The proposed solution provides a novel approach for SAR dataset augmentation by effectively leveraging the differential features of interpolation techniques.

Key words: dataset expansion, image simulation, interpolation algorithm

CLC Number: 

[an error occurred while processing this directive]