A recursive fast super-resolution imaging method for scanning radar based on total variation constraints
By optimizing the radar imaging method using total variation constraints and the alternating direction multiplier method (ADMM), the problems of low azimuth resolution and high computational complexity of airborne scanning radar are solved, achieving high resolution and fast imaging.
CN117169881BActive Publication Date: 2026-07-17UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF 2 Cites 0 Cited by
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- UNIV OF ELECTRONICS SCI & TECH OF CHINA
- Filing Date
- 2023-08-31
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing airborne scanning radars have low azimuth resolution and high computational complexity in forward-looking imaging, making it difficult to achieve high resolution and rapid imaging.
Method used
A recursive fast super-resolution imaging method for scanning radar with total variation constraints is proposed. By constructing a regularized objective function and solving it using the alternating direction multiplier method (ADMM), matrix inversion is transformed into iterative operations to achieve recursive updates.
Benefits of technology
It significantly reduces computational complexity without sacrificing imaging performance, improves imaging speed and robustness of reconstruction results, and is suitable for rapid imaging in scanning radar.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN117169881B_ABST
Abstract
This invention discloses a recursive fast super-resolution imaging method for scanning radar based on total variation constraints. First, the azimuth echo is modeled as a convolution of the target scattering distribution and the antenna radiation function. Then, within a regularization framework, the total variation norm is selected as a constraint to derive the optimization problem. Finally, matrix inversion is transformed into iterative matrix multiplication. The reconstruction results are effectively updated recursively using real-time scanning echoes, achieving real-time recursive updating of targets in the forward-looking area. Compared with existing batch processing methods, this method significantly reduces computational complexity and saves computation time without sacrificing imaging performance, making it suitable for fast imaging with scanning radar. Compared with existing TV regularization methods, it strengthens the overall reconstruction results as the scanning echoes are continuously updated, improving the robustness of the reconstruction results. Furthermore, the dimensions of each matrix remain fixed during the iterative update process, requiring updates only based on the current beam echo, providing constant computational and storage costs.
Need to check novelty before this filing date? Find Prior Art