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Modified omega-k algorithm for high-speed platform highly-squint staggered SAR based on azimuth non-uniform
Hong-Cheng Zeng1, Jie Chen2, Wei Liu3
1School of Electronic and Information Engineering, Beihang University, Beijing 100191, China. zenghongcheng@buaa.edu.cn.
Sensors (Basel, Switzerland)
|February 10, 2015
Summary
A new method improves Synthetic Aperture Radar (SAR) imaging for high-speed platforms. This technique efficiently processes staggered SAR data, reducing computational load and storage needs for better imaging performance.
Area of Science:
- Remote Sensing
- Signal Processing
- Electromagnetics
Background:
- High-speed platforms in Synthetic Aperture Radar (SAR) present challenges for imaging, particularly with highly squinted data.
- Staggered SAR techniques vary the pulse repetition interval (PRI) to manage range-walk, but efficient data focusing remains complex.
Purpose of the Study:
- To develop a low-complexity algorithm for focusing staggered SAR data from high-speed, highly-squint SAR platforms.
- To improve the efficiency of range cell migration (RCM) recovery and reduce computational demands.
Main Methods:
- Employed a staggered SAR technique with a linearly varying PRI as a function of range-walk.
- Proposed a modified Omega-k algorithm incorporating optimal azimuth non-uniform interpolation (ANI).
- Utilized an approximate model for continuous PRI variation and compensated for azimuth non-uniform sampling (ANS) effects.
Main Results:
- The proposed modified Omega-k algorithm effectively focuses staggered SAR data with reduced complexity.
- Avoided zero-padding in the range direction, saving data storage and computational resources.
- Achieved imaging performance comparable to existing methods but with significantly lower computational complexity.
Conclusions:
- The novel modified Omega-k algorithm offers an efficient solution for processing high-speed, highly-squint SAR data.
- The method successfully addresses challenges associated with staggered SAR and PRI variations.
- Demonstrated significant improvements in computational efficiency without compromising imaging quality.
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