首页|Orthogonal waveform design with fractional programming on the ambiguity suppression of SAR systems

Orthogonal waveform design with fractional programming on the ambiguity suppression of SAR systems

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Waveform diversity(WD)represents a dynamic and transformative technology widely used in radar systems to enhance sensitivity and discrimination capabilities.Recently,WD techniques have been ex-tensively explored for their potential ambiguity suppression within synthetic aperture radar(SAR)systems.Among these,the alternate transmitting mode combined with orthogonal waveforms emerges as a particularly promising solution.This study focuses on optimizing the power spectrum density(PSD)of signals to design and generate an orthogonal waveform pair that achieves both a low cross-correlation-to-autocorrelation ratio(CAR)and satisfactory imaging performance.Initially,we construct a fractional programming model with convex constraints to minimize the CAR.To address this challenge,we introduce an iterative optimization procedure for the PSD variable,which sequentially reduces the CAR.Each optimization step can be effi-ciently solved using a quadratically constrained quadratic program,ensuring that the resulting computational complexity remains low.Building on the optimized PSD,we established a parametric piecewise linear model to generate an orthogonal waveform pair.This model not only maintains a low CAR but achieves satisfac-tory imaging performance in real-time applications.Consequently,this orthogonal waveform pair effectively suppresses range ambiguity in SAR systems.Finally,we demonstrated the practicability and effectiveness of the proposed orthogonal waveforms through detailed simulation experiments,specifically targeting ambiguity suppression in conventional quad-polarization SAR systems.

synthetic aperture radar(SAR)waveform diversity(WD)ambiguity suppressionorthogonal waveformfractional programmingpower spectrum density(PSD)

Yunkai DENG、Yongwei ZHANG、Zhimin ZHANG、Wei WANG、Heng ZHANG

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Department of Space Microwave Remote Sensing System,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100190,China

National Key Research and Development Program of China

2023YFB3904901

2024

中国科学:信息科学(英文版)
中国科学院

中国科学:信息科学(英文版)

CSTPCDEI
影响因子:0.715
ISSN:1674-733X
年,卷(期):2024.67(9)