Compressed sensing synthetic aperture radar (SAR) imaging method based on fractional order fourier transformation

Abstract

The invention provides a compressed sensing synthetic aperture radar (SAR) imaging method based on fractional order fourier transformation, and belongs to the technical field of microwave imaging. For a sparse target scene, a system emits a linear frequency modulation pulse signal; by adopting a method for projecting an echo signal to a low-dimension measurement matrix, measurement data which are much smaller than those required by a Nyquist sampling principle are acquired; due to the echo signal, after a reconstruction matrix is constructed by a simplified fractional order fourier transformation domain sparse mode and a data acquisition mode, a calculated distance pulse pressure result is optimized by a compressed sensing signal reconstruction method and is subjected to distance migration correction and direction pulse pressure to obtain a target scene imaging result. By the imaging method, the measurement data amount of a target scene with a sparse characteristic can be greatly reduced; and pressure on data storage and data transmission can be effectively relieved.

Description

Technical field [0001] The invention belongs to the technical field of microwave imaging, and specifically relates to a signal processing method for compressed sensing synthetic aperture radar (SAR) imaging based on fractional Fourier transform. Background technique [0002] Synthetic Aperture Radar (SAR) transmits electromagnetic pulses to the observed area through a transmitting antenna, and uses the receiving antenna to receive radar echoes to obtain the spatial distribution of electromagnetic scattering characteristics of the target scene. As an active system, SAR actively emits electromagnetic waves in the microwave range without relying on sunlight, and clouds, fog, and precipitation have little effect on microwaves, ensuring SAR imaging all day long. It has a wide range of applications in environmental protection, disaster monitoring, ocean observation, resource exploration, geological surveying and mapping, and has become an important means of high-resolution earth observ...

AI Technical Summary

Problems solved by technology

The modern radar imaging system based on the Nyquist sampling theorem is faced with the challenges of high sampling rate, large data volume, and the difficulty of massive data storage and transmission.

In the process of processing, there is also the problem of data volume imbalance between the measurement data and the processing results, that is, for relatively sparse scenes, it is still necessary to obtain huge data according to the requirements of the Nyquist sampling theorem, while the processing results only retain a small number of positions and scattering coefficients, etc. useful information

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