Evolutionary Developments of Today’s Remote Sensing Radar Technology—Right From the Telemobiloscope: A review

Kari, Samedh Sachin; Raj, A Arockia Bazil; K, Balasubramanian.

doi:10.1109/mgrs.2023.3329928

Cited by 4 publications

(1 citation statement)

References 151 publications

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“…However, in reality, SAR imaging covers a wide area, and there may be multiple ground-based radars emitting LFM interference with multiple parameters. Additionally, considering the long synthetic aperture of SAR, even if there is only one ground-based radar, its operational mode and waveform parameters may switch within the time span of the beam coverage [34,35]. Therefore, it is crucial to research and develop methods that can effectively suppress LFM interference with multiple parameters.…”

Section: Introductionmentioning

confidence: 99%

A Sparse Recovery Algorithm for Suppressing Multiple Linear Frequency Modulation Interference in the Synthetic Aperture Radar Image Domain

Tong,

Lu,

Yang

et al. 2024

Sensors

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In synthetic aperture radar (SAR) signal processing, compared with the raw data of level-0, level-1 SAR images are more readily accessible and available in larger quantities. However, an amount of level-1 images are affected by radio frequency interference (RFI), which typically originates from Linear Frequency Modulation (LFM) signals emitted by ground-based radars. Existing research on interference suppression in level-1 data has primarily focused on two methods: transforming SAR images into simulated echo data for interference suppression, or focusing interference in the frequency domain and applying notching filters to reduce interference energy. However, these methods overlook the effective utilization of the interference parameters or are confined to suppressing only one type of LFM interference at a time. In certain SAR images, multiple types of LFM interference manifest bright radiation artifacts that exhibit varying lengths along the range direction while remaining constant in the azimuth direction. It is necessary to suppress multiple LFM interference on SAR images when original echo data are unavailable. This article proposes a joint sparse recovery algorithm for interference suppression in the SAR image domain. In the SAR image domain, two-dimensional LFM interference typically exhibits differences in parameters such as frequency modulation rate and pulse width in the range direction, while maintaining consistency in the azimuth direction. Based on this observation, this article constructs a series of focusing operators for LFM interference in SAR images. These operators enable the sparse representation of dispersed LFM interference. Subsequently, an optimization model is developed that can effectively suppress multi-LFM interference and reduce image loss with the assistance of a regularization term in the image domain. Simulation experiments conducted in various scenarios validate the superior performance of the proposed method.

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Section: Introductionmentioning

confidence: 99%