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On-Board RFI Detection Performance of a Multichannel SAR System with Digital Square-Law Detectors | IEEE Conference Publication | IEEE Xplore

On-Board RFI Detection Performance of a Multichannel SAR System with Digital Square-Law Detectors


Abstract:

Radio Frequency Interference (RFI) is a growing problem for future Synthetic Aperture Radar (SAR) missions, resulting in data loss, image artifacts and undetected biases....Show More

Abstract:

Radio Frequency Interference (RFI) is a growing problem for future Synthetic Aperture Radar (SAR) missions, resulting in data loss, image artifacts and undetected biases. A new approach for mitigating RFI is digital beamforming (DBF), which is possible with the next generation of multichannel SAR systems and allows for a spatial filtering of signals from different directions. While on-board RFI removal with DBF is challenging for spaceborne systems due to the computational load, past publications have shown that this problem can be overcome with DBF-based auxiliary beams by moving most of the processing to the ground without requiring the down-linking of all channels. A remaining problem of measuring RFI information with auxiliary beams is determining the interferer position. This paper shows the performance simulation of a series of digital square-law detectors which can be used to overcome this issue. It is shown that a series of digital square-law detectors provides the opportunity to simultaneously determine if RFI is present and under which direction, while maintaining a low system complexity. This is possible because the detectors provide a good probability of detection and false alarm rate even if the data rate is decimated. The simulated system performs well for a decimation factor of 110.
Date of Conference: 17-22 July 2022
Date Added to IEEE Xplore: 28 September 2022
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Conference Location: Kuala Lumpur, Malaysia
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1. Introduction

Synthetic Aperture Radar (SAR) has been increasingly af-fected by Radio Frequency Interference (RFI) over the past decade and this trend is expected to worsen further over time [1], [2]. A robust RFI mitigation scheme is therefore critical for future missions in order to avoid data loss and un-detected biases in scientific end products. A variety of techniques have been proposed to reduce the impact of RFI [2]–[7]. However, all conventional RFI mitigation methods suffer sig-nificant drawbacks, such as remaining data loss or resolution loss, or depend on parameters that vary strongly from case to case.

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