An Autocorrelation-Based Radio Frequency Interference Detection and Removal Method in Azimuth-Frequency Domain for SAR Image

Natsuaki, Ryo; Motohka, Takeshi; Shimada, Masanobu; Suzuki, Shuichi

doi:10.1109/jstars.2017.2775205

Cited by 26 publications

(17 citation statements)

References 25 publications

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“…Reigber et al [30] and Doerry [35] proposed posteriori filtering methods to excise interference for focused image. Natsuaki et al [36] proposed a filtering method in the range-time and azimuth-frequency domain utilizing the Doppler difference for intermittently transmitted wideband (ITWB) RFI.…”

Section: Notch Filteringmentioning

confidence: 99%

Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends

et al. 2019

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Radio frequency interference (RFI) is a major issue in accurate remote sensing by a synthetic aperture radar (SAR) system, which poses a great hindrance to raw data collection, image formation, and subsequent interpretation process. This paper provides a comprehensive study of the RFI mitigation techniques applicable for an SAR system. From the view of spectrum allocation, possible terrestrial and spaceborne RFI sources to SAR system and their geometry are analyzed. Typical signal models for various RFI types are provided, together with many illustrative examples from real measured data. Then, advanced signal processing techniques for removing RFI are reviewed. Advantages and drawbacks of each approach are discussed in terms of their applicability. Discussion on the future trends are provided from the perspective of cognitive, integrated, and adaptive. This review serves as a reference for future work on the implementation of the most suitable RFI mitigation scheme for an air-borne or space-borne SAR system.

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Section: Notch Filteringmentioning

confidence: 99%

Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends

et al. 2019

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“…With their ability to obtain high-resolution images under all time and weather conditions, synthetic aperture radar (SAR) systems are proven to be very useful methods for earth resource surveys and military reconnaissance. Apart from the target signal, signals received by the SAR system may also have interference from communication devices, television networks, and other radar systems [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. These interference signals are collectively referred to as radio frequency interference (RFI).…”

Section: Introductionmentioning

confidence: 99%

“…These interference signals are collectively referred to as radio frequency interference (RFI). On the one hand, the energy of RFI is much greater than the energy of the target signal, which may result in the quality of a SAR image being significantly degraded [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. On the other hand, there are diverse forms of RFI due to their different sources [ 1 , 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, there are diverse forms of RFI due to their different sources [ 1 , 2 , 3 ]. The multiple types of RFI bury the real target signal and blur the SAR imagery [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. Thus, it is essential to study the characteristics of RFI and develop an interference detection and suppression algorithm for SAR signal processing.…”

Section: Introductionmentioning

confidence: 99%

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Multiclass Radio Frequency Interference Detection and Suppression for SAR Based on the Single Shot MultiBox Detector

Sun

et al. 2018

Sensors

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Radio frequency interference (RFI) is known to jam synthetic aperture radar (SAR) measurements, severely degrading the SAR imaging quality. The suppression of RFI in SAR echo signals is usually an underdetermined blind source separation problem. In this paper, we propose a novel method for multiclass RFI detection and suppression based on the single shot multibox detector (SSD). First, an echo-interference dataset is established by randomly combining the target signal with various types of RFI in a simulation, and the time–frequency form of the dataset is obtained by utilizing the short-time Fourier transform (STFT). Next, the time–frequency dataset acts as input data to train the SSD and obtain a network that is capable of detecting, identifying and estimating the interference. Finally, all of the interference signals are exactly reconstructed based on the prediction results of the SSD and mitigated by an adaptive filter. The proposed method can effectively increase the signal-to-interference-noise ratio (SINR) of RFI-contaminated SAR echoes and improve the peak sidelobe ratio (PSLR) after pulse compression. The simulated experimental results validate the effectiveness of the proposed method.

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“…However, well-focused SAR images are always prominently corrupted by untargeted interference caused by natural or man-made factors, especially the interferences whose frequencies fall into the frequency spectrum of useful signals [1,2]. Although the two-dimensional matched filter has an inherent ability in interference suppression, interferences with stronger power will defocus the image and degrade the imaging quality seriously [3,4].…”

Section: Introductionmentioning

confidence: 99%

Time-Varying SAR Interference Suppression Based on Delay-Doppler Iterative Decomposition Algorithm

Tao

et al. 2018

Remote Sensing

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Narrow-band interference (NBI) and Wide-band interference (WBI) are critical issues for synthetic aperture radar (SAR), which degrades the imaging quality severely. Since some complex signals can be modeled as linear frequency modulated (LFM) signals within a short time, LFM-WBI and NBI are mainly discussed in this paper. Due to its excellent energy concentration and useful properties (i.e., auto-terms pass through the origin of Delay-Doppler plane while cross-terms are away from it), a novel nonparametric interference suppression method using Delay-Doppler iterative decomposition algorithm is proposed. This algorithm consists of three stages. First, we present signal synthesis method (SSM) from ambiguity function (AF) and cross ambiguity function (CAF) based on the matrix rearrangement and eigenvalue decomposition. Compared with traditional SSM from Wigner distribution (WD), the proposed SSM can synthesize a signal faster and more accurately. Then, based on unique properties in Delay-Doppler domain, a mask algorithm is applied for interference identification and extraction using Radon and its inverse transformation. Finally, a signal iterative decomposition algorithm (IDA) is utilized to subtract the largest interference from the received signal one by one. After that, a well-focused SAR imagery is obtained by conventional imaging methods. The simulation and measured data results demonstrate that the proposed algorithm not only suppresses interference efficiently but also preserves the useful information as much as possible.

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An Autocorrelation-Based Radio Frequency Interference Detection and Removal Method in Azimuth-Frequency Domain for SAR Image

Cited by 26 publications

References 25 publications

Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends

Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends

Multiclass Radio Frequency Interference Detection and Suppression for SAR Based on the Single Shot MultiBox Detector

Time-Varying SAR Interference Suppression Based on Delay-Doppler Iterative Decomposition Algorithm

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