Synthetic Aperture Radar (SAR) is easily affected by various radio frequency interference (RFI), which leads to the degradation of image quality. In multi-channel SAR, the position of the RFI source is a prerequisite for most spatial filtering methods to remove interference. For dual-channel SAR systems, the existing RFI source localization methods can only obtain the position of a single jammer, while in a complex electromagnetic environment, there may be multiple RFI sources. To address this problem, a multisource RFI localization method for dual-channel SAR is proposed in this letter. First, the time-frequency analysis is employed to establish the feature mapping of RFI and SAR signals in the time-frequency domain. Then, ridge path detection and recombination algorithms are proposed to separate and extract the received interference signals. Finally, the leastL1-norm models are established for each extracted interference signal based on the phase difference of the two channels, and the high precision azimuth position of the RFI sources can be obtained using the interior point method. Simulations indicate that the azimuth localization accuracy of the proposed method can be within 20 m when the Signal-to-Interference Ratio (SIR) is below 0dB. The spaceborne SAR data acquired by Chinese Gaofen-3 (GF-3) also verify the effectiveness of the proposed method.

This letter proposes a scheme for automatically and accurately extracting the parameters of weak radio frequency interference (RFI) present in the signal within the time-frequency domain. This scheme utilizes Short-Time Fourier Transform (STFT) to transform each frame of radar echo containing interference into the time-frequency domain. In the time-frequency domain, a joint low-rank sparse robust principal component analysis based on truncated nuclear norms (TJLS-RPCA) is employed to divide the time-frequency representation into two joint low-rank sparse matrices, from which the interference parameters are extracted. Subsequently, K-means clustering is applied to determine the number of RFIs, and Gaussian fitting is applied to eliminate high-error items. This scheme can extract parameters such as the central frequency, bandwidth, and duration of the interference. The proposed scheme improves the accuracy of parameter extraction and processing speed, demonstrating notable effectiveness in handling weak interference. The Monte Carlo experimental results demonstrate that the scheme provides highly accurate parameter estimation when the Signal-to-Interference Ratio (SIR) is less than 13dB, with errors below 0.5%. Finally, the feasibility of the proposed scheme is validated using Sentinel-1A data, and the extracted results are consistent with the simulation results.

In the above article[1], there is a correction to the author list. The author list is as follows:

Elevation multichannel synthetic aperture radar (SAR) utilizes digital beamforming (DBF) technology to achieve high-resolution and wide-swath (HRWS) imaging. However, electromagnetic jamming sometimes occurs in SAR images, resulting in the loss of scene information. A DBF-SAR system is weak in resisting jamming signals, and the barrage jamming signals within an imaging swath are not easy to remove using traditional suppression methods for DBF-SAR. Thus, an advanced barrage jamming suppression scheme based on elevation multichannel cancellation is proposed. First, the jamming signals in the echoes are removed using a well-designed channel cancellation filter to obtain the jamming-free signals. In accordance with the characteristics of jamming-free signals, the weighting coefficients are rededuced, and a modified DBF method is presented to achieve HRWS imaging and improve the DBF-SAR signal-to-noise ratio (SNR). In this way, the proposed scheme can effectively eliminate barrage jamming signals. In addition, some simulations and a 16-channel airborne DBF-SAR experiment were executed to demonstrate the proposed scheme.

The high-fidelity deceptive jamming contaminated synthetic aperture radar (SAR) images are very confusing when they are interpreted for target recognition. In this letter, a novel azimuth phase coding (APC)-based method is proposed for deceptive jamming suppression, especially with characteristics of high fidelity and intermittent sampling. The deceptive jamming model is detailedly formulated, and the difference and relation related to the real target are also discussed. Then, the APC-based suppression method is proposed, where the original APC principle and how it is to be introduced into deceptive jamming suppression are deduced and analyzed. Considering the delay feature of deceptive jamming retransmission, azimuth phase modulation, azimuth phase demodulation, and azimuth filtering are successively implemented. Then, parameters discussion is carried out for a deeper understanding. Simulation results demonstrate the superiority of the proposed method.

Intermittent sampling deceptive jamming is widely used in electronic warfare because of its similar characteristics to echo signal and higher gain after two-dimensional matched filtering. In this paper, a novel range intermittent sampling deceptive jamming suppression method is proposed based on azimuth phase coding (APC), which is originally used to suppress range ambiguity. Utilizing the feature that deceptive jamming is generated by intercepting the previous pulse and repeating after at least one or more pulse repetition intervals, an azimuth phase modulation and demodulation are employed to the transmitted signal and received signal respectively. Finally, the interference can be separated in doppler domain, then removed by azimuth filtering rather than azimuth defocusing as conventional suppression methods do. Simulation results show the suppression effectiveness and superiority of the proposed method.

Narrow-band interference (NBI) suppression is an important technique in the low-frequency synthetic aperture radar (SAR). NBI sources either intentional or unintentional can mask the SAR signals and cause image degradation. According to the different characteristics of the spectra between the NBI and the SAR signals, a new method using subband spectral cancellation is applied to suppress the NBI. In contrast to the conventional suppression method performed on the raw data, this letter deals with the focused SAR image. By subtracting different range subband spectra of the SAR image, the NBIs are obtained and cancelled. The proposed method does not need to detect and estimate the parameters of the NBI and is easy to put in practice. Its performance is tested on the real data acquired by an experimental SAR system at P-band.

Unambiguous wide swath and high azimuth resolution pose contradicting requirements on the design of SAR systems. The requirements can be overcome by using concurrent subbands technology. This paper reviews the concurrent subbands technology for the imaging of wide swath with high range-azimuth resolutions. In the designed system, the concurrent subbands technology is used to integrate a wider range signal bandwidth, and thus achieve a higher range resolution; multichannel allows a lower Pulse Repetition Frequency (PRF) and enables unambiguous wide swath. The synthetic bandwidth method is used to obtain a wide-bandwidth signal, which is described in detail. With the application of the classical Displaced Phase Centre (DPC) technique, more spatial sampling along the synthetic aperture can be used and thus reduce the PRF.

For synthetic aperture radar imaging, stepped-frequency chirp signals are widely used to obtain high range resolution. One advantage of the approach is the reduction of the instantaneous bandwidth and sampling rate requirements of the radar system. To reconstruct the spectrum of a wideband signal, the amplitude and phase discontinuity between contiguous pulses should be removed. Otherwise, the discontinuity will defocus the range profile and degrade the range resolution. In this letter, a detailed internal calibration technique combined with stepped-frequency mode is proposed to eliminate the discontinuity and thus improve the focusing quality of the final image. The simulation and real raw data experiments are performed to validate the proposed method.