In azimuth multichannel high-resolution and wide-swath (AMC-HRWS) synthetic aperture radar (SAR) system, undersampling of azimuth signal results in the failure of the single-channel echo imaging, so the echoes of all the channels should be reconstructed to obtain the unambiguous SAR image. Many methods have been proposed to reconstruct the stationary scene echoes. However, moving targets (MTs) will cause false targets in the reconstructed SAR image, which has a great influence on SAR image interpretation and moving target detection, especially in maritime scenes. Hence, we propose an unambiguous imaging method of the moving target for maritime scenes with AMC-HRWS SAR. First, azimuth deramp processing is introduced to obtain coarse-focused moving targets, and then their echoes can be extracted from the sea clutter. Based on the extracted data, a radial velocity estimation method is proposed, which is high efficiency and does not require redundant channels. In addition, based on the estimated radial velocity and the characteristics of the coarse-focused signal, a novel signal reconstruction method of moving target is presented. The reconstruction performance of this method is not affected by channel imbalance, and false targets can be removed even if there is radial velocity error. Besides, the effectiveness of this scheme is verified by the simulation data and GaoFen-3 SAR real data. The estimated radial velocities of ships are verified by automatic identification system (AIS) information. The imaging results show that false targets are effectively suppressed, and moving targets are located in correct positions.

Segmentation is an essential part in SAR image analysis and application. However, the presence of speckle noise and intensity inhomogeneity regions leads to great difficulty in SAR image segmentation. In this letter, we propose a novel level set method that integrates the local intensity and the global feature information for better segmentation results. To establish the energy function, a new image model is developed to describe the inhomogeneous SAR images and form the local intensity clustering term. Meanwhile, the feature map extracted by invariant moment is used to define the global fitting term through a piecewise constant function. Segmentation is realized by solving the level set function from the minimization of the energy function. Experiments on the synthetic and real SAR images verify the effectiveness of the proposed method.

Azimuth ambiguity degrades the quality of synthetic aperture radar (SAR) images and leads to the increase of false alarm rate in ground moving target indication (GMTI). Due to the existing azimuth ambiguity, suppression methods do not remove the first-order ambiguity completely and ignore the ambiguity above first order as well, moving target detection is affected by residual ambiguity. Hence, a novel method to suppress first-order and higher order azimuth ambiguities for the dual-channel SAR/GMTI is proposed in this letter. First, the displaced phase center antenna (DPCA) technique is applied to suppress clutter. Then, estimate the local azimuth ambiguity-to-signal ratio (LAASR) to find out the area affected by ambiguity. Finally, an inpainting algorithm is improved to patch the ambiguity area. The proposed method can remove the ambiguity almost completely. Moreover, the method is verified using the GaoFen-3 SAR dual-channel complex image data, and the result shows that the false alarm of moving target detection is degraded without reducing the detection rate.

In this letter, a novel and low-cost echo separation technique for the multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is presented, based on the orthogonal frequency-division multiplexing (OFDM) chirp waveforms. The proposed scheme allows the generation of multiple OFDM chirp waveforms on common spectral support. In the new scheme, a series of simple time-domain operations including replica, T-shift, and superposition is applied to eliminate the interference waveform within a limited time. Then, a combination with a bandpass filter instead of a matched filter to focus signal power and digital beamforming (DBF) on receive in elevation enables the suppression of interference signals for a realistic spaceborne SAR scenario, where the swath width exceeds the spatial extension of the transmitted pulse. Furthermore, the distributed scene simulation results are presented to verify the practicability of the proposed scheme.

The echo separation issue associated with different transmit antennas is the most technical challenge in realizing the multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) system. In this article, a novel MIMO-SAR imaging scheme based on an advanced radar waveform, namely, segmented-phase-code (SPC) waveform, is proposed. Compared with the state-of-the-art short-term shift-orthogonal (STSO) waveform beamforming schemes, this scheme relieves the short-term shift-orthogonality condition of transmitted waveforms without losing the imaging performance, which extends the optional waveform space. In this scheme, the separation of the echoes from close arrival angles is ensured by a simple time-shift weighting processing. Furthermore, a range bandpass filter bank and the digital beamforming (DBF) technique are employed to ensure that the echoes from far arrival angles are separable. Finally, detailed simulation experiments are performed to verify the feasibility of the proposed scheme, and in-depth discussions of different waveforms and MIMO-SAR imaging schemes are presented.

For synthetic aperture radars (SARs), an alternate transmitting mode based on waveform diversity is widely discussed for suppressing range-ambiguity in many letters, because it is easy to implement and there is no need to improve the pulse repetition frequency (PRF). These studies mainly focus on the discussion of pseudo-orthogonal waveform design, such as up-down chirp waveforms and orthogonal-frequency-division-multiplexing (OFDM) waveforms; however, the effect on imaging caused by waveform diversity is ignored. This letter, for the first time, provides a demonstrative derivation of imaging for the alternate transmitting mode, which will deepen the understanding of this mode and be helpful for the future research. In this letter, we point out that transmitting different waveforms will introduce a phase-amplitude periodic modulation in the azimuth domain; furthermore, it will cause the aliasing of the azimuth spectrum. In addition, the simulation experiment is performed for verifying the correctness of the theoretical analysis.

Azimuth ambiguity greatly affects the image quality and application of synthetic aperture radar (SAR). Several azimuth ambiguity suppression methods have been proposed; however, these methods cannot remove the ambiguity completely and only the first-order ambiguity has been considered. Hence, in this letter, a novel method based on Wiener filtering and local azimuth ambiguity-to-signal ratio (AASR) estimation for N-order azimuth ambiguity suppression is proposed. The Wiener filtering is used to attenuate the ambiguity energy. Then the original image and the filtered image are combined to estimate local AASR, which is used to identify the ambiguity pixel. Finally, the ambiguity can be removed via interpolation. Through this method, the N-order ambiguity energy can also be suppressed to a lower level, and simultaneously, the consistency, resolution, and signal-to-noise ratio of an SAR image are maintained. Furthermore, in order to verify the practicability of the proposed method, it has been tested on the GaoFen-3 image and TerraSAR-X image.

It is well known that the nonlinear frequency modulation (NLFM) chirp waveform can shape advantageously the power spectrum density (PSD) such that the autocorrelation function exhibits reduced sidelobes as the window function. However, differences between the PSD and window function due to the Gibbs effects caused by the Fresnel integral would lead to deteriorative performance of the NLFM chirp waveform. In particular, the correlation function of NLFM waveform with Chebyshev PSD is seriously inconsistent with the lowest sidelobe level of the Chebyshev window function possesses. To overcome the inconsistency, therefore, in this letter, a novel NLFM waveform with modified Chebyshev window PSD is proposed, which combines the Chebyshev with edge distortion compensation, allowing, in theory, low sidelobe level as Chebyshev window. Using theoretical analysis also confirmed by simulation, this letter shows that the novel NLFM waveform possesses low sidelobes without high computational complexity in design.

It is well known that the nonlinear frequency modulation (NLFM) waveform with the advantage that it can shape the power spectral density (PSD) to provide a radar matched filter output with lower sidelobe without the loss of signal-to-noise ratio (SNR) when compared with the linear frequency modulation (LFM) waveform. But NLFM waveform would also broaden the main lobe and reduce the range resolution. In this paper, we report a novel waveform optimization framework. Through this framework, an advanced nonlinear frequency modulation (NLFM) waveform with lower sidelobes and a smaller main lobe is constructed. In addition, we apply it in a real synthetic aperture radar (SAR) system with a bandwidth of 100 MHz at 9.6 GHz carrier frequency and the imaging results validate the proposed NLFM waveform.

Range ambiguity suppression is a technical challenge for current synthetic aperture radar systems. A potential solution is to orthogonally modulate the transmitting pulses; however, these orthogonal waveforms (e.g., up-down chirp waveforms) actually cannot reduce the cross correlation energy (CCE). Nonlinear frequency modulation (NLFM) waveform can change the time-frequency relationship to adjust the energy distribution within the bandwidth to reduce the CCE. In this letter, a novel orthogonal NLFM waveform optimization framework is proposed. Through this framework, advanced NLFM waveforms with low sidelobe and CCE are constructed. Furthermore, point and distributed scene simulation results are presented to verify the practicability of the proposed waveforms. In addition, the system scheme, waveform design, and range ambiguity suppression performance are detailed.

Generally, synthetic aperture radar (SAR) system transmits linear frequency modulation (LFM) signal to obtain the high-resolution image and weighted windowing is usually employed to suppress sidelobes. However, it will cause a 1-2-dB signal-to-noise ratio (SNR) loss. Nonlinear frequency modulation (NLFM) signal, which can construct the signal's power spectral density (PSD) to reduce sidelobes without loss of SNR, is a promising candidate. However, the real-time generation of precise NLFM signal is still a technical challenge. In this letter, a high-precision NLFM signal generator with the ability of predistortion compensation is developed, and this signal generator will be employed in LuTan-1 (LT-1, i.e., TwinSAR-L) mission which is an innovative spaceborne bistatic SAR mission and planned to launch in 2020. In addition, a two-step error compensation method is developed to compensate the system error. Finally, the ground experiment is performed to validate the designed signal generator.

With the development of high-resolution radar satellite for global comprehensive environmental monitoring, day-and-night and all-weather surveillance has become an active and growing research field. However, in all cases, these applications require radar to have a high-efficiency radar module (e.g., T/R module), and high system transmitting power. These requirements may put an important limitation on the performance of a radar satellite with a high-power configuration. In this paper, we report a novel waveform optimization framework. Through this framework, an advanced nonlinear frequency modulation (NLFM) waveform with lower sidelobes and a smaller main lobe, which can significantly relieve the restriction of very limited satellite power, is constructed. In addition, we apply it in a real synthetic aperture radar (SAR) system with a bandwidth of 100 MHz at 9.6-GHz carrier frequency and the whole process of the NLFM waveform for radar imaging is discussed in detail, including the system architecture and configuration, a system error compensation method, and a modified chirp scaling algorithm (CSA). The imaging results demonstrate the excellent performance of the advanced NLFM waveform. Moreover, we observe that the SAR system with the advanced waveform has a higher signal-to-noise ratio (SNR) of 1.29 dB compared with the conventional linear frequency modulation (LFM) waveform. The improvement of 1.29-dB SNR means that the real radar system can reduce transmitting power with a ratio of 25%. This effect is likely to be a potential feature of NLFM waveform, which can reduce the transmitting power requirement, especially for radar satellite.