Waveform decoupling is usually considered a more technical challenge for fully exploiting the potential benefits provided by multiple-input–multiple-output (MIMO) synthetic aperture radar (SAR) structure. Spotlighted as a promising solution to this challenge, the well-known orthogonal-waveform beamforming scheme has become increasingly popular. However, in some cases, the performance of digital beamforming (DBF) involved in this scheme may be significantly degraded due to the nonlinear array configuration under stringent space constraints. Up until now, relatively little research on robust DBF on receive in elevation has been presented for a nonlinear array configuration. To alleviate this, we here propose a least absolute shrinkage and selection operator (LASSO) regression-based DBF technique for the improved segmented phase coding (SPC) decoupling scheme. First, a generalized steering vector formation model based on a 3-D geometric vector is provided for the subsequent DBF operation. Given that, due to the nonlinear array configuration, the calculated steering vector exhibits space-varying characteristics within the azimuth pulse extension of the illumination beam, steering vector constraints for the desired signal and interferences are subsequently designed to allow for such variation within the azimuth footprint. Furthermore, the beamforming problem is addressed by generalized LASSO regression to approach the goal that providing a distortionless response and deep nulls for each desired signal and interference component within the azimuth pulse extension. Finally, we assess the feasibility and performance of the proposed LASSO regression-based DBF technique for waveform decoupling with the use of numerical simulations.

The separation of multiple transmit waveforms with time and frequency synchronization constitutes a considerable challenge for multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) systems. It is well-known that aliased signal returns may be separable by digital beamforming (DBF) on receive in elevation. However, the current orthogonal-waveform beamforming schemes significantly increase the hardware complexity. Moreover, the direction of arrival (DOA) mismatch issue caused by topographical variations significantly increases the complexity of the DBF process. To alleviate these issues, we here introduce a multiple-subpulse separation and weighting synthesis (MSS-WS) echo separation framework, which is formed using segmented phase coding (SPC) waveforms. The proposed MSS-WS scheme can halve the number of interferences from far arrival angles, allowing for a reduction of the system complexity. In addition, constrained/generalized least absolute shrinkage and selection operator (LASSO) regression is exploited to form the beamformer with relatively high robustness in terms of dealing with the presence of topographical variations. The so-called LASSO-based dynamic beam response (LASSO-DBR) technique introduced here contains two parts: the source localization and the beamforming based on the designed constraint matrices. In this respect, the proposed LASSO-DBR beamformer can produce a distortionless response to the desired signal and still yield wide nulls for the unwanted interferences. Using numerical simulations, we illustrate the feasibility and performance of the proposed MSS-WS framework using the LASSO-DBR beamforming technique.

To address the echo separation issue involved in multiple-input multiple-output (MIMO) synthetic aperture radar (SAR), the elevation beamforming solution has become increasingly popular and been widely investigated. However, the current elevation digital beamforming (DBF) schemes usually require high hardware complexity, which is not allowed for practical MIMO-SAR systems. To alleviate this problem and achieve a low-cost MIMO-SAR system, we here detail an improved two-stage echo separation scheme, i.e., subband match filtering and DBF (SMF-DBF). First, the subband match filtering enables the number of interference components to be halved. Afterwards, the remained interferences from far arrival angles will be suppressed by DBF techniques. The two-stage processing can considerably simplify the array configuration and reduce the system complexity. Numerical simulations have demonstrated the feasibility and potential of the proposed method for channel-limited MIMO-SAR systems.

Ground armored weapons have a high detection value in military operations. Satellite synthetic aperture radar (SAR) cannot accurately detect military targets with meter-level sizes limited by resolution of sensors. Airborne SAR have strict experimental conditions and cannot be applied in actual battlefield environments. MiniSAR sensors, which combine the advantages of submeter-level ultrahigh resolutions and flexible flight, play a crucial role in recognizing military targets. In this paper, various small military targets in real complex ground scenarios are detected with the MiniSAR of NUAA. However, there are still two difficulties. First, because of a limitation in the number of flight circles, the number of obtainable military target samples is not sufficient to adapt to the traditional deep learning methods that rely on a large number of image samples. Second, due to the imaging systems and different depression angle of MiniSAR, the SAR images of MiniSAR suffer from the same deformation challenge as the moving and stationary target acquisition and recognition (Mstar) with high depression angle. To address these two challenges, we propose a FASAR-Net framework based on few-shot learning with meta learning and adversarial domain learning, combined with the inherent scattering features of the SAR targets. Furthermore, we validate the reliability and accuracy of this algorithm on Mstar and our datasets, and the result of recognizing small SAR targets is compared with our algorithm and other classical algorithms. We conclude that the proposed algorithm has high accuracy in the recognition of the deformation small targets under the few sample condition.

Multi-input and multi-output (MIMO) radar is an advanced radar system, which grows into a promising candidate for the future synthetic aperture radar (SAR) because the MIMO radar can provide more degrees of freedom (DOFs). Monostatic MIMO SARs (where transceiver channels share the same antenna array) will produce lots of repeated equivalent phase centers (EPCs) due to the same wave path, and these repeated EPCs actually have no improvement to the DOFs of the radar system, resulting in a tremendous waste of the radar resources. To this end, this paper devises a novel radar framework, which is referred to as MIMO SAR with interpulse phase coding and multi-carrier (IPCMC). The IPCMC scheme employs multi-carrier and well-designed phase codes in transmitting channels, which has the advantage of increasing the DOFs in elevation. Concretely, by introducing the carrier information into the transmission-receiving spatial frequency domain, non-overlapped spatial frequency difference curves can be obtained to further increase the DOFs in elevation. Furthermore, an advanced range ambiguity separation method based on the proposed IPCMC MIMO SAR is presented. Compared with SAR systems with different numbers of DOFs, the proposed IPCMC MIMO scheme can precisely separate more ambiguous regions, due to the increased DOFs. Finally, detailed simulation experiments are carried out to verify the efficacy of the proposed IPCMC MIMO SAR.

Barrage jamming technique with controllable jamming coverage against synthetic aperture radar (SAR) systems is of great importance in electronic countermeasures. However, it is still a difficulty for the jammer to accurately impose controllable two-dimensional (2-D) local jamming on the regions of interest (ROIs). In this respect, a new parameterized and large-dynamic-range precise controllable (PLDR-PC) jamming method has been proposed in this paper to assist in solving such problems. Based on the SAR imaging properties of linear frequency modulation (LFM) case, the range and azimuth modulation factors have been well designed to generate large dynamic controllable coverage of jamming signals with high 2-D processing gain. In such a context, the PLDR-PC technique can provide the optimal power allocation and considerably reduce the jamming power while still ensuring the satisfactory performance. The proposed PLDR-PC technique can improve the jamming efficiency and considerably reduce the exposure probability of the jammer. Moreover, to improve the barrage jamming performance, the parameter estimation error model is also established to determine the simple yet valid jamming strategy in practical implementations. Finally, extensive numerical simulations in comparison with the current jamming methods have been carried out to demonstrate the effectiveness and prospect of the PLDR-PC technique against airborne/spaceborne SAR systems.

The problem of echo separation using digital beamforming (DBF) on receive for multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is of notable importance to allow for practical systems. Regrettably, current DBF-MIMO-SAR schemes, such as the short-term shift-orthogonal (STSO) scheme, are computationally cumbersome, increasing the required hardware complexity. To alleviate this problem, we here propose an improved echo separation solution for realizing a low-cost MIMO-SAR system. We detail a generic waveform design scheme as well as optimized monostatic radar waveforms (e.g., nonlinear frequency modulation (NLFM) signal) showing how these can be directly adopted in the proposed scheme to improve the imaging performance. The proposed scheme enables the number of the interference segments generated by unmatched waveforms to be halved by the use of the fast time spectrum preprocessing and segment synthesis, dramatically simplifying the array configuration and reduces the system complexity. By exploiting inter-pulse phase coding techniques, the proposed method can provide a reconfigurable waveform transmitting scheme, allowing the system resources in range frequency, elevation space, and Doppler domains to be jointly exploited for the separation of aliased signal returns. The proposed scheme is evaluated using extensive numerical and measured data sets, demonstrating the feasibility and potential of the proposed method for resource-limited spaceborne/airborne MIMO-SAR systems.

This paper deals with a novel transmitted scheme for a multi-subcarrier frequency MIMO-SAR system, which aims at suppressing the intrapulse repeater mainlobe-jamming and immensely improving the dynamic range of the receiver. To this end, due to the multi-subcarrier frequency transmission scheme, the mixed signal with true target signal and repeater jamming can be separated by a well-designed spatial-frequency filter. Thus, the range and direction of arrival (DOA) information is accurately estimated without interrupting the normal work of the radar. Furthermore, to further improve the orthogonality of transmitted waveform, the design of a phase-coded LFM waveform pair exhibiting both low cross-correlation energy (CCE) and low peak to sidelobe ratios (PSLRs), is considered. Besides, to handle the resulting nondeterministic polynomial (NP) hard problem, an alternating direction multiplier method (ADMM) based optimization method is employed. Compared with the traditional jamming suppression method, the proposed method improves the degree of freedom (DOF) from the carrier frequency domain, and it has the capability to suppress the intrapulse repeater mainlobe-jamming. Finally, detailed simulation experiments are carried out to verify the practicability and effectiveness of the newly proposed transceiver schemes.

The range ambiguity issue is a technical challenge in the radar community and has been widely discussed over the years. Researchers have given special attention to multiple-input and multiple-output (MIMO) radar to address the range ambiguity because this radar system can employ more equivalent degrees of freedom. Open studies on MIMO radar are generally based on the assumption of orthogonal waveforms, whereas radar performance is seriously limited by distributed targets due to mismatched energy. To this end, this paper deals with a novel MIMO radar transmission scheme called transmitter interpulse phase coding (TIPC) without using orthogonal waveforms. First, a set of well-designed TIPC codes are employed to modulate transmitter subarrays with the same modulated signal. Second, in the case of high pulse repetition frequency (PRF)1, aliased echoes from different transmitted channels are directly separated by a group of simple Doppler filters; for normal PRF2radar systems, a technique called digital beamforming in azimuth is exploited to ensure an effective multiple waveform separation. Third, a decoding processing is performed for a further derivation of the residual TIPC matrix that is related with ambiguity order. Next, the desired and ambiguous echoes are separated by a specifically designed spatial filter that absorbs the residual TIPC matrix. Particularly, the separated signal can be used for some further applications such as increasing the observation swath. Finally, point-like target and distributed targets simulation experiments are performed to verify the feasibility of the proposed TIPC MIMO radar.

The echo separation issue for multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is usually regarded as a more technical challenge. Spotlighted as a promising solution to the echo separation, the well-known short-term shift-orthogonal (STSO) beamforming scheme has become increasingly popular. However, for airborne MIMO SAR systems, the digital beamforming (DBF) involved in the STSO scheme usually encounters more issues, e.g., the direction of arrival (DOA) mismatch induced by topography variation. Up to now, relatively less research on robust DBF processing has been conducted for airborne MIMO SAR systems. In this respect, an adaptive DBF technique, based on interference plus noise covariance matrix (IPNCM) reconstruction and desired signal steering vector estimation, has been proposed in this paper. IPNCM reconstruction and steering vector estimation can not only cope with the DOA mismatch problem, but also remove the desired signal component in the training data cells to increase the beamformer convergence rates. Consequently, the proposed approach really improves the array output signal-to-interference-plus-noise ratio (SINR). Moreover, numerous discussions and simulations are carried out to prove the effectiveness of proposed DBF technique under various disturbance environments. Compared with the current DBF techniques, the proposed method provides a bright application prospect for the STSO scheme.

Synthetic aperture radar (SAR) distributed target scene raw signal simulation is an important tool for the study and test of SAR systems and processing algorithms, mission planning, and inversion algorithm design. In this paper, the squint spotlight SAR scene model is evaluated to achieve spotlight SAR raw signals in the 2-D frequency domain and the precision of the model is analyzed. It is known that the range migration phenomenon in the time domain is explained as the coupling between the range and azimuth in the 2-D frequency domain. To realize the coupling relation in the 2-D frequency, interpolation may be needed. However, interpolation is a time-consuming manipulation. For efficiency, some signal processing methods are employed to couple the range and azimuth frequencies. Those tricks are derived from some optical principles, which give us some novel thoughts. Therefore, the efficiency of the simulator is highly improved, which facilitates its application to the verification and test of the real-time processor.