Multiple-input Multiple-output Synthetic Aperture Research Articles

A Novel Intrapulse Beamsteering SAR Imaging Mode Based on OFDM-Chirp Signals

The multiple-input multiple-output synthetic aperture radar (MIMO SAR) system has developed rapidly since its discovery. At the same time, the low-disturbance and high-gain requirements of the MIMO system are continuing to increase. Through the application of digital beamforming (DBF) techniques, the multidimensional waveform encoding (MWE) technique can play a key role in MIMO systems, which can greatly improve the system’s performance, especially the multi-mission capability of radar. Intrapulse beamsteering in elevation is a typical form of multi-dimensional waveform encoding which can greatly improve the transmitting efficiency and multi-mission performance of radar. However, because of the high sensitivity of the DBF technique to height, there is significant deterioration in performance in the presence of terrain undulations. The OFDM (Orthogonal Frequency Division Multiplexing) technique is widely used in communication. Due to the similarity of radar and communication systems and the great waveform diversity of OFDM signals, the OFDM radar has recently begun to emerge as a new radar system, simultaneously, the orthogonality of OFDM signals is in the time and frequency domains, and is not affected by terrain undulation. So, this paper proposes a novel radar mode combining intrapulse beamsteering in elevation and OFDM-Chirp signals, that is, the combination of “beam orthogonality” and “waveform orthogonality”, which can greatly improve the performance and fault tolerance to interference signals. In this manuscript, the system working mode and signal processing flow are introduced in detail, and simulations for both point targets and distributed targets are carried out to verify the feasibility of the proposed mode. Simultaneously, a comparison experiment is carried out, which shows the high level of fault tolerance to terrain undulation and the high potential of the proposed radar mode in Earth observation.

Platform motion estimation in multiple-input multiple-output synthetic aperture sonar with coupled variational autoencoders

Synthetic aperture sonar (SAS) utilizes the motion of the platform carrying the sonar system to synthesize an aperture that is much longer than thephysical antenna by coherently combining data from several pings. Coherent processing in SAS requires platform motion estimation and compensation with sub-wavelength accuracy for high-resolution imaging. Micronavigation, i.e., through-the-sensor platform motion estimation from spatio-temporal coherence measurements of diffuse backscatter on overlapping recordings between successive pings, is essential when positioning information from navigational instruments is absent or inadequately accurate. Representation learning with a variational autoencoder (VAE) offers an unsupervised data-driven micronavigation solution. In this study, we introduce a hierarchical variational model implemented with coupled VAEs to relate the common latent features between datasets of coherence measurements in broadband multiple-input multiple-output SAS systems. We show that self-supervising the training process of independently parameterized but coupled VAEs improves significantly the accuracy of the micronavigation estimates.

Object Recognition for Millimeter Wave MIMO-SAR Images Based on High-Resolution Feature Recursive Alignment Fusion Network

There are several complex situations in recognizing concealed objects from millimeter wave multiple-input multiple-output synthetic aperture radar (MIMO-SAR) security images, such as incomplete imaging of objects, partially occluded objects, and overlapping objects, which are detrimental to the accurate recognition of concealed objects. To solve these problems, a concealed object detection method based on a high-resolution feature recursive alignment fusion network (HR-FRAFnet) is proposed. The HR-FRAFnet can segment the object area from the grayscale image with complex human background and complete the recognition. The overall architecture of the HR-FRAFnet follows the encoder-decoder framework. Specifically, in the encoder stage, a deep parallel feature extraction network (DPFEN) connects the multi-resolution feature maps in parallel and repeats multi-scale feature fusion. This approach suppresses the background noise flowing and retains more recognizable target characteristics. Then, in the decoder stage, a feature recursive alignment fusion module (FRAFM) is designed to enhance the perception of object edges. The FRAFM effectively improves the segmentation accuracy of objects whereas decreasing the computational complexity of the network. Besides, we employ a combined loss function to alleviate the foreground-background imbalance problem in MIMO-SAR images. Homemade human security screening image datasets are used for evaluation. The experimental results show that the proposed method outperforms existing semantic segmentation methods in Mean Intersection over Union (mIoU) and reduces the incidence of missed and error detection of targets.

Ground-Based MIMO-SAR Fast Imaging Algorithm Based on Geometric Transformation

Ground-based multiple-input multiple-output synthetic aperture radar (MIMO-SAR) is a new type of deformation monitoring sensor that has the advantages of no mechanical motion and fast echo acquisition. Ground-based MIMO-SAR can significantly improve the data rate of deformation monitoring. In this paper, a fast imaging algorithm tailored for ground-based MIMO-SAR data is proposed, which can be applied in both far-field and near-field scenarios. First, the phase center approximation error of the non-collinear array in the near field is analyzed. Then, a fast imaging algorithm based on geometric transformation for the coherent synthesis of subimages is put forward. The algorithm uses the geometric transformation to convert the subaperture imaging results into the full aperture coordinate system, which avoids the point-by-point interpolation calculation and further reduces the computational cost of the subimage coherent synthesis algorithm. Simulations and experiments show that the algorithm can achieve high-precision focusing imaging, and its operation efficiency is significantly improved compared with the algorithm based on interpolation.

MIMO-SAR Interferometric Measurements for Wind Turbine Tower Deformation Monitoring

Deformations affect the structural integrity of wind turbine towers. The health of such structures is thus assessed by monitoring. The majority of sensors used for this purpose are costly and require in situ installations. We investigated whether Multiple-Input Multiple-Output Synthetic Aperture Radar (MIMO-SAR) sensors can be used to monitor wind turbine towers. We used an automotive-grade, low-cost, off-the-shelf MIMO-SAR sensor operating in the W-band with an acquisition frequency of 100 Hz to derive Line-Of-Sight (LOS) deformation measurements in ranges up to about 175 m. Time series of displacement measurements for areas at different heights of the tower were analyzed and compared to reference measurements acquired by processing video camera recordings and total station measurements. The results showed movements in the range of up to 1 m at the top of the tower. We were able to detect the deformations also with the W-band MIMO-SAR sensor; for areas with sufficient radar backscattering, the results suggest a sub-mm noise level of the radar measurements and agreement with the reference measurements at the mm- to sub-mm level. We further applied Fourier transformation to detect the dominant vibration frequencies and identified values ranging from 0.17 to 24 Hz. The outcomes confirmed the potential of MIMO-SAR sensors for highly precise, cost-efficient, and time-efficient structural monitoring of wind turbine towers. The sensors are likely also applicable for monitoring other high-rise structures such as skyscrapers or chimneys.

Efficient Millimeter-Wave Imaging Algorithm for Layered Dielectrics Based on MIMO-SAR With Nonuniform Transmitting Array

In this letter, an efficient near-field millimeter-wave (MMW) imaging algorithm is presented for layered dielectrics based on multiple-input–multiple-output synthetic aperture radar (MIMO-SAR) with nonuniform transmitting array. First, the model of target echo under MIMO-SAR configuration is built by dyadic Green's function, and the precise spectral echo expression is obtained through fast Fourier transform (FFT) and spherical-wave decomposition. Then, the image reconstruction of sparse MIMO-SAR is divided into separate single-input–multiple-output (SIMO)-SAR imaging problems, and the target's subimage corresponding to different SIMO-SAR setup can be quickly solved by employing inverse FFT, multistep phase compensation and wavenumber integration. Finally, the fully focused MIMO-SAR reconstructed image will be obtained by coherently accumulating all the SIMO-SAR results. Simulation analysis and experimental results validate the effectiveness the proposed algorithm.

A Novel MIMO-SAR Echo Separation Solution for Reducing the System Complexity: Spectrum Preprocessing and Segment Synthesis

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.

An Efficient MMW 3-D Imaging Algorithm for Near-Field MIMO-SAR With Nonuniform Transmitting Array

In this letter, an efficient millimeter-wave (MMW) frequency-domain imaging algorithm is presented for 3-D object reconstruction of the near-field multiple-input–multiple-output synthetic aperture radar (MIMO-SAR) with nonuniform transmitting array. For each single-input–multiple-output (SIMO) case of the MIMO-SAR setup, the precise spectral echo expression is derived by spherical-wave decomposition and fast Fourier transform (FFT) operations. To obtain the linear phase in range direction, the multiorder approximation theory is employed to expand the coupling phases, and thus the target subimage can be reconstructed by utilizing phase compensation, central wavenumber approximation, and inverse FFT. Finally, the fully focused 3-D image for MIMO setup will be realized through accumulating all the SIMO subimages. Compared with the existing representative algorithms, our method avoids complicated interpolation and achieves high-quality fast imaging with only matrix multiplication and a small amount of iteration operations. The experimental results validate the effectiveness of the proposed algorithm.

Improved DBF-MIMO-SAR Waveform Transmission Scheme for Reducing the Cost of DOF in the Elevation

The echo separation solution based on digital beamforming (DBF) in the elevation is quite applicable to multiple-input multiple-output (MIMO) synthetic aperture radar (SAR). For the current DBF-MIMO-SAR schemes, however, at least <inline-formula><tex-math notation="LaTeX">$\bm {2M-1}$</tex-math></inline-formula> subapertures in the elevation must be employed to successfully separate the aliased signal returns induced by the <inline-formula><tex-math notation="LaTeX">$\bm M$</tex-math></inline-formula> simultaneously transmitted waveforms, which essentially increases the system complexity. To this end, the paper proposes an improved waveform transmission scheme to exploit the potential benefits that MIMO concept can provide for a practical remote sensing system with limited available channels. In this scheme, the basic signal segments are coded by the improved phase coding matrix which is associated with the slow time. Afterwards, time-shift weighting, using the decoding matrix, is implemented to remove the interference from close arrival angles. In this process, the interference segments in near or far range can also be cancelled out. Consequently, the number of interferences has been halved and thereby, compared with the already-proposed DBF-MIMO-SAR schemes, e.g., short-term shift-orthogonal (STSO), the designed scheme only needs <inline-formula><tex-math notation="LaTeX">$\bm {M}$</tex-math></inline-formula> elevation channels for the realization of DBF-MIMO-SAR. Finally. numerous simulations have been carried out to demonstrate that the proposed scheme shows great potential in terms of echo separation for channel-limited MIMO SAR systems.

A Robust Digital Beamforming on Receive in Elevation for Airborne MIMO SAR System

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.

A Reconfigurable MIMO-SAR Transmission Scheme Based on Inter-Pulse and Intra-Pulse Joint Phase Modulation

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 paper, a reconfigurable MIMO-SAR transmission scheme based on inter-pulse and intra-pulse joint phase modulation is proposed. The proposed scheme has many advantages. First, lots of monostatic waveforms can be directly employed in a MIMO-SAR system, which offers flexibility in waveform selection. Second, according to different MIMO-SAR applications, it is reconfigurable and can flexibly adjust the system Degree of Freedoms (DoFs) to accomplish echo separation, achieving the best system performance, which is the key for the multimodal operation of MIMO-SARs. Finally, due to the limited system resources in the real MIMO-SAR system, it is hard to separate echo in a single domain, and the proposed scheme jointly capitalizes DoFs of Doppler, time, and space domains to ensure the successful echo separation. In addition, detailed simulation experiments are carried out to verify the practicability and effectiveness of the newly proposed transceiver schemes.

IRCI‐free multiple subband MIMO SAR

An inter-range cell interference (IRCI)-free multiple subband multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) algorithm is proposed to obtain a high-resolution wide swath (HRWS) imaging. The received signals of the proposed configuration are formulated as multiple-input single-output (MISO) system identification problems using the principle of the displaced phase centre in a way that all the subband waveforms are processed simultaneously without the need to separate them at the receiver. This would maximise the bandwidth utilisation efficiency. The channel impulse response in the range dimension is identified using a frequency domain system identification--based estimation algorithm, which is free from IRCI, instead of using conventional matched filters. A pulse repetition frequency lower than the Doppler bandwidth is used to obtain the HRWS imaging, and the resulted azimuth ambiguity is removed using a set of spatial filters applied on the received signals formulated as separate MISO system identification problems. Finally, both simulated and constructed raw data are used to validate the efficiency of the proposed algorithm.

A FFT-Based Millimeter-Wave Imaging Algorithm with Range Compensation for Near-Field MIMO-SAR

In this article, an improved fast Fourier transform (FFT)–based millimeter-wave imaging algorithm with range compensation is presented, which can be used to reconstruct 3D images for near-field multiple-input multiple-output synthetic aperture radar (MIMO-SAR). The frequency-domain interpolation is avoided and only one-step spherical-wave decomposition is employed in this algorithm. During the image reconstruction process, the amplitude factor is considered for the compensation of signal propagation loss, and the final target image can be obtained by FFT/IFFT and coherent accumulation steps. As demonstrated with numerical theoretical analysis and experimental results, the proposed method greatly reduces the computational load but ensures the quality of image reconstruction compared to the back-projection (BP) algorithm. Moreover, it is superior to the MIMO-range migration algorithm (MIMO-RMA) in compensating propagation loss and other performance indexes in the image reconstruction results.

DBF Processing in Range-Doppler Domain for MWE SAR Waveform Separation Based on Digital Array-Fed Reflector Antenna

With the rapid development of the multiple-input multiple-output synthetic aperture radar (MIMO SAR) system, the demands for miniaturization and high gain of antenna are increasing. The digital array-fed reflector antenna has such virtues so that it can play an important role in such system. However, the geometric models and signal models based on a reflector antenna are considerably different from the directly radiating planar antenna. The signal processing for the reflector antenna is more complex and difficult. As a result, the applications of the reflector antenna in SAR system are not as mature as those of the planar antenna. A combination of multidimensional waveform encoding (MWE) technique and digital beamforming (DBF) technology at the receiving end can greatly improve the MIMO SAR system performance, especially ambiguity suppression and waveform separation. This configuration can realize different radar functions and meet multidimensional observation requirements, such as the polarized SAR. Thus, this study combines digital array-fed reflector antenna and the DBF technique in the elevation direction for MWE SAR waveform separation. The echo models for the array-fed reflector antenna and the planar antenna are established based on short-time shift-orthogonal waveforms. In the models, a mismatch in steering vectors is inevitable if DBF processing is continuously performed traditionally in the azimuth-elevation two-dimensional time domain. This mismatch will worsen the waveform separation effect and the image quality. Therefore, we propose a DBF method which is processed in range-Doppler domain. The method enables waveform separation without ambiguity at the receiver. Then, the conventional SAR imaging methods are enabled, and we acquire an ideal SAR image. The simulation results for both point targets and distributed targets prove the effect and feasibility of the proposed DBF method.

Segmented Phase Code Waveforms: A Novel Radar Waveform for Spaceborne MIMO-SAR

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.

A Novel Spaceborne MIMO-SAR Imaging Scheme Based on Improved OFDM Waveforms

In recent years, the multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) concept has been widely researched because it can provide more degrees of freedom to dramatically improve SAR system performance. However, the echo separation issue of different transmit antennas is the most challenging issue and it stirs up extensive discussions. In this letter, a novel MIMO-SAR imaging scheme based on the improved orthogonal frequency-division multiplexing (OFDM) waveforms is proposed. The main contributions of this work are that: <list list-type="ordered" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><list-item><label>1)</label> Improved generation method for <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> OFDM waveforms is presented. This method can compensate the extra carrier frequency deviation and compared with the other compensation methods, this method is more general and suitable for <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> OFDM waveforms. </list-item><list-item><label>2)</label> Based on the proposed OFDM waveforms, a novel and low-cost spaceborne MIMO-SAR imaging scheme is proposed. </list-item> </list> In this scheme, a simple time-shift weighting process and a bandpass filter bank are employed to separate the echoes from the close arrival angles. Then, the digital beamforming (DBF) on receive in elevation is employed to separate the echoes from far arrival angles. Furthermore, the distributed scene simulation results are presented to verify the practicability of the proposed scheme.

Analysis and Optimization of a Pulse Repetition Frequency for Along-Track Distributed Multiple-Input Multiple-Output Synthetic Aperture Radar

A distributed multiple-input multiple-output synthetic aperture radar (MIMO-SAR) system combines azimuth multi-channel and digital beamforming technologies to produce data with a high-resolution azimuth and wide swath. The MIMO-SAR system uses a tight along-track formation, and the spacing between its satellites is typically 100 m. The space sampling characteristic is sensitive to changes in pulse repetition frequency (PRF). This paper presents a method for optimizing the PRF of a distributed MIMO-SAR system based on the performance of the latter. The optimized PRF adapts well to variations in satellite spacing. These results show that PRF optimization can effectively improve the performance of the distributed MIMO-SAR system.

Implementation of a MIMO-SAR Imaging Mode Based on OFDM Chirp Waveforms

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.

Range-Ambiguous Clutter Suppression for the SAR-GMTI System Based on Extended Azimuth Phase Coding

A range-ambiguous clutter suppression approach based on extended azimuth phase coding (EAPC) is proposed to handle the range ambiguity of the multiple-input multiple-output synthetic aperture radar (MIMO-SAR) system for ground moving target indication (GMTI) application. The echoes from different ambiguous range regions can be well separated in the transmit spatial frequency domain by properly designing the EAPC shift factor. In the sequel, a set of transmit filters are employed to extract the echoes of each ambiguous region independently. Then the azimuth deramp operation is applied to the extracted data to focus the target energy of the desired region while the residual target energy of other regions is still smeared due to the mismatched reference function. After this, the adaptive matched filtering algorithm is adopted to suppress the clutter and detect the moving target. Finally, numerical simulation experiments are presented to demonstrate that the developed framework can obtain good results for range-ambiguous clutter suppression and ground moving target detection.

Ultrahigh Resolution Wide Swath MIMO-SAR

A new multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) configuration using multiple contiguous azimuth beams is proposed to map wider image swaths with higher cross-range resolution as compared with the conventional MIMO-SAR. The proposed configuration is independent of the orthogonal waveforms used for transmission and it allows the use of all the phase centers including the overlapping ones to reduce the minimum operating pulse repetition frequency that should be satisfied to avoid aliasing in the azimuth dimension unlike the case of the conventional MIMO-SAR in which only the nonoverlapped phase centers and one of each overlapped phase centers are utilized. This is the result of employing multiple contiguous azimuth beams which makes the echoes, whose effective phase centers are overlapped, occupy different Doppler bandwidths. Each transmitted waveform consists of a sequence of subpulses such that each subpulse is a conventional linear frequency modulated waveform. Echoes corresponding to different phase centers at a given receiver are separated using digital beamforming on receive in elevation. The estimated range profile is free from interrange cell interference as frequency domain system identification-based estimation algorithm is used to identify the impulse response in the range dimension. Finally, both simulated and constructed raw data are used to validate the efficiency of the proposed algorithm.