Open Access Publications - Department of Electrical and Computer Engineering
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Open access publications by faculty, postdocs, and graduate students in the Department of Electrical and Computer Engineering
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Item Enhanced Matrix Completion Method for Super-resolution Tomography SAR Imaging: First Large-scale Urban 3-D High-resolution Results of LT-1 Satellites Using Monostatic Data(IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025-08-29) Zhou, Honghao; Xu, Gang; Gen Xia, Xiang; Yu, Hanwen; Li, Tao; Zhang, Xiang; Xing , Mengdao; Hong, Wei; Liu, YanyangLuTan-1 (LT-1) constellation is an innovative distributed L-band spaceborne synthetic aperture radar (SAR), which can potentially provide tomographic mapping with twin satellites, i.e., Tomographic SAR (TomoSAR) imaging. Usually, compressed sensing (CS) techniques can be used in TomoSAR imaging to improve the elevation resolution by exploiting the layout sparsity. However, the off-grid effect of discrete dictionary used in traditional CS methods tends to dramatically degrade the imaging performance. In this paper, a novel non-convex enhanced matrix completion (NcEMC) algorithm is proposed for gridless super-resolution TomoSAR imaging. Specifically, a Hankel matrix completion model is firstly designed to effectively exploit the latent data structure in an off-grid manner. Benefiting from the enhanced low-rankness of Hankel matrix form, a more refined uniform baseline observation is reconstructed from the original configuration using the optimization of matrix completion with the achievement of signal enhancement. To avoid using a regularization term to balance the traditional singular value decomposition solution of Hankel matrix, the proposed algorithm restates the low-rank constraint in a symmetric decomposition manner, which is beneficial to reduce the computation cost. Subsequently, an incoherence condition is introduced as a significant constraint in the non-convex Hankel matrix reconstruction process. To this end, a projected gradient descent iteration method is designed to satisfy the incoherence condition, thereby facilitating a more robust and accurate process of data reconstruction. Meanwhile, this paper presents the first large-scale urban 3-D high-resolution results of LT-1 satellites. We use a collection of 10 repeat-pass LT-1 monostatic SAR images to demonstrate the entire processing in tomographic SAR imaging application and the superiority of the proposed algorithm.Item Coherently distributed RF antenna arrays using photonic links(Optics Express, 2025-08-21) Chowdhury, Shadia Islam; Sinigaglio, Hannah; Ullah, Md Saheed; Shi,Shouyuan; Qi, Xiao-Feng; Mait, Joseph N.; Schneider, Garrett J.; Murakowski, Janusz; Prather, Dennis W.This paper uses radio-frequency-over-fiber (RFoF), or RF-photonic links, to implement a remotely distributed antenna system that preserves both the spatial and temporal coherence of RF signals, over long distances with negligible propagation loss. The system is used to implement optimized complex weights, on distributed antenna elements, to realize “flat,” i.e., lying in the plane of propagation, holographic field profiles. Experimental validation of a one-dimensional indoor system is used to demonstrate such “in-plane” holograms along with their comparison to simulation results.Item Data Privacy Made Easy: Enhancing Applications with Homomorphic Encryption(ACM Transactions on Design Automation of Electronic Systems, 2025-02-24) Gouert, Charles; Tsoutsos, Nektarios GeorgiosHomomorphic encryption is a powerful privacy-preserving technology that is notoriously difficult to configure and use, even for experts. The key difficulties include restrictive programming models of homomorphic schemes and choosing suitable parameters for an application. In this tutorial, we outline methodologies to solve these issues and allow for conversion of any application to the encrypted domain using both leveled and fully homomorphic encryption. The first approach, called Walrus, is suitable for arithmetic-intensive applications with limited depth and applications with high throughput requirements. Walrus provides an intuitive programming interface and handles parameterization automatically by analyzing the application and gathering statistics such as homomorphic noise growth to derive a parameter set tuned specifically for the application. We provide an in-depth example of this approach in the form of a neural network inference as well as guidelines for using Walrus effectively. Conversely, the second approach (HELM) takes existing HDL designs and converts them to the encrypted domain for secure outsourcing on powerful cloud servers. Unlike Walrus, HELM supports FHE backends and is well-suited for complex applications. At a high level, HELM consumes netlists and is capable of performing logic gate operations homomorphically on encryptions of individual bits. HELM incorporates both CPU and GPU acceleration by taking advantage of the inherent parallelism provided by Boolean circuits. As a case study, we walk through the process of taking an off-the-shelf HDL design in the form of AES-128 decryption and running it in the encrypted domain with HELM.Item Movable Antenna Enabled Near-Field MU-MIMO Communication(IEEE Wireless Communications Letters, 2025-07-25) Pi, Xiangyu; Zhu, Lipeng; Mao, Haobin; Xiao, Zhenyu; Xia, Xiang-Gen; Zhang, RuiThis letter investigates movable antenna (MA)-enabled near-field multiuser multiple-input multiple-output (MU-MIMO) systems, in which the base station (BS) equipped with an MA array serves multiple users equipped with fixed-position antenna (FPA) arrays. First, we present the near-field channel model to characterize channel variations with different positions of the MAs in a large moving region. Then, we aim to maximize the weighted sum-rate (WSR) of users by jointly optimizing the antenna position vector (APV) and precoding matrix at BS, subject to the constraints on antenna movement and maximum transmit power. To address the formulated challenging optimization problem, we discretize the feasible antenna moving region into a discrete-position set, and transform the problem into a sparse signal recovery framework. Next, based on the orthogonal matching pursuit (OMP) method, the suboptimal MAs’ positions are selected from the discrete-position set and the precoding matrix is simultaneously updated in closed-form to align with the APV changes. Simulation results show that the proposed MA-enabled system can significantly improve near-field MIMO channel conditions and enhance multi-stream transmission via antenna position optimization, achieving substantial performance gains over conventional FPA-based schemes.Item Information theoretical computational lithography based on pattern density statistics(Optics Express, 2025-04-10) Wang, Bingyang; Ma, Xu; Liu, Jiamin; Jiang, Hao; Liu, Shiyuan; Arce, Gonzalo R.Computational lithography is an important technology to improve the image resolution and fidelity of the optical lithography process. Recently, information theoretical models were introduced to explore the physical limit of image fidelity that can be achieved by different computational lithography methods. However, the existing models were derived based on a simple and idealized assumption of uniform pattern density, thus rendering a loose lower bound on the lithography imaging error. This work improves the accuracy of the information theoretical model by introducing a statistical approach of pattern density. In particular, a density classification rule (DCR) of mask and print image is established based on a number of randomly generated layout samples. The information transfer function between the mask and print image is formulated under the DCR constraint. Then, the optimal information transfer (OIT) and the theoretical limit of lithography image fidelity are derived using a numerical optimization algorithm with mask manufacturing regularization. It has been proved analytically and experimentally that our proposed model provides a much more accurate theoretical limit of lithography image fidelity than the conventional approach.Item Short-range order and longer-range disorder revealed in germanium–tin alloy thin films by extended x-ray absorption fine structure analysis Open Access(Journal of Applied Physics, 2025-04-08) Lentz, J. Zachary; Zhao, Haochen; Woicik, J. C.; Zeng, Yuping; McIntyre, Paul C.Short-range order (SRO) in semiconductor alloys, a relatively under-studied structural phenomenon in which local atomic arrangements differ from those of a random solid solution, is investigated in molecular beam epitaxy (MBE)-grown GeSn thin films. A novel preparation technique is used to pattern these films into microscale ribbons that are released from the substrate for extended x-ray absorption fine structure (EXAFS) analysis. The results indicate a strong SRO in which the first shell around Sn atoms is greatly denuded of Sn atoms relative to the nominal atomic composition of the alloy. This effect is more pronounced than that observed recently in GeSn nanowires grown by chemical vapor deposition. Additionally, the presence of a longer-range disorder detected by EXAFS analysis in the shells of atoms more distant from the absorbers is indicative of the defects and inhomogeneous strain present in the MBE-grown films. The evident existence of the SRO in GeSn alloys deposited by different growth methods and in different strain states suggests that SRO is a general phenomenon in the thin films of this metastable solid solution.Item Generative Diffusion Models for Compressed Sensing of Satellite LiDAR Data: Evaluating Image Quality Metrics in Forest Landscape Reconstruction(Remote Sensing, 2025-03-29) Ramirez-Jaime, Andres; Arce, Gonzalo R.; Porras-Diaz, Nestor; Ieremeiev, Oleg; Rubel, Andrii; Lukin, Vladimir; Kopytek, Mateusz; Lech, Piotr; Fastowicz, Jarosław; Okarma, KrzysztofSpaceborne LiDAR systems are crucial for Earth observation but face hardware constraints, thus limiting resolution and data processing. We propose integrating compressed sensing and diffusion generative models to reconstruct high-resolution satellite LiDAR data within the Hyperheight Data Cube (HHDC) framework. Using a randomized illumination pattern in the imaging model, we achieve efficient sampling and compression, reducing the onboard computational load and optimizing data transmission. Diffusion models then reconstruct detailed HHDCs from sparse samples on Earth. To ensure reliability despite lossy compression, we analyze distortion metrics for derived products like Digital Terrain and Canopy Height Models and evaluate the 3D reconstruction accuracy in waveform space. We identify image quality assessment metrics—ADD_GSIM, DSS, HaarPSI, PSIM, SSIM4, CVSSI, MCSD, and MDSI—that strongly correlate with subjective quality in reconstructed forest landscapes. This work advances high-resolution Earth observation by combining efficient data handling with insights into LiDAR imaging fidelity.Item A Machine Learning Model for Post-Concussion Musculoskeletal Injury Risk in Collegiate Athletes(Sports Medicine, 2025-03-27) Claros, Claudio C.; Anderson, Melissa N.; Qian, Wei; Brockmeier, Austin J.; Buckley, Thomas A.Background Emerging evidence indicates an elevated risk of post-concussion musculoskeletal injuries in collegiate athletes; however, identifying athletes at highest risk remains to be elucidated. Objective The purpose of this study was to model post-concussion musculoskeletal injury risk in collegiate athletes by integrating a comprehensive set of variables by machine learning. Methods A risk model was developed and tested on a dataset of 194 athletes (155 in the training set and 39 in the test set) with 135 variables entered into the analysis, which included participant’s heath and athletic history, concussion injury and recovery-specific criteria, and outcomes from a diverse array of concussion assessments. The machine learning approach involved transforming variables by the weight of evidence method, variable selection using L1-penalized logistic regression, model selection via the Akaike Information Criterion, and a final L2-regularized logistic regression fit. Results A model with 48 predictive variables yielded significant predictive performance of subsequent musculoskeletal injury with an area under the curve of 0.82. Top predictors included cognitive, balance, and reaction at baseline and acute timepoints. At a specified false-positive rate of 6.67%, the model achieves a true-positive rate (sensitivity) of 79% and a precision (positive predictive value) of 95% for identifying at-risk athletes via a well-calibrated composite risk score. Conclusions These results support the development of a sensitive and specific injury risk model using standard data combined with a novel methodological approach that may allow clinicians to target high injury risk student athletes. The development and refinement of predictive models, incorporating machine learning and utilizing comprehensive datasets, could lead to improved identification of high-risk athletes and allow for the implementation of targeted injury risk reduction strategies by identifying student athletes most at risk for post-concussion musculoskeletal injury. Key Points - There is a well-established elevated risk of post-concussion subsequent musculoskeletal injury; however, prior efforts have failed to identify risk factors. - This study developed a composite risk score model with an area under the curve of 0.82 from common concussion clinical measures and participant demographics. - By identifying athletes at elevated risk, clinicians may be able to reduce injury risk through targeted injury risk reduction programs.Item Color-Coded Compressive Spectral Imager Based on Focus Transformer Network(Sensors, 2025-03-23) Li, Jinshan; Ma, Xu; Paruchuri, Aanish; Alrushud, Abdullah; Arce, Gonzalo R.Compressive spectral imaging (CSI) methods aim to reconstruct a three-dimensional hyperspectral image (HSI) from a single or a few two-dimensional compressive measurements. Conventional CSIs use separate optical elements to independently modulate the light field in the spatial and spectral domains, thus increasing the system complexity. In addition, real applications of CSIs require advanced reconstruction algorithms. This paper proposes a low-cost color-coded compressive snapshot spectral imaging method to reduce the system complexity and improve the HSI reconstruction performance. The combination of a color-coded aperture and an RGB detector is exploited to achieve higher degrees of freedom in the spatio-spectral modulations, which also renders a low-cost miniaturization scheme to implement the system. In addition, a deep learning method named Focus-based Mask-guided Spectral-wise Transformer (F-MST) network is developed to further improve the reconstruction efficiency and accuracy of HSIs. The simulations and real experiments demonstrate that the proposed F-MST algorithm achieves superior image quality over commonly used iterative reconstruction algorithms and deep learning algorithms.Item Monolithically integrated ultra-wideband photonic receiver on thin film lithium niobate(Communications Engineering, 2025-03-22) Moller de Freitas, Marco; Zhu, Xiaofeng; Ullah, Md Saheed; Shi, Shouyuan; Yao, Peng; Schneider, Garrett; Prather, Dennis W.As the demand for data capacity in wireless networks and mobile communications continues to grow, they are moving toward higher carrier frequencies and wider modulation bandwidths. Unfortunately, electronic device performance degrades in association with increased frequency and modulation bandwidths, which inhibits the application of conventional microwave architectures, particularly in the millimeter wave and terahertz regimes. Alternatively, microwave photonic systems address these challenges by offering device and system performance with exceptionally higher operational bandwidths. The challenge, however, is the ability to monolithically integrate both electronic and photonic devices into functional components that provide ultra-wideband performance up into the millimeter wave and terahertz regions. In particular, such integration remains a major technical challenge due to the high dielectric permittivity of commonly used material platforms for photonic integrated circuits, such as silicon, indium phosphide, and lithium niobate. In this paper, we present a photonic receiver consisting of a broadband antenna and a low-drive-voltage modulator monolithically integrated on thin-film lithium niobate with a quartz handle. A free-space data link is demonstrated, achieving data rates up to 2.7 Gbps using quadrature amplitude modulation, with error vector magnitude as low as 3%. This work demonstrates the potential of thin-film lithium niobate for high-frequency, monolithically integrated radiofrequency and photonic devices to enable ultra-wideband millimeter wave-to-terahertz communication systems.Item A tool to measure maize root system stiffness that enables a comprehensive understanding of plant mechanics and lodging(Journal of Experimental Botany, 2025-01-24) Hostetler, Ashley N.; Reneau, Jonathan W.; Cristiano, Joseph; Weldekidan, Teclemariam; Kermani, Taran A.; Kim, Therese T.; Sparks, Erin E.Plant mechanical failure, known as lodging, has detrimental impacts on the quality and quantity of maize yields. Failure can occur at stalks (stalk lodging) or at roots (root lodging). While previous research has focused on proxy measures for stalk stiffness, stalk strength, and root strength, there is a need to quantify the root system stiffness, which quantifies the force–displacement relationship. Here, we report a tool to quantify the root system stiffness of maize hybrids grown in different conditions. The results show that maize hybrids with a higher root system stiffness have a greater susceptibility to root lodging. This result is consistent with expected mechanical behavior, since higher root system stiffness values mean that the plant reaches the failure strength at lower displacements compared with a plant with lower root system stiffness. Collectively, this study describes the first tool to measure root system stiffness and enables a comprehensive understanding of the integrated plant mechanics and lodging.Item Folded Sub-1V Vπ Thin Film Lithium Niobate Phase Modulator(IEEE Photonics Technology Letters, 2025-02-20) Zhu, Xiaofeng; Moller de Freitas, Marco; Shi, Shouyuan; Yao, Peng; Wang, Fuquan; Cullen, Christopher J.This work reports a sub-1 volt drive voltage (V π ) folded phase modulator utilizing capacitor-loaded traveling wave electrodes (CLTWEs). The implementation employs a low-loss CLTWE on a quartz (Qz) substrate, facilitating both broadband index matching and minimal RF loss. A series of phase modulators of varying lengths have been fabricated and subjected to experimental characterization. The measured loss for straight CLTWEs is 0.21 dB/(cm ⋅ GHz 1/2 ). The experimentally determined DC V π is 0.52 V for a modulation length of 7.5 cm.Item Capacitive-loaded traveling wave electrodes on thin film lithium niobate for sub-terahertz operation(Optical Materials Express, 2025-02-19) Zhu, Xiaofeng; Moller de Freitas, Marco; Shi, Shouyuan; Xue, Ruidong; Yao, Peng; Prather, Dennis W.This paper presents the experimental demonstration of a capacitive-loaded traveling wave electrode (CLTWE) on a thin-film lithium niobate electro-optic modulator designed for ultra-wideband operation, up to the sub-terahertz region. The parametric structural analysis of the T-rail in the CLTWE and its periodicity were varied to evaluate its high-frequency loss and phase index behavior. Modulator designs having various T-rail periodicities were fabricated with the S-parameters and the optical response of the TFLN modulators was characterized up to 220 GHz. The measured results reveal that the cutoff frequency of the CLTWE strongly depends on the T-rail periodicity. The 20-mm long Mach-Zehnder Modulator (MZM) with 50 µm T-rail periodicity exhibits a half-wave voltage (Vπ) of 1 V with a corresponding 3-dB bandwidth of approximately 125 GHz, and 6-dB bandwidth of 180 GHz.Item A Generalized Adder for Cell Size Homeostasis: Effects on Stochastic Clonal Proliferation(Biophysical Journal, 2025-03-21) Nieto, César; Vargas-García, César Augusto; Singh, AbhyudaiMeasurements of cell size dynamics have revealed phenomenological principles by which individual cells control their size across diverse organisms. One of the emerging paradigms of cell size homeostasis is the adder, where the cell cycle duration is established such that the cell size increase from birth to division is independent of the newborn cell size. We provide a mechanistic formulation of the adder considering that cell size follows any arbitrary non-exponential growth law. Our results show that the main requirement to obtain an adder regardless of the growth law (the time derivative of cell size) is that cell cycle regulators are produced at a rate proportional to the growth law and cell division is triggered when these molecules reach a prescribed threshold level. Among the implications of this generalized adder, we investigate fluctuations in the proliferation of single-cell derived colonies. Considering exponential cell size growth, random fluctuations in clonal size show a transient increase and then eventually decay to zero over time (i.e., clonal populations become asymptotically more similar). In contrast, several forms of non-exponential cell size dynamics (with adder-based cell size control) yield qualitatively different results: clonal size fluctuations monotonically increase over time reaching a non-zero value. These results characterize the interplay between cell size homeostasis at the single-cell level and clonal proliferation at the population level, explaining the broad fluctuations in clonal sizes seen in barcoded human cell lines.Item Priestia megaterium cells are primed for surviving lethal doses of antibiotics and chemical stress(Communications Biology, 2025-02-08) Guha, Manisha; Singh, Abhyudai; Butzin, Nicholas C.Antibiotic resistant infections kill millions worldwide yearly. However, a key factor in recurrent infections is antibiotic persisters. Persisters are not inherently antibiotic-resistant but can withstand antibiotic exposure by entering a non-dividing state. This tolerance often results in prolonged antibiotic usage, increasing the likelihood of developing resistant strains. Here, we show the existence of “primed cells” in the Gram-positive bacterium Priestia megaterium, formerly known as Bacillus megaterium. These cells are pre-adapted to become persisters prior to lethal antibiotic stress. Remarkably, this prepared state is passed down through multiple generations via epigenetic memory, enhancing survival against antibiotics and other chemical stress. Previously, two distinct types of persisters were proposed: Type I and Type II, formed during stationary and log phases, respectively. However, our findings reveal that primed cells contribute to an increase in persisters during transition and stationary phases, with no evidence supporting distinct phenotypes between Type I and Type II persisters.Item The magneto-mechanical coupling of multiphase magnetorheological elastomers(Journal of Physics: Condensed Matter, 2025-01-31) Barron III, Edward J.; Williams, Ella T.; Lazarus, Nathan; Bartlett, Michael D.Magnetorheological elastomers (MREs) are soft magnetic composites that achieve tunable changes in stiffness and damping in the presence of a magnetic field. Rigid particle composite (RC) MREs have been studied for decades for their potential applications to automotive dampers and robotic systems. Recently, magnetic fluid composite (FC) MREs have been developed which utilize magnetic fluids as inclusions to elastomers. An investigation into how inclusion phase affects magneto-mechanical performance may greatly improve MRE design capabilities. Here we experimentally evaluate the impact of solid and liquid magnetic inclusions on MRE properties, construct a simple model that captures the performance of diverse MRE material architectures, and demonstrate the use of the model to create material design maps relating the material structure, zero-field properties, and applied field to the elastic modulus and specific loss. The magneto-mechanical response is evaluated for three material architectures: RC, FC, and hybrid composite MREs that use solid particles, magnetic fluids, and a combination of the two as inclusions respectively. The model is developed through magnetic and mechanical energy principles, which suggests that the phase of the magnetic inclusions impacts the change in energy density during deformation. We show that the magneto-mechanical coupling factor is dependent on the zero-field properties of the composites, which allows for the development of material design maps to inform the fabrication of MREs based on desired properties.Item Creating a Softer RoboSquid: Liquid-Metal-Based Compliant Pumps for Pulsed Jet Propulsion(Advanced Materials Technologies, 2025-02-28) Cortazar, Juan D.; Lazarus, NathanSoft pumps are a crucial element in biology, from our own hearts to actuators driving the motion of many creatures in nature. For example, the squid is one of the fastest and most powerful animals in the ocean despite being almost entirely soft, using controlled jets by compressing an internal chamber to propel itself rapidly through the water. Duplicating this performance in an artificial system has, however, remained challenging. Here, a novel soft electromagnetic pump based on using coils of room temperature LM (liquid metal) to drive a permanent magnet piston is demonstrated and used to propel a squid-inspired vehicle. Liquid gallium alloys in silicone tubing are used to manufacture a stretchable electromagnet which is then integrated into a silicone bubble and used to actuate an attached permanent magnet. The robosquid here was able to achieve as high as 4.53 cm s−1 (0.65 body lengths/s) and 9.52 cm s−1 (1.38 body lengths/s) average and peak speed respectively, competitive with current squid inspired vehicles integrating rigid motors and actuators. This result is a major milestone in creating high performance pumps for soft robotics, and will enable superior performance of future soft underwater vehicles leveraging biological principles.Item Single-Step Fabrication of a 3D Stretchable Inductor with Multi-jet Modeling Printing Technology(Advanced Materials Technologies, 2025-01-23) Ahn, Jung-Bin; Yoo, Byungseok; Pines, Darryll J.; Lazarus, Nathan; Bowen, David; Kim, SoaramThe development of flexible and stretchable electronic devices is crucial for advanced electronics, which necessitate inductors with stable performance under deformation. This work presents the fabrication of stretchable polymeric matrices for 3D inductors through a single-step method via additive manufacturing. A multi-jet modeling (MJM) type 3D printer is used to print a stretchable and rigid hybrid matrix by leveraging the features of high-resolution and multi-component printing techniques. Owing to the presence of access channels designed in multiple directions, the coil channel shows a clean and smooth surface with uniformity. A room-temperature liquid metal, the eutectic gallium indium (EGaIn) alloy, is encapsulated in the designated channels without any leakage under mechanical deformation. Electrical performance tests demonstrate that the MJM-printed solenoid and toroid inductors maintain stable performance under bending and stretching deformations, which is suitable for soft electronic applications. Additionally, a flexible helical structured inductor is fabricated and tested as a wireless power receiver inductor. It generated an output voltage of more than 10 V, sufficient to power a red LED light bulb. These results highlight the simplicity and effectiveness of multi-jet 3D printing for fabricating a stretchable and rigid hybrid matrix for the inductors at once, with excellent mechanical deformability and electrical performance.Item Robust Precoder Design for Massive MIMO High-Speed Railway Communications with Matrix Manifold Optimization(IEEE Transactions on Wireless Communications, 2025-02-21) Sun, Rui; Sun, Chen; Shi, Ding; Lu, An-An; Gao, Xiqi; Xia, Xiang-GenIn high-speed railway (HSR) communications, the channel suffers from severe Doppler and channel aging effects caused by the high mobility, making the channel outdated quickly. To address this issue, we investigate the robust precoder design against channel aging and prediction inaccuracy in massive multiple-input multiple-output (MIMO) systems with matrix manifold optimization. First of all, we introduce the concept of the quadruple beams (QBs), and establish a QB based channel model with sampled quadruple steering vectors. Then, the upcoming space domain channel of interest can achieve a higher accuracy by channel prediction with the estimated QB domain channel. To further improve the performance while save the pilot overhead, we predict the forthcoming QB domain channel and integrate the prediction inaccuracy within the a posterior QB domain statistical channel model. Then, we consider the robust precoder design aiming to maximize the upper bound of the ergodic weighted sum-rate (WSR) on the Riemannian submanifold formed by the precoders satisfying the total power constraint (TPC). Riemannian ingredients are derived for matrix manifold optimization, with which the Riemannian conjugate gradient (RCG) method is proposed to solve the unconstrained problem on the manifold. The RCG method mainly involves the matrix multiplication and avoids the need of matrix inversion of the transmit antenna dimension. The simulation results demonstrate the effectiveness of the proposed channel model and the superiority of the RCG method for robust precoder design against channel aging and prediction inaccuracy.Item A Novel ISAR Imaging Algorithm for a Maneuvering Target Based on Generalized Second-Order Time-Scaled Transform(IEEE Transactions on Geoscience and Remote Sensing, 2025-02-11) Ma, Jingtao; Wang, Jiannan; Xia, Xiang-Gen; Huang, Haihong Tao Penghui; Liao, GuishengIt is well-known that for a maneuvering target, its ISAR imaging quality may significantly deteriorate by using the classical range-Doppler (RD) algorithm. To address this issue, this paper proposes a novel ISAR imaging algorithm based on the generalized second-order time-scaled transform (GSOTST). In the proposed method, the multicomponent cubic phase signal (CPS) modeling is adopted for the radar echo signal after translational motion compensation (TMC) in order to portray the phase change characteristics more accurately. First, the target signal is transformed into the slow-time-delay-time domain using a correlation kernel function (CKF). Subsequently, the non-stationary phase is eliminated in the slow-time-generalized delay-time frequency domain, and the GSOTST is utilized to decouple the temporal variables. Finally, the generalized Fourier transform is performed to transform the signal into the 2-D frequency domain, where the energy of the target signal is integrated into a well-focused 2-D peak, enabling the high-precision target parameter estimation as well as finely focused ISAR imaging. The experimental results from both simulation and real-measured data validate the effectiveness of the proposed algorithm.