arXiv subjects

Mohammad Roueinfar

Publications and source records attributed to Mohammad Roueinfar.

5 recordsLinked to original sources

arXiv2026

Multi-Target ISAR Imaging of UAV Swarms Using Fast Reweighted Atomic Norm Denoising

Inverse Synthetic Aperture Radar (ISAR) imaging of UAV swarms presents significant challenges due to the coherent superposition of backscattered signals from multiple closely spaced targets. This work explores the extension of the Fast Reweighted Atomic Norm Denoising (FRAND) algorithm to this multi-target scenario. We develop a comprehensive mathematical framework that reformulates the atomic norm minimization problem for swarm imaging, incorporating weighted regularization and efficient optimization via the TwoDimensional Alternating Direction Method of Multipliers (2DADMM). The proposed method handles both sparse aperture conditions and additive white Gaussian noise while maintaining computational efficiency. We simulate an ISAR system receiving composite echoes from UAV swarms, each modeled with distinct scattering centers. The results demonstrate that FRAND effectively disentangles the mixed signals and generates high-resolution range-Doppler profiles for individual UAVs, outperforming traditional methods like Multiple Signal Classification (MUSIC) and Cadzow in low Signal-to-Noise Ratio (SNR) conditions. Quantitative evaluation using MeanSquare Error (MSE) criteria confirms the superiority of the proposed approach. This study establishes the strong potential of atomic norm minimization for complex multi-target radar imaging applications.

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arXiv2026

Non-Line-of-Sight imaging using raster scanning at NIR wavelength

Non-line-of-sight (NLOS) imaging is an emerging technique with transformative potential, enabling the visualization of hidden objects through indirect light reflection. This paper presents a NLOS imaging method operating in the near-infrared (NIR) wavelengths, specifically employing a raster scanning technique with a pan-tilt device. The NIR laser, operating at a wavelength of 808 nm and an output power of 500 mW, illuminates a hidden target occluded by an obstacle. The imaging process involves three bounces: the laser beam first strikes a relay wall, then reflects off the hidden target, returns to the relay wall, and subsequently reaches the NIR camera. This study systematically evaluates the effectiveness of the proposed method across three distinct targets, demonstrating the capability to recover high-quality images from non-line-of-sight scenarios. The obtained images of the hidden targets are compared with their ground truth images, and the error in the obtained images is assessed based on the criteria of Mean Squared Error (MSE) and Root Mean Square Error (RMSE).

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arXiv2025

In-Orbit Cosmo-SkyMed antenna pattern estimation by a narrowband sweeper receiver

This paper introduces a novel method for antenna pattern estimation in satellites equipped with Synthetic Aperture Radar (SAR), utilizing a Narrowband Sweeper Receiver (NSR). By accurately measuring power across individual frequencies within SAR's inherently broadband spectrum, the NSR significantly enhances antenna pattern extraction accuracy. Analytical models and practical experiments conducted using the Cosmo-SkyMed satellite validate the receiver's performance, demonstrating superior signal-to-noise ratio (SNR) compared to conventional receivers. This research represents a key advancement in SAR technology, offering a robust framework for future satellite calibration and verification methodologies.

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arXiv2024

Noise reduction in ISAR imaging of UAVs using weighted atomic norm minimization and 2D-ADMM algorithm

The effect of noise on the Inverse Synthetic Aperture Radar (ISAR) with sparse apertures is a challenging issue for image reconstruction with high resolution at low Signal-to-Noise Ratios (SNRs). It is well-known that the image resolution is affected by the bandwidth of the transmitted signal and the Coherent Processing Interval (CPI) in two dimensions, range and azimuth, respectively. To reduce the noise effect and thus increase the two-dimensional resolution of Unmanned Aerial Vehicles (UAVs) images, we propose the Fast Reweighted Atomic Norm Denoising (FRAND) algorithm by incorporating the weighted atomic norm minimization. To solve the problem, the Two-Dimensional Alternating Direction Method of Multipliers (2D-ADMM) algorithm is developed to speed up the implementation procedure. Assuming sparse apertures for ISAR images of UAVs, we compare the proposed method with the MUltiple SIgnal Classification (MUSIC), Cadzow, and SL0 methods in different SNRs. Simulation results show the superiority of FRAND at low SNRs based on the Mean-Square Error (MSE), Peak Signal-to-Noise ratio (PSNR) and Structural Similarity Index Measure (SSIM) criteria.

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arXiv2022

Two-dimensional gridless super-resolution method for ISAR imaging

We are focused on improving the resolution of images of moving targets in Inverse Synthetic Aperture Radar (ISAR) imaging. This could be achieved by recovering the scattering points of a target that have stronger reflections than other target points, leading to increasing the higher Radar Cross Section (RCS) of a target. These points, however, are sparse and when the received data is incomplete, moving targets would not be properly recognizable in ISAR images. To increase the resolution in ISAR imaging, we propose the 2-Dimensional Reweighted Trace Minimization (2D-RWTM) method to retrieve frequencies of sparse scattering points in both range and cross-range directions. This method is a gridless super-resolution method, which does not depend on fitting the scattering point on the grids, leading to less complexity compared to the other methods. Using computer simulations, the proposed 2D-RWTM is compared to the Atomic Norm Minimization (ANM) in terms of the Mean Squared Errors (MSE). The results show that using the proposed method, the scattering points of a target are successfully recovered. It is shown that by selecting different weighting matrices and scattering points adjacent to each other, the recovery in ISAR imaging is still successful.

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