arXiv subjects

Shahrokh Hamidi

Publications and source records attributed to Shahrokh Hamidi.

11 recordsLinked to original sources

arXiv2024

Modeling and Analysis of Spatial and Temporal Land Clutter Statistics in SAR Imaging Based on MSTAR Data

The statistical analysis of land clutter for Synthetic Aperture Radar (SAR) imaging has become an increasingly important subject for research and investigation. It is also absolutely necessary for designing robust algorithms capable of performing the task of target detection in the background clutter. Any attempt to extract the energy of the desired targets from the land clutter requires complete knowledge of the statistical properties of the background clutter. In this paper, the spatial as well as the temporal characteristics of the land clutter are studied. Since the data for each image has been collected based on a different aspect angle; therefore, the temporal analysis contains variation in the aspect angle. Consequently, the temporal analysis includes the characteristics of the radar cross section with respect to the aspect angle based on which the data has been collected. In order to perform the statistical analysis, several well-known and relevant distributions, namely, Weibull, Log-normal, Gamma, and Rayleigh are considered as prime candidates to model the land clutter. The goodness-of-fit test is based on the Kullback-Leibler (KL) Divergence metric. The detailed analysis presented in this paper demonstrates that the Weibull distribution is a more accurate fit for the temporal-aspect-angle statistical analysis while the Rayleigh distribution models the spatial characteristics of the background clutter with higher accuracy. Finally, based on the aforementioned statistical analyses and by utilizing the Constant False Alarm Rate (CFAR) algorithm, we perform target detection in land clutter. The overall verification of the analysis is performed by exploiting the Moving and Stationary Target Acquisition and Recognition (MSTAR) data-set, which has been collected in spotlight mode at X-band, and the results are presented.

cs.CV↗

arXiv2024

Target Detection in Sea Clutter with Application to Spaceborne SAR Imaging

In this paper, the challenging task of target detection in sea clutter is addressed. We analyze the statistical properties of the signals which have been received from the scene and based on that, we model the amplitude of the signals that have been reflected from the background sea clutter according to several well-known probability distribution functions. Next, by exploiting the Kullback-Leibler (KL) divergence metric as a goodness-of-fit test, we will demonstrate that among the proposed probability distributions, the Weibull distribution can model the statistical properties of the background sea clutter with higher accuracy. Subsequently, we utilize the aforementioned information to design an adaptive threshold based on the Constant False Alarm Rate (CFAR) algorithm to detect the energy of the targets which have been buried in the sea clutter. Thorough analysis of the experimental data gathered from the Canadian RADARSAT-1 satellite demonstrates the overall effectiveness of the proposed method.

eess.SP↗

arXiv2024

Joint Image De-noising and Enhancement for Satellite-Based SAR

The reconstructed images from the Synthetic Aperture Radar (SAR) data suffer from multiplicative noise as well as low contrast level. These two factors impact the quality of the SAR images significantly and prevent any attempt to extract valuable information from the processed data. The necessity for mitigating these effects in the field of SAR imaging is of high importance. Therefore, in this paper, we address the aforementioned issues and propose a technique to handle these shortcomings simultaneously. In fact, we combine the de-noising and contrast enhancement processes into a unified algorithm. The image enhancement is performed based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) technique. The verification of the proposed algorithm is performed by experimental results based on the data that has been collected from the European Space Agency's ERS-2 satellite which operates in strip-map mode.

eess.IV↗

arXiv2024

Millimeter-Wave Circular Synthetic Aperture Radar Imaging

In this paper, we present a high resolution microwave imaging technique using a compact and low cost single channel Frequency Modulated Continuous Wave (FMCW) radar based on Circular Synthetic Aperture Radar (CSAR) technique. We develop an algorithm to reconstruct the image from the raw data and analyse different aspects of the system analytically. Furthermore, we discuss the differences between the proposed systems in the literature and the one presented in this work. Finally, we apply the proposed approach to the experimental data collected from a single channel FMCW radar operating at $\rm 79 \;GHz$ and present the results.

eess.SP↗

arXiv2024

High Resolution Millimeter Wave Imaging Based on FMCW Radar Systems at W-Band

In this paper, we present a unique $\text {2D}$ high resolution, compact, low-cost, lightweight, and highly accurate millimeter wave imagery system capable of operating in all weather conditions. We describe millimeter wave imaging process in detail and present several novel signal processing methods with their applications. To create the array, we utilize the Synthetic Aperture Radar (SAR) concept. The imagery system presented in this paper, can strongly compete with Lidar systems as the resolution limit is at the same level. Furthermore, in contrast to the Lidar systems, our imagery system can operate in heavy rain and dense fog and produce high quality images. Finally, we utilize our wide-band custom-made Frequency Modulated Continuous Wave (FMCW) radar, which operates at W-band with $\text {33 GHz}$ bandwidth, for data collection and present the results.

eess.SP↗

arXiv2024

3D Near-Field Virtual MIMO-SAR Imaging Using FMCW Radar Systems at 77 GHz

In this paper, we present 3D high resolution radar imaging at millimeter-Wave (mmWave) frequencies by means of a combination of virtual Multiple Input Multiple Output (MIMO) Frequency Modulated Continuous Wave (FMCW) Radars and Synthetic Aperture Radar (SAR) which results in a compact, low-cost, and high-speed 3D mmWave imagery system with low complexity.

eess.SP↗

arXiv2024

CDM Based Virtual FMCW MIMO Radar Imaging at 79GHz

Multiple Input Multiple Output (MIMO) Frequency Modulated Continuous Wave (FMCW) radars operating at 79GHz are compact, light and cost effective devices with low peak-to-average power ratio that have applications in different areas such as automotive industry and Unmanned Arial Vehicle (UAV) based radar imaging. In order to keep the structure small and simple, these radars come with small number of transmitters and receivers. The number of elements can be virtually increased using techniques such as Time Division Multiplexing (TDM), Frequency Division Multiplexing (FDM) or Code Division Multiplexing (CDM) and as a result higher angular resolution can be achieved. Both TDM and FDM based virtual FMCW MIMO radar imaging process have been reported in literature. However, to the best of our knowledge CDM based virtual FMCW MIMO radar has not received any attention. In this paper we will be using an 79GHz FMCW MIMO radar and apply the idea of the CDM method to increase the number of elements virtually which in turn enhances the angular resolution.

eess.SP↗

arXiv2021

Single Channel MMWave FMCW Radar for 2D Target Localization

In this paper, we present a 2D target localization method using two low cost and compact Mellimeter Wave Frequency Modulated Continuous Wave (MMW-FMCW) radars. To create a 2D map we exploit the bilateration method followed by a multi-target tracking block to remove the ghost targets. Finally, we present experimental results based on the data gathered from two FMCW radars operating at $\rm 79 \;GHz$.

eess.SP↗

arXiv2021

3D Near-Field Millimeter-Wave Synthetic Aperture Radar Imaging

In this paper, we present 3D high resolution radar imaging process at millimeter-Wave (mmWave) frequencies by creating the effect of a large aperture synthetically. We use a low cost fully integrated Frequency Modulated Continuous Wave (FMCW) radar operating at $\rm 79\;GHz$ and then perform Synthetic Aperture Radar (SAR) imaging in the near-filed zone. At the end, we conduct a real experiment and present the reconstructed image.

eess.SP↗

arXiv2020

Entropy-Based Doppler Centroid Estimation and Speckle Noise Reduction for Spaceborne SAR Imaging

In this paper, we present strip-map mode spaceborne Synthetic Aperture Radar (SAR) imaging with the focus on Doppler centroid frequency estimation. The non-zero Doppler centroid frequency is the result of non-zero squint angle which if it is not compensated it can de-focus the image. We present an efficient method based on the entropy of the reconstructed image to estimate the fractional part of the Doppler centroid frequency. Furthermore, we discuss the speckle noise, which degrades the quality of the reconstructed images considerably, and attempt to alleviate its effect efficiently. Following the implementation of the speckle noise reduction algorithm, a significant improvement in the quality of the reconstructed images is achieved. Finally, we utilize the experimental data gathered from the RADARSAT-1 satellite of Vancouver Canada to verify the accuracy and effectiveness of the proposed techniques.

eess.SP↗

arXiv2020

Sparse Based Super Resolution Multilayer Ultrasonic Array Imaging

In this paper, we model the signal propagation effect in ultrasonic imaging using Huygens principle and use this model to develop sparse signal representation based imaging techniques for a two-layer object immersed in water. Relying on the fact that the image of interest is sparse, we cast such an array based imaging problem as a sparse signal recovery problem and develop two types of imaging methods, one method uses only one transducer to illuminate the region of interest {and for this case the system is modeled as a single input multiple output (SIMO) system. The second method relies on all transducers to transmit ultrasonic waves into the material under test and in this case the system is modeled as a multiple input multiple output (MIMO) system}. We further extend our work to a scenario where the propagation velocity of the wave in the object under test is not known precisely. {We discuss different techniques such as greedy based algorithms as well as $\ell_1$-norm minimization based approach to solve the proposed sparse signal representation based method. We give an assessment of the computational complexity of the $\ell_1$-norm minimization based approach for the SIMO and the MIMO cases. We further point out the superiority of the $\ell_1$-norm minimization based approach over the greedy based algorithms. Then we give a comprehensive analysis of error for both the greedy based approaches as well as the $\ell_1$-norm minimization based technique for both the SIMO and the MIMO cases. The analysis utilizes tools from two powerful branches of modern analysis, \emph{local analysis in Banach spaces} and \emph{concentration of measure}}. We finally apply our methods to experimental data gathered from a solid test sample immersed in water and show that sparse signal recovery based techniques outperform the conventional methods available in the literature.

eess.SP↗