Optimal design of sparse mimo arrays for wideband near-field imaging based on a statistical framework

Download

index.pdf

Date

2018

Author

Kocamış, Mehmet Burak

Metadata

Show full item record

Item Usage Stats

355
views

109
downloads

Wideband near-field imaging is an emerging remote sensing technique in various applications such as airport security, surveillance, medical diagnosis, and through-wall imaging. Recently, there has been increasing interest in using sparse multiple-input-multiple-output (MIMO) arrays to achieve high resolution with reduced hardware complexity and cost. In this thesis, based on a statistical framework, an optimal design method is presented for two-dimensional MIMO arrays in wideband near-field imaging. Different optimality criteria are defined based on the image reconstruction quality obtained with the final design. An algorithm called clustered sequential backward selection is used to perform the optimization of the chosen criterion over all initial locations of antenna elements. The developed framework also allows incorporating different practical considerations into the design such as synthetic apertures and antenna patterns. The performance of the approach is illustrated for a microwave imaging application. The designs obtained for different observation settings are compared with some commonly used sparse array configurations in terms of image reconstruction quality. Numerical simulation results suggest that the approach can yield designs that outperform conventional sparse array configurations in terms of image reconstruction quality for a wide range of SNR.

Subject Keywords

Near-field communication., Ultra-wideband antennas., Imaging systems., Remote sensing., MIMO systems.

URI

http://etd.lib.metu.edu.tr/upload/12622055/index.pdf
https://hdl.handle.net/11511/27260

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Optimal Design of Sparse MIMO Arrays for Near-Field Ultrawideband Imaging Kocamis, M. Burak; Öktem, Sevinç Figen (2017-09-02) Near-field ultrawideband imaging is a promising remote sensing technique in various applications such as airport security, surveillance, medical diagnosis, and through-wall imaging. Recently, there has been increasing interest in using sparse multiple-input-multiple-output (MIMO) arrays to reduce hardware complexity and cost. In this paper, based on a Bayesian estimation framework, an optimal design method is presented for two-dimensional MIMO arrays in ultrawideband imaging. The optimality criterion is def...
Performance evaluation of similarity measures for dense multimodal stereovision Yaman, Mustafa; Kalkan, Sinan (SPIE-Intl Soc Optical Eng, 2016-05-01) Multimodal imaging systems have recently been drawing attention in fields such as medical imaging, remote sensing, and video surveillance systems. In such systems, estimating depth has become possible due to the promising progress of multimodal matching techniques. We perform a systematic performance evaluation of similarity measures frequently used in the literature for dense multimodal stereovision. The evaluated measures include mutual information (MI), sum of squared distances, normalized cross-correlat...
Deep learning-based reconstruction methods for near-field MIMO radar imaging Manisalı, İrfan; Öktem, Sevinç Figen; Department of Electrical and Electronics Engineering (2022-6-29) Near-field multiple-input multiple-output (MIMO) radar imaging systems are of interest in diverse fields such as medicine, through-wall imaging, airport security, and surveillance. These computational imaging systems reconstruct the three-dimensional scene reflectivity distribution from the radar data. Hence their imaging performance largely depends on the image reconstruction method. The analytical reconstruction methods suffer from either low image quality or high computational cost. In fact, sparsity-bas...
Absorbance Estimation and Gas Emissions Detection in Hyperspectral Imagery Başkurt, Nur Didem; Gur, Yusuf; Omruuzun, Fatih; Çetin, Yasemin (2016-05-19) Hyperspectral imaging in gas detection applications is a leading and widely studied research topic thanks to its high spectral resolution and remote detection ability. The main problems in these applications covers the leakage detection, gas identification, and quantification. The proposed algorithm aims to reach the transmittance and absorbance features of the gas and to detect the gaseous region by using the measured radiance data from the hyperspectral infrared sensors.
Çok Genişbantlı Mikrodalga Görüntüleme için Optimal MIMO Dizilimi Kocamis, Burak; Öktem, Sevinç Figen (2017-05-18) Wideband microwave imaging systems are recently used in various applications including airport security, surveillance, through-wall imaging and medicine. For the operation of such high-resolution systems, sparse multiple-input-multiple output (MIMO) arrays are of interest to reduce the hardware complexity and cost of conventional planar arrays. In this paper, we present a method for the optimal design of two-dimensional MIMO arrays in near-field imaging. Using a statistical framework, the optimality criteri...

Citation Formats

M. B. Kocamış, “Optimal design of sparse mimo arrays for wideband near-field imaging based on a statistical framework,” M.S. - Master of Science, Middle East Technical University, 2018.