Ultra-wideband Impulse-based Radar Signals for Through-the-wall Imaging

Ultra-wideband (UWB) is the promising technology for localization of the objects behind the walls. Recent terrorist activities and law-enforcement situations underscore the need for effective through-wall detection. The approval of UWB technology made by federal communications commission (FCC) in 2002 makes the researchers to have a look on this technology. UWB radar signals has extremely large frequency spectrum and since low frequencies has more penetration capabilities through dielectric materials it is best suitable for through-the-wall radar imaging (TWRI). Signal processing in TWRI has a greater impact in getting the information of the scanned area. This paper uses impulse signals in TWRI, examines the factors impacting in TWRI and obtains the two dimensional information of the scanned scene. Electromagnetic simulation software is used to generate the room like structure, and to obtain the raw radar data.Defence Science Journal, 2012, 62(1), pp.187-192, DOI:http://dx.doi.org/10.14429/dsj.62.84

LFM based Wideband DOA Estimation using Deep Neural Network at Low SNR

This work focuses on deep learning-based wideband direction-of-arrival (DoA) estimation for a wideband in particular LFM in case of extreme noise. We propose a convolutional neural network (CNN) that utilizes the correlation matrix to estimate and trained using multi-channel data in low SNR conditions. By using a systematic approach and treating the problem as a way to identify multiple possible DoAs, the CNN is trained to predict DoAs under different SNR conditions. This allows the CNN to accurately estimate the directions from which signals are coming, regardless of the level of noise in the environment. The architecture proposed exhibits robustness to noise, works effectively with a small number of snapshots, and achieves high resolution in angle estimation. Experimental findings demonstrate notable enhancements in performance under low SNR conditions when compared to existing methods, without the need for parameter tuning for correlated and uncorrelated sources. The enhanced robustness of our solution has broad applications in various fields, including wireless array sensors, acoustic microphones, and sonars

An efficient source localization method in presence of multipath using smart antenna system

In this paper, a MATLAB based smart antenna testbed that efficiently localizes the line-of-sight (LOS) source in the presence of multipath signals is developed. By exploiting the consistent amplitude nature of the LOS signal, a variant of Constant Modulus Algorithm, namely Multitarget-Least Square Constant Modulus Algorithm is employed to adapt and update the weights of the smart antenna for estimation of the direction-of-arrival (DOA) of the of the LOS and multipath interference signals. Performance is compared with the conventional and recently proposed algorithms in the same testbed with alike considerations. Simulation result shows that the proposed method of DOA estimation performs better in terms of probability of resolution and root mean square error

An Efficient Source Localization Method in Presence of Multipath using Smart Antenna System

1069-1073In this paper, a MATLAB based smart antenna testbed that efficiently localizes the line-of-sight (LOS) source in the presence of multipath signals is developed. By exploiting the consistent amplitude nature of the LOS signal, a variant of Constant Modulus Algorithm, namely Multitarget-Least Square Constant Modulus Algorithm is employed to adapt and update the weights of the smart antenna for estimation of the direction-of-arrival (DOA) of the of the LOS and multipath interference signals. Performance is compared with the conventional and recently proposed algorithms in the same testbed with alike considerations. Simulation result shows that the proposed method of DOA estimation performs better in terms of probability of resolution and root mean square error