Tarig Ballal Khidir Ahmed

About Tarig Ballal Khidir Ahmed

Tarig Ballal Khidir Ahmed

Research Scientist (former), Electrical and Computer Engineering

image processing acoustic signal detection Digital signal processing low complexity systems Low sampling Ultra-wideband communication UWB channel impulse response estimation. Acoustic sensing and communications Sonars and radars. Movement detection and tracking using RF and acoustic waves. Respiration detection and tracking. Robust estimation and regularization Experimentation and testing.

Research Scientist Laboratory for Nanomedicine, Computational Bioscience Research Center King Abdullah University of Science and Technology | KAUST

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July 2020

ISL Team Nominated for IEEE Walter R. Fried Memorial Award

1 min read · Tue, Jul 28 2020

News

GNSS localization

This year, the ISL team attended the 2020 IEEE/ION Position, Location and Navigation Symposium. A team of Professor Tareq Al-Naffouri, Xing Lui and Tarig Ballal co-authored the Conference Publication titled GNSS Attitude Determination Using a Constrained Wrapped Least Squares Approach. The publication focused on GNSS Attitude Determination. The publication's excellence was recognized as it was shortlisted for the Walter R. Fried Memorial Award. While the publication did not ultimately win the award, the superior technical quality of the work was recognized.

August 2019

SNR Estimation in Linear Systems With Gaussian Matrices

1 min read · Tue, Aug 6 2019

News

SNR estimation Guassian matrices ISL Highlighted Publications

M. A. Suliman and A. M. Alrashdi and T. Ballal and T. Y. Al-Naffouri, "SNR Estimation in Linear Systems With Gaussian Matrices", IEEE Signal Processing Letters. vol. 24 , pp. 1867-1871, Dec 2017. Abstract: This letter proposes a highly accurate algorithm to estimate the signal-to-noise ratio (SNR) for a linear system from a single realization of the received signal. We assume that the linear system has a Gaussian matrix with one sided left correlation. The unknown entries of the signal and the noise are assumed to be independent and identically distributed with zero mean and can be drawn from

July 2019

ISL Students place 4th at Microsoft Indoor Localization Competition 2017

1 min read · Mon, Jul 29 2019

News

Accurate indoor positioning has the potential to transform the way people navigate indoors similar to the way the GPS transformed outdoor navigation. Over the last 20 years, many indoor positioning technologies have been proposed and experimented by both academia and industry. We developed an accurate acoustic 3D positioning system, which consists of one mobile device (MD) and four base stations (BSs) with known locations. The MD transmits a series of ultrasound and RF sequences, named Zadoff-Chu (ZC) sequences, at the same time. The propagation time of the RF signal is negligible compared to