Indoor localization

Signal Processing and Optimization Techniques for High Accuracy Indoor Localization, Tracking, and Attitude Determination

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B1 L3 R3119

High-accuracy indoor localization and tracking systems are essential for many modern applications and technologies. However, accurate location estimation of moving targets is challenging. This thesis addresses the challenges in indoor localization and tracking systems and proposes several solutions. A novel signal design, which we named Differential Zadoff-Chu, allows us to develop algorithms that accurately estimate the distances of static and moving targets even under random Doppler shifts. The results show that the proposed algorithms outperform the state-of-the-art in terms of both accuracy and complexity.

Sameh Sorour

Postdoctoral Research Fellow (former), Communication Theory Lab
Postdoctoral Research Fellow at King Abdullah University of Science and Technology (KAUST),Assistant Professor at King Fahd University of Petroleum and Minerals (KFUPM) since September 2013.

Safwan .H Ibrahim

Consultant-Technical Lead at KAUST (King Abdullah University of Science and Technology).

Reema Alnafisi

M.S. student, advised by Professor Tareq Al-Naffouri under the Information System Lab (ISL). at King Abdullah University of Science and Technology (KAUST)

Hui Chen

Ph.D. Student (former), Electrical and Computer Engineering
Ph.D. degree Electrical and Computer Engineering, King Abdullah University of Science and Technology (KAUST) ,Currently a Ph.D. student working on localization & tracking and gesture recognition.