SPS Distinguished Lecture: Advances in Localization and Tracking for Internet of Things

The Signal Processing Society (SPS) Schenectady Chapter and Control System Society Schenectady Chapter are the honored to host a SPS Distinguished Lecture in a virtual/webinar format.

SPS Distinguished Lecturer: Xiao-Ping (Steven) Zhang, PhD, MBA, P.Eng., FIEEE, FEIC, FCAE

Professor, Ryerson University, Canada

Abstract: With the emerging deployment of 5G wireless systems and the rapid growing number of smart sensors and deploying sensors on or around physical objects, the Internet of Things (IoT) seamlessly integrates a world of networked smart objects, makes their information be shared on a global scale, and provides an ability of intelligent computing and information processing, such as reporting status, position, and surrounding condition of each sensor node. Localization and tracking is a key problem, which has been studied in various fields, including sonar, radar, seismic, mobile communications, wireless sensor networks. Typical metrics are measured at the local sensors including sample covariance matrices (SCM), time of arrival (TOA), gain ratios of arrival (GROA), angles of arrival (AOA) and frequency differences of arrival (FDOA). Estimating the source position as accurate as possible by utilizing the above-mentioned metrics is full of challenges. In this talk, we introduce the fundamentals, elements, basic localization principles and measurement models, and typical source localization and target tracking methods. We discuss state-of-the-art advances and applications with examples in passive source localization, including subband information fusion, localization penalized maximum likelihood, and performance bounds using AOA-GROA-TOA, and other state-of-the-arts in localization and tracking systems for IoT applications.

Speaker(s): Professor Xiao-Ping Zhang, PhD, MBA, P.Eng., FIEEE, FEIC, FCAE,

Virtual: https://events.vtools.ieee.org/m/269994