Leveraging Bandwidth-Rich Wireless Signals for Passive Localization of RF-Silent Mobile Objects

Project: Research project

Project Details

Description

Many wireless communication signals, WiFi, cellular, radio/TV, and satellites, can be utilized to provide passive radio frequency (RF) sensing services as by-products, including object and event detection, localization, healthcare monitoring, etc. Passive RF sensing is capable of locating non-cooperative device-free objects, which are usually harder to locate than cooperative objects equipped with an active RF device (e.g., a mobile phone). However, most prior passive solutions are non-coherent processing based, using signal strength or channel state information. Non-coherent methods suffer poor resolution, small coverage, and fluctuating performance due to their intrinsic physical limitations. They are ineffective in exploiting the larger bandwidth (BW) of newer wireless signals. Aimed to surpass the limitations of state-of-the-art non-coherent methods, this project will develop coherent high-resolution techniques to locate passive RF-silent mobile objects in complex indoor and outdoor multipath environments, by harnessing bandwidth-rich wireless signals such as 5G/6G cellular, WiFi-6/7, among others. Passive RF sensing, which obviates the need for dedicated transmitters, is environmentally green. It is nonintrusive and economical, requiring no additional investment in infrastructure. Research outcomes of this project can potentially be integrated with existing wireless networks, enabling service providers to offer both wireless communication and RF sensing services to their customers. Therefore, the potential economic and societal impact of the proposed research can be substantial. On the educational front, this project will offer opportunities for training undergraduate and graduate students, summer research programs targeting local high school students, and engagement of the PI to work with women, minorities, and students from under-represented groups.The objective of this project is to develop a coherent processing based framework for robust high-resolution localization and mapping of multiple targets in multipath environments. It comprises three research thrusts. Thrust A is focused on the development of passive localization and mapping techniques by employing RF emissions from multiple wireless base stations (BSs), which form a multi-static sensing geometry and provide multi-perspectives of the surveillance area. One task is to develop a direct mapping approach, which yields targets' location and velocity estimates directly from the observed signals, thus bypassing a combinatorial data association step involved in conventional indirect methods. Other research tasks include the development of multipath-resistant localization methods, by capitalizing on spatial and geometric diversity inherent in the multi-static sensing system, and a multi-rate fast/slow-time sampling approach, which enables decoupled location and velocity estimation to reduce the complexity. While Thrust A mainly considers centralized methods that have access to all BSs' measurements, Thrust B extends the effort and develops distributed privacy-preserving localization and mapping algorithms for the proposed multi-static passive sensing system. The purpose is to seek robustness, computational efficiency, and privacy. The latter arises as the multi-static system involves different BSs serving different communication users with potentially private data. The proposed algorithms run in parallel at each BS, which shares intermediate computing results instead of raw data to preserve data privacy, and incur minimum communication overhead through novel graph partitioning techniques. Thrust C is devoted to a software-defined-radio (SDR) based testbed for experimental data collection and testing, as well as evaluation of data cleaning methods for clutter and direct-path interference removal.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
StatusActive
Effective start/end date1/09/2231/08/25

Funding

  • National Science Foundation

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