University of California - Irvine
This project develops a Chip-Scale Personal Navigation System to localize emergency responders, assets, and people indoors and in covered environments, where GPS signals are unusable. UC Irvine is developing Micro-Electro-Mechanical Systems (MEMS) technology within this project and investigating cellular signals (CDMA & LTE), Digital TV, and WiFi, for position determination inside buildings. Cooperative Localization is also being investigated for a team of mobile agents equipped with the uNavChip and communication and computational capabilities. Jointly processing a relative measurement between any two agents could lead to additional increases in localization accuracy. - July 2019
Principal Investigator: Andrei Shkel*
Co-Investigator: Zak Kassas
Co-Investigator: Solmaz Kia
Orange County Fire Authority, public safety partner*
* Team involved in 2021-2022 Demonstration Project
University of California Irvine was awarded a separate, one-year award to complete a demonstration project to further develop their Ultimate Personal-Indoor-Navigator (uPIN) system with Orange County Fire Authority (OCFA) at OCFA’s Regional Fire Operations Training Center and fire stations. Their demonstration project will focus on uPIN’s tracking localization, visualization, and data collection capabilities. System improvements will include adaptable parameter selection of its internal zero-velocity-update (ZUPT) algorithm to accommodate the walking style of a user (such as walking, running, jumping, and crawling) and surface characteristics of terrains (hard floor, grass, sand, etc); and realistic temperature profiles of the operational environment.
The Ultimate Navigation Chip (uNavChip): Chip-Scale Personal Navigation System Integrating Deterministic Localization and Probabilistic Signals of Opportunity project is designed to develop an innovative framework for location-based services to localize emergency responders, assets and equipment, and other people (e.g., patients and trapped persons) indoors and in covered outdoor environments, where GPS signals are unusable. The overall technical objective of this project is to design, build, and demonstrate a Personal Navigation System (PNS) achieving the localization accuracy on the level of 1 m in GPS-denied environment for hours of operation. The technical approach to this project is based on simultaneous integration of Deterministic, Probabilistic, and Cooperative Localization algorithms.
Based on Inertial Navigation augmented by Zero Velocity Updates (ZUPting) algorithms, the team will work to integrate the custom designed MEMS Inertial Measurement Unit (IMU) integrated on the same chip with micromachined ultrasonic transducers (CMUTs). The IMU+CMUT localization unit will be integrated in the sole of shoes, for the most efficient compensation of drift. The IMU will derive the absolute orientation and position, which are regularly re-calibrated by ultrasonic transducers with ZUPting algorithms.
The ultimate vision is to have the IMU and CMUT all fabricated in parallel on both sides of a single silicon substrate and subsequently folded into a cube and locked in place using specially designed microlock mechanisms. The micro-system will be over two orders of magnitude higher in performance (near navigation grade) and smaller in size (on the order of 1 cc) than the current state-of-the-art.
Based on Signals of Opportunity. ZUPting in the Deterministic Localization approach helps contain the error growth, however the uncertainty will still propagate due to errors in determination of the zero velocity updates and residual uncompensated errors due to the pattern of motion. The Probabilistic Localization approach aims to exploit cellular signals of opportunity, which are abundant and usable in GPS challenged environments, turning cell towers into something analogous to terrestrial GPS satellites.
Based on mobile agents, with communication and computation capabilities, jointly processing a relative measurement between each agent to increase their localization accuracy. The team will develop an integrated collaborative positioning framework that will utilize synthetic aperture navigation, aiding an inertial navigation system in an ultra-tightly-coupled fashion with cellular signals