NC-BSI 2.3: Smart Border Systems for Localization and Tracking Problem Statement/Objectives Develop methods which will allow accurately, robustly and ubiquitously determine the position, speed (velocity) and motion history of vehicles, persons and objects approaching and departing borders. Methodology -Our overall approach consists of the following three steps: First, we will identify the required performance for localization and tracking in border security applications. Second, we will identify candidate methods for sensing. Third, we will develop the algorithms and systems to integrate the various sensor for tracking and localization. Benefits to DHS Localization and tracking of cargo/assets, are enabling technologies for smart borders. This will allow commercial border operations efficient and secure. Being able to track each and every item from its point of origin, across the border and to its final destination can enhance safety and streamline inspection procedures at borders. Deliverables and Timelines Year 1: (Q1) Quantify the performance required by localization and tracking systems for various border security operations. (Q2) Identify candidate sensing methods. (Q3 & Q4) Develop a computational framework for integrating the various sensors that will be used in localization and tracking. Year 2: Develop vehicle localization & tracking methods Year 3: Develop freight localization & tracking methods. Year 4: Develop personnel navigation/localization systems. Year 5: Conceptual design of an integrated localization & tracking system for smart borders. Year 6: An integrated test of a tracking and localization system for a smart border. 1

UMN Twin Cities Campus GPS Coverage

NC-BSI 2.3: Smart Border Systems for Localization and Tracking Elevator speech The ability to determine the position history of cargo, assets and vehicles accurately from point of departure to destination is an enabling technology for efficient and secure commercial borders. For example, it can allow identifying cargo that has potentially been tampered with since it left its source of origin. It can also be used to monitor and control (in real-time) cargo flow at busy harbors and ports of entry. Ongoing/leveraged research Using GPS Reflections for Proximity Sensing (AFOSR) Personnel Navigation Systems (Honeywell International) Networked GNSS navigation (Lockheed Martin) Open source Guidance Navigation and Control Sensor Suite for Small UAVs (Lockheed Martin) Costs and Special Equipment Total project cost for the first year is $ 137.2K. For the remainder of the years it is $150 K$ per year. The only special equipment purchase is a GNSS signal simulator. Otherwise, the remainder of equipment purchased will be small electronic sensors and microprocessors/computers. Investigators Demoz Gebre-Egziabher (Associate Professor, Aerospace Engineering & Mechanics) Thomas Posbergh (Associate Professor, Electrical Engineering) Yohannes Ketema (Associate Professor, Aerospace Engineering & Mechanics) Dr. Craig Shankwitz (Research Staff, Intelligent Transportation Systems Laboratory) Two graduate research assistants 3