The Global Position System (GPS) has simplified many of our positioning, navigation, and timing (PNT) estimation problems by providing global availability and high accuracy at all times.  In addition, for safety-critical applications, the integrity of GPS can be assured through self-monitoring, overbounding, and several other well-known statistical techniques.  As we move into an environment where GPS may be denied or spoofed, complementary navigation sources (e.g., vision, inertial, doppler, star tracking, etc.) may be used to provide PNT updates.  However, ensuring the integrity of these solutions is a technically challenging problem.  We are interested in studying and developing techniques for providing integrity in an estimation system that is using different types of navigation signals.  GPS may be one of those signals, but broadening the integrity framework of GPS to include other sensors, errors over time, possible (unknown) correlation between sensors, and on-line learning of models for different sensors are of interest.

Citations:

1. Naveen, Aryan, and Clark Taylor. "Decentralized data fusion with probabilistically conservative ellipsoidal intersection." In 2021 American Control Conference (ACC), pp. 1613-1618. IEEE, 2021.

2. Watson, Ryan M., Jason N. Gross, Clark N. Taylor, and Robert C. Leishman. "Robust incremental state estimation through covariance adaptation." IEEE Robotics and Automation Letters 5, no. 2 (2020): 3737-3744.

3. Vanli, O. Arda, and Clark N. Taylor. "Robust error estimation based on factor-graph models for non-line-of-sight localization." EURASIP Journal on Advances in Signal Processing 2022, no. 1 (2022): 3.

key words

GPS-denied Navigation; Assurance; Integrity; correlation-agnostic fusion; signal modeling

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral and Senior applicants