Information and Resource Management (INFORM) For Accurate Tracking of Resident Space Objects
Dear IEEE members and guests,
The next IEEE Control, Aerospace and Electronic Systems (CAES) seminar will be on Friday, 22nd November, 2022 at 5:30 pm (Adelaide time).
The speaker is Prof Puneet Singla, he will be presenting a seminar on:
Information and Resource Management (INFORM) For Accurate Tracking of Resident Space Objects
Space situation awareness (SSA), including space surveillance and characterization of all space objects and environments, is critical for national and economic security. SSA is the ability to detect, track and characterize passive and active space objects. In light of the large number of Resident Space Objects (RSOs), and the generally accepted notion that our knowledge about the number and nature of most of the objects is severely limited, an unmet and urgent need exists for accurate tracking and characterization of RSOs. A common example involves assigning probabilities of collision of between two different RSOs. For RSO tracking, the core information needed is the orbit parameters and their associated uncertainties specified at a given epoch. This allows for accurate forward prediction but owing to both the nonlinearity of the orbital dynamics and measurement sparsity, the uncertainty associated with RSOs orbit increases in time. Given the fact that none of the prior accidental collision between tracked objects was observed in real time as they occurred, underscores the need for SSA.
This talk will focus on recent development of mathematical and computational approaches for accurate tracking of RSOs within the geostationary (GEO) regime as well as beyond GEO (XGEO). The crux of the work lies in accounting for uncertainties in orbit and sensor models, characterizing the evolution of the uncertainty of the RSO position, and integrating disparate sources of sensor data with the model output using a Bayesian framework. The probability density function associated with state uncertainty is utilized to compute effective information metrics that reflect the information gain associated with ground-based observation platforms. These data driven metrics can be used to pose an optimization problem that provides an optimal sensor schedule to yield useful observations of high valued targets in space. To accommodate the increasing number of sensors and manage the computational challenges associated with the model data fusion process, it is necessary to develop a computational engine that gracefully scales with the resolution of the desired solution. By accurately characterizing the uncertainty associated with both process and measurement models, this work offers systematic design of low-complexity model-data fusion or filtering algorithms with significant improvement in nominal performance and computational effort. Results from studies corresponding to tracking RSOs, where traditional methods either fail or perform very poorly, are considered to assess the reliability and limitations of the newly established methods.
Finally, some results corresponding to application of this framework to other aerospace applications such as reachability analysis for air mobility and surveillance of an area of interest with autonomous agents such as Unmanned Air Vehicles (UAVs) equipped with various sensors will be discussed.
Date and Time
Location
Hosts
Registration
- Date: 22 Nov 2024
- Time: 05:30 PM to 06:30 PM
- All times are (UTC+10:30) Adelaide
-
Add Event to Calendar
- The University of Adelaide
- Adelaide, South Australia
- Australia 5000
- Building: Engineering North
- Room Number: N132
- Click here for Map
Speakers
Puneet Singla of Pennsylvania State University
Biography:
Prof. Puneet Singla is a Harry and Arlene Schell Professor of Engineering in the department of Aerospace Engineering at the Pennsylvania State University. He received his bachelor’s degree in Aerospace Engineering from the Indian Institute of Technology, Kanpur, India in 2000 and earned his doctoral degree in Aerospace Engineering from Texas A&M University, College Station in 2006. He was a faculty member of Mechanical & Aerospace Engineering at the University at Buffalo (UB) from 2006-2017. His research work involves fundamental development of new mathematical and computational approaches for uncertainty propagation through nonlinear dynamical systems, integrating sensing with numerical models, dynamic sensing, optimal control and developing models from sensor data. The interplay between dynamic system analysis, estimation and control lay the scientific groundwork for the development of a data driven framework for diverse problems of varying scales such as tracking resident space objects, trajectory planning for hypersonic vehicles, accurate prediction of toxic material plumes through the atmosphere or water, tumor motion modeling, and control of robotic systems. He is a recipient of the competitive NSF CAREER and the AFOSR Young Investigator awards for his research work. He is also the recipient of the young outstanding aerospace engineer award from Texas A&M University. He has authored over 200 papers to-date including 50 peer-reviewed journals articles. He is the principal author of a text- book entitled “Multi-Resolution Methods for Modeling and Control of Dynamical Systems,” (300 pages) published in August 2008 by CRC Press (Boca Raton, FL). He has received the best paper awards at the 2006 AIAA/AAS Astrodynamics Specialists Conference, 2009 International Information Fusion Conference and 2020 Dynamic Data Driven Application Systems Conference for his research work. His work in attitude estimation included algorithms supporting a successful experiment StarNav that flew on the STS-107. His work on uncertainty propagation was used to compute a probabilistic spatial-temporal estimate of ash presence during the April 2010 eruption of the Eyjafjallajökull volcano in Iceland. He is currently a deputy director of United States Space Force (USSF) funded multi-university SURI program titled Space Object Understanding and Reconnaissance of Complex Events (SOURCE). He is serving as an Associate Editor for AIAA Journal of Guidance, Control and Dynamics (since 2017) and IEEE Transactions on Aerospace and Electronic Systems (since 2015). He has also served as a guest editor for the special issue of the ASME Journal for Dynamic Systems, Measurement, and Control to commemorate the life, achievements, and impact of Rudolph E. Kalman. He has also conducted workshop on new advances in uncertainty quantification at AFRL-RV and national conferences to disseminate his research work to research practitioner.
He is a fellow of American Astronautical Society (AAS), an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).