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Graduate Exam Abstract


Lucas Krakow

Ph.D. Preliminary
May 2, 2018, 9:00 am - 10:30 am
Engineering C101B (ECE Conference Room)
Spanning Sensor Resource Management

Abstract: This paper presents multiple applications of sensor resource management. The general focus entails two chapters on adaptive estimation of time-varying sparse signals and three chapters exploring autonomous control of unmanned aerial vehicles (UAVs) sensor platforms employed for target tracking. All of the included applications are posed as decision control problems formulated in the rigorous framework of a partially observable Markov decision process (POMDP) and solution methods based on Bellman's equation are exercised, generating adaptive control policies for action selections in the given scenarios. Specifically, the rollout optimization method is administered in the cases of signal estimation under the objective of maximizing the information gain about the unknown sparse signal. For the UAV sensor platform control, nominal belief-state optimization (NBO) is employed for control selection for optimizing objectives including target-tracking error, surveillance performance and fuel efficiency. The empirical studies in each investigation present evidence that non-myopic solution methods, accounting for both the immediate and future costs of the current action choices, provide performance gains for these scenarios.

Adviser: Edwin Chong
Co-Adviser: N/A
Non-ECE Member: Patrick Burns
Member 3: Ali Pezeshki
Addional Members: Jie Luo

Publications:
Journal Papers:
[1] Y. Li, L. W. Krakow, E. K. P. Chong, and K. N. Groom, "Approximate stochastic dynamic programming for sensor scheduling to track multiple targets," Digital Signal Processing, vol. 19, no. 6 pp. 978--989, December 2009

[2] R. Zahedi, L. Krakow, A. Pezeshki, and E. K. P. Chong, "Adaptive estimation of time-varying sparse signals," IEEE Access, vol. 1, pp. 449--464, July 2013.

Conference Paper:
[1] Y. Li, L. W. Krakow, E. K. P. Chong, and K. N. Groom, "Dynamic sensor management for multisensor multitarget tracking," Proceedings of the 40th Annual Conference on Information Sciences and Systems, Princeton, New Jersey, March 22--24, 2006 (Invited paper), pp. 1397--1402.

[2] L. W. Krakow, E. K. P. Chong, K. N. Groom, J. Harrington, Y. Li, and B. Rigdon, "Control of perimeter surveillance wireless sensor networks via partially observable Marcov decision process," in Proceedings of the 2006 40th Annual IEEE International Carnahan Conference on Security Technology (ICCST), Lexington, Kentucky, October 17--20, 2006, pp. 261--268.

[3] Y. Li, L. W. Krakow, E. K. P. Chong, and K. N. Groom, "Approximate stochastic dynamic programming for sensor scheduling to track multiple targets," in Proceedings of the 2006 Workshop on Defense Applications of Signal Processing (DASP'06), The Kingfisher Bay Resort, Fraser Island, Queensland, Australia, December 10--14, 2006 (Invited paper).

[4] R. Zahedi, L. W. Krakow, E. K. P. Chong, and A. Pezeshki, "Adaptive compressive sampling using partially observable Markov decision processes," in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012), Kyoto, Japan, March 25--30, 2012, pp. 5265--5272 (Invited Paper).

[5] R. Zahedi, L. W. Krakow, E. K. P. Chong, and A. Pezeshki, "Adaptive compressive measurement design using approximate dynamic programming," in Proceedings of the 2013 American Control Conference, Washington, DC, June 17--19, 2013, pp. 2448--2453

[6] L. W. Krakow, R. Zahedi, E. K. P. Chong, and A. Pezeshki, "Adaptive compressive sensing in the presence of noise and erasure," in Proceedings of the Symposium on Controlled Sensing for Inference: Applications, Theory and Algorithms, part of the 1st IEEE Global Conference on Signal and Information Processing (GlobalSIP 2013) Austin, TX, December 3--5, 2013, pp. 133--136 (Invited paper).

[7] L. W. Krakow, L. Rabiet, Y. Zou, G. Iooss, E. K. P. Chong, and S. Rajopadhye, "Optimizing dynamic resource allocation," in Proceedings of the International Conference on Computational Science (ICCS 2014), Cairns, Australia, June 10--12, 2014, Procedia Computer Science, vol. 29, pp. 1277--1288.

[9] L. W. Krakow and E. K. P. Chong, "Autonomous UAV control: Balancing target tracking and persistent surveillance," Proceedings of the 2017 IEEE Conference on Control Technology and Applications (CCTA), Kohala Coast, Hawai'i, August 27--30, 2017, pp 1524--1529 (Invited paper)

Book Chapters:

[1] Yoon, Y., Gruber, S., Krakow, L., & Pack, D. (2009). Autonomous target detection and localization using cooperative unmanned aerial vehicles. In Optimization and Cooperative Control Strategies (pp. 195-205). Springer, Berlin, Heidelberg.


Submitted:

[1] L. W. Krakow, C. M. Eaton, and E. K. P. Chong, " Simultaneous Non-Myopic Optimization of UAV Navigation and Camera Gimbal Control for Target Tracking," Submitted to 2018 IEEE Conference on Control Technology and Applications (CCTA), Copenhagen, Denmark, August 21--24, 2018, (Invited paper).

[2] C. M. Eaton, L. W. Krakow, E. K. P. Chong, and A. A. Maciejewski, "Fuel Efficient Moving Target Tracking using POMDP with Limited FOV Sensor," Submitted to 2018 IEEE Conference on Control Technology and Applications (CCTA), Copenhagen, Denmark, August 21--24, 2018, (Invited paper).


Program of Study:
M 566
M 617
ECE 512
ECE 514
MATH 618
N/A
N/A
N/A