Full metadata
Title
Integrated waveform-agile multi-modal track-before-detect algorithms for tracking low observable targets
Description
In this thesis, an integrated waveform-agile multi-modal tracking-beforedetect sensing system is investigated and the performance is evaluated using an experimental platform. The sensing system of adapting asymmetric multi-modal sensing operation platforms using radio frequency (RF) radar and electro-optical (EO) sensors allows for integration of complementary information from different sensors. However, there are many challenges to overcome, including tracking low signal-to-noise ratio (SNR) targets, waveform configurations that can optimize tracking performance and statistically dependent measurements. Address some of these challenges, a particle filter (PF) based recursive waveformagile track-before-detect (TBD) algorithm is developed to avoid information loss caused by conventional detection under low SNR environments. Furthermore, a waveform-agile selection technique is integrated into the PF-TBD to allow for adaptive waveform configurations. The embedded exponential family (EEF) approach is used to approximate distributions of parameters of dependent RF and EO measurements and to further improve target detection rate and tracking performance. The performance of the integrated algorithm is evaluated using real data from three experimental scenarios.
Date Created
2012
Contributors
- Liu, Shubo (Author)
- Papandreou-Suppappola, Antonia (Thesis advisor)
- Duman, Tolga (Committee member)
- Kovvali, Narayan (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
vii, 67 p. : col. ill
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.14953
Statement of Responsibility
by Shubo Liu
Description Source
Viewed on March 22, 2013
Level of coding
full
Note
thesis
Partial requirement for: M.S., Arizona State University, 2012
bibliography
Includes bibliographical references (p. 64-67)
Field of study: Electrical engineering
System Created
- 2012-08-24 06:27:10
System Modified
- 2021-08-30 01:46:25
- 3 years 2 months ago
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