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Radio Frequency (RF) Sensor Technology Thrust:
Subtask 3.3.11- Data Compression of Geolocation Signals
Project Director: Dr. Bobby L. Wilson, Acting President and Provost, TSU
Faculty Investigator:
Dr. Lei Yu
Sponsoring Agency:
AFRL/UTC-Clarkson Aerospace Minority Leaders Program Sensors
Technical Thrus
Period:
September 1, 2006 ~ August 31, 2007
Research
Abstract:
TSU team plans to investigate the progressive and
non-conventional data compression techniques, and explore
the use for geolocation problem. The specific research tasks
include six (6) parts. (a) Geolocation Signal Acquiring: The
faculty investigators of TSU team will work with project
director (PD) and project supervisor (PS) to request from
relevant sources the sets of necessary geolocation signals
for data compression. The obtained data sets should be
representative and include all typical scenarios and
environments. (b) Geolocation Signal Decomposition: In
order to have better knowledge of the nature and
characteristics of the data, the detailed properties of the
acquired geolocation data will be scanned and analyzed. We
propose to use the novel technique, which is to go through
the wavelet data decomposition process to decompose the
geolocation signal into different levels, and identify the
possible corresponding physical sense if any. Data
decomposition will also help to scan the possible noises and
disturbances during the process of sensing, transmission and
processing. To be reconstructed at all useful levels, the
noises and disturbances will be eliminated naturally. TSU
team will compile a self-developed data decomposition
program in computer language MATLAB with its Wavelet Toolbox
fully used. (c) Novel Methodology Identification: TSU team
will investigate all novel compression techniques from
various types of literatures (academic and conference
papers, research reports, etc.), and identify the most
progressive and non-conventional ones. Based on whether
there is information loss, the investigated data compression
methodologies will be classified into Lossy Compression (LYC)
and Lossless (LLC) Compression. Compression ratios and
suitability will be evaluated. (d) Lossy and Lossless
Compression: In order to investigate the application of all
possible methods, both LYC and LLC will be tested using the
acquired geolocation signals. While the goal is to identify
the best and intelligent methods, the combination of
different compression approaches is a good practice that TSU
has tested when compressing the Intelligent Transportation
System (ITS) data in other Federal level research projects.
(e) Methodology Evaluation: TSU team will systematically
assess all tested methodologies by using a well-defined
evaluation system including but not limited to: Compression
Ratio (CS), Energy Retained (ER), and Distortion Ratio (DR).
The algorithm(s) should be determined that works out the
final decision while all the indices (CS, ER, and DR) cannot
be fully fitted. (f) Extended Compression Practice: TSU
team will then request more geolocation signals for a wider
range of testing practice. The previously identified
methodologies including the evaluation process will be
improved if necessary.
During the entire research process, TSU team will maximize the use
of the computer language MATLAB to compose the program as well as
all its relevant toolboxes such as Wavelet Toolbox, Image Processing
Toolbox, Signal Processing Toolbox, System Identification Toolbox,
etc. The computer programs will be ready to be compiled for real
time and/or on-line uses. Dr. Yu’s lab in the Department of
Transportation Studies (DTS) is not only equipped with all necessary
computer software, but also complemented and supported by two
research units: Urban Traffic and Air Quality Lab (UTAQL) and Center
for Transportation Training and Research (CTTR), which have
conducted advanced research for both federal and state agencies.
UTAQL is a research unit concentrating on urban traffic and air
quality issues including massive transportation and air quality data
compression. CTTR is a member of the Southwest Region University
Transportation Consortium (SWUTC), which is led by Texas A&M
University and also includes the University of Texas at Austin. This
allows TSU to share with necessary resources from the other two
universities (TAMU and UT-Austin). Meanwhile, TSU team members will
work closely in order to seek funding support from federal agencies
(NSF, FHWA, NASA, DoD, etc.) and the Department of Education (Title
III) to expand research capabilities at TSU campus.
Research
Information
For further information about the research, please
contact Dr. Lei Yu by telephone at (713) 313-7282 or by
e-mail at
yu_lx@tsu.edu.
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