Department of Electrical & Computer Engineering
Signal and Image Laboratory (SaIL)
The University of Arizona®
|
|
Past Research |
Automatic Target Recognition Using Millimeter-Wave Radar
Images
Student: Mary L. Cassabaum
|
A challenging problem in digital signal and image processing is that of
automatic target recognition (ATR) and object classification. In defense
operations in particular, rapid object discrimination is critical. While
this problem has been studied extensively, it remains a challenge due to
the complex and time-intensive methods of typical approaches. This study
involved constructing features from the range profile signal returns,
identifying the "best" set of features and performing ATR.
MMW radar returns for two different target classes:
Maturation of millimeter wave (MMW) radar technology has led to the
potential for exploitation of range profile signatures in the detection and
identification of targets from the surrounding background. This potential
is realizable due to the MMW wavelengths and the corresponding high range
resolution obtainable at these frequencies. An additional benefit is the
capability of MMW energy at key frequency bands to penetrate rain, dust,
fog and smoke and provide an associated narrow radar beamwidth pattern.
The narrow radar beamwidth results in improved cross-range resolution with
the accompanying increase in the signal-to-clutter ratio (SCR). This
increase in SCR is a significant benefit to detection/identification of
targets due to the inherent suppression of terrain-induced clutter present
in air-to-ground scenarios. The SCR may be further improved by
utilizing doppler beam sharpening (DBS). DBS refers to a technique that
improves the cross-range resolution through a "poor-man's SAR," and
provides the capability to increase
cross-range resolution beyond that nominally available with the traditional
real beam (RB) techniques. Additionally, DBS permits the exploration of
image-based techniques for feature extraction and pattern recognition.
Whether using RB or DBS, the approach under investigation relies on the
development and selection of salient features that are constructed from the
range profiles derived from radar target signatures. Feature selection
involves developing a suite of statistics (in the broad sense) that
summarize and maximize the discriminatory information of the original
signals. If the set of features is "sufficient," the set provides all the
necessary information content of the original signal. It is the goal of
feature extraction to select a set of statistics that provide "sufficiency"
for discriminating between the target classes of interest; these are not
necessarily the same statistics required for target signal characterization.
In this investigation, the targets of interest were characterized
using fully polarimetric radar returns. A target radar cross-section (RCS)
is commonly described by the scattering matrix. The scattering matrix is
usually represented by a circular or linear orthogonal basis.
Collecting the full polarimetric signal allows the investigator to exploit
all the information relating to target RCS. The advantages of extracting
the polarimetric nature of a particular target RCS for detection and
identification have been previously documented. This investigation derived
several features that require full polarimetric returns.
This study considered the extraction and selection of features from
MMW radar returns, providing the information necessary
for automated target
class identification from RB and DBS signals of scenes.
Publications:
-
Mary L. Cassabaum, Donald E. Waagen, Jeffrey J. Rodriguez,
and Harry A. Schmitt, "Unsupervised
Optimization of Support Vector Machine Parameters," in Automatic
Target Recognition XIV, Ivan Kadar, ed., Proc. of SPIE, vol. 5426(1),
SPIE Defense \& Security Symposium, Orlando, FL, April 13-15, 2004,
pp. 316-325. [ PDF ]
-
Mary L. Cassabaum, Jeffrey J. Rodriguez, Jack G. Riddle,
and Donald E. Waagen,
"Feature Analysis Using Millimeter-Wave Real Beam and Doppler Beam
Sharpening Techniques," in Proc. 2002 IEEE Southwest Symp. on
Image Analysis and Interpretation, Santa Fe, NM, April 7-9, 2002, pp.
101-105.[ PDF ]
|
|
1230 E. Speedway Blvd., P.O. Box 210104, Tucson, AZ 85721-0104
|
©2014 All Rights Reserved. |
Contact webmaster
|
|
|
|
|