Aerospace and Electronic Systems Magazine November 2016 Tutorial X - 114

IEEE AES Tutorials
Research in the last two decades has resulted in a tremendous increase in the data capacity of Loran thereby increasing
its utility. Currently, a modernized Loran is being evaluated for
its capability to backup GPS and data modulation is an integral
part of this Loran design. An overview and analysis of Loran
modulation techniques is provided.

TUTORIAL V
Published as Part 2 of IEEE Aerospace & Electronic Systems
Magazine

TEMPLATE-BASED TARGET IDENTIFICATION AND
CONFUSION MATRICES

Volume Twenty-Five Number Seven-July 2010.

KENT HASPERT, Member, IEEE
JAMES HEAGY
ROGER SULLIVAN, Member, IEEE
Institute for Defense Analyses

A TUTORIAL OVERVIEW OF ANOMALY DETECTION IN
HYPERSPECTRAL IMAGES

One-dimensional high-range-resolution (HRR) and two-dimensional range-Doppler-imaging (RDI) radar represent possible sensor technologies where template-based techniques can be applied to
perform combat identification (CID). The majority of the research
reported in these areas consists of empirical studies. This article provides a theoretical basis for understanding some of the fundamental
trade-offs associated with these CID techniques, such as the following.
1) What are the relative advantages of RDI over HRR radar or
of finer versus coarser resolution in the HRR process?
2) What is the relative advantage of coherent over noncoherent
processing?
3) How do target correlations, signal-to-noise ratio (SNR), and
target scintillation affect the ability to identify targets?
Because confusion matrices are often used to characterize the performance of CID systems, we provide analytical
methods for calculating the entries in confusion matrices as
a function of the issues cited above. These formulations provide analytical bases to guide system trade-off decisions. The
organization of this paper is as follows. We begin with a short
overview of HRR and RDI and then explore a number of ways
to process the associated target templates that range from an
ideal, theoretical approach to an approach that would be more
feasible to implement within current-day radars. We first develop analytic template-based methodologies for constructing
confusion matrix entries for nonscintillating targets for both
coherent and noncoherent processing assumptions. The confusion matrix entries in these cases are conditional probabilities
obtained from a simple rule: find the probability that among m
(in general, correlated) random variables, each associated with
a possible target, that any one is the largest. For the noncoherent case, the successful application of this rule requires the
target template values to explicitly include the effects of thermal noise (noise-adjusted templates). We conclude by showing how to calculate theoretically optimum results (e.g., using
maximum likelihood techniques) for noncoherent processing
of targets that exhibit uncorrelated Swerling 1 scintillation in
all resolution bins as a function of the SNR. This approach

114	

allows us to include overall target intensity (e.g., total radar
cross section (RCS)) as a further factor in the target decision
process.

STEFANIA MATTEOLI, Student Member, IEEE
MARCO DIANI, Member, IEEE
GIOVANNI CORSINI, Member, IEEE
University of Pisa
In this paper, a tutorial overview on anomaly detection for hyperspectral electro-optical systems is presented. This tutorial is
focused on those techniques that aim to detect small man-made
anomalies typically found in defense and surveillance applications. Since a variety of methods have been proposed for detecting such targets, this tutorial places emphasis on the techniques
that are either mathematically more tractable or easier to interpret physically. These methods are not only more suitable for a
tutorial publication, but also an essential to a study of anomaly
detection. Previous surveys on this subject have focused mainly
on anomaly detectors developed in a statistical framework and
have been based on well-known background statistical models. However, the most recent research trends seem to move
away from the statistical framework and to focus more on deterministic and geometric concepts. This work also takes into
consideration these latest trends, providing a wide theoretical
review without disregarding practical recommendations about
algorithm implementation. The main open research topics are
addressed as well, the foremost being algorithm optimization,
which is required for embodying anomaly detectors in real-time
systems.

ON BAYESIAN TRACKING AND DATA FUSION: A TUTORIAL
INTRODUCTION WITH EXAMPLES
WOLFGANG KOCH, Senior Member, IEEE
Fraunhofer-FKIE
Germany
This tutorial paper provides a short introduction to selected aspects of sensor data fusion by discussing characteristic examples.
We consider three cases when fusion of sensor data is important:
when emphasis is placed on data produced at different instants
of time (i.e., target tracking), when data being collected from
different sensor sources are important, and when we have data
with background information on the sensor performance as well

IEEE A&E SYSTEMS MAGAZINE	

NOVEMBER 2016, Part II of II



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