Aerospace and Electronic Systems Magazine July 2017 Tutorial XI - 63

DOI No. 10.1109/MAES.2017.173231

Abstracts of Previous Tutorials in this Series
TUTORIAL I
Published as Part 2 of IEEE Aerospace & Electronic Systems
Magazine
Volume Nineteen-Number One-January 2004

MULTIPLE HYPOTHESIS TRACKING FOR MULTIPLE TARGET
TRACKING
SAMUEL S. BLACKMAN
Raytheon Co., Segundo, CA
Multiple hypothesis tracking (MHT) is generally accepted as the
preferred method for solving the data association problem in modern multiple target tracking (MTT) systems. This paper summarizes the motivations for MHT, the basic principles behind MHT and
the alternative implementations in common use. It discusses the
manner in which the multiple data association hypotheses formed
by MHT can be combined with multiple filter models, such as used
by the interacting multiple model (IMM) method. An overview of
the studies that show the advantages of MHT over the conventional
single hypothesis approach is given. Important current applications
and areas of future research and development for MHT are discussed.

A STAP OVERVIEW
WILLIAM L. MELVIN, Senior Member, IEEE
GTRI, Smyrna, GA
This tutorial provides a brief overview of space-time adaptive
processing (STAP) for radar applications. We discuss space-time
signal diversity and various forms of the adaptive processor, including reduced-dimension and reduced-rank STAP approaches.
Additionally, we describe the space-time properties of ground
clutter and noise-jamming, as well as essential STAP performance
metrics. We conclude this tutorial with an overview of some current
STAP topics: space-based radar, bistatic STAP, knowledge-aided
STAP, multi-channel synthetic aperture radar and non-sidelooking
array configurations.

CLASS-SPECIFIC CLASSIFIER: AVOIDING THE CURSE OF
DIMENSIONALITY
PAUL M. BAGGENSTOSS, Member, IEEE
Naval Undersea Warfare Center
Newport, RI
This article describes a new probabilistic method called the
"class-specific method" (CSM). CSM has the potential to avoid
the "curse of dimensionality" which plagues most classifiers
JULY 2017, Part II of II

which attempt to determine the decision boundaries in a highdimensional featue space. In contrast, in CSM, it is possible to
build classifiers without a common feature space. Separate lowdimensional features sets may be defined for each class, while
the decision functions are projected back to the common raw data
space. CSM effectively extends the classical classification theory
to handle multiple feature spaces. It is completely general, and
requires no simplifying assumption such as Gaussianity or that
data lies in linear subspaces.

"STATISTICS 101" FOR MULTISENSOR, MULTITARGET DATA
FUSION
RONALD P. S. MAHLER
Lockheed Martin, Eagan, MN
This tutorial summarizes the motivations, concepts, techniques,
and applications of finite-set statistics (FISST), a system-level,
"top-down" direct generalization of ordinary single-sensor, single-target engineering statistics to the multisensor, multitarget
realm. FISST provides powerful new conceptual and computational methods for dealing with multisensor, multitarget, and
multi-evidence data fusion problems. The paper begins with
a broad-brush overview of the basic concepts of FISST. It describes how conventional single-sensor, single-target formal
Bayesian modeling is carefully extended to general data fusion
problems. We examine a simple example: joint detection and
tracking of a possibly non-existent maneuvering target in heavy
clutter. The tutorial concludes with a commentary on certain
criticisms of FISST.

TUTORIAL II
Published as Part 2 of IEEE Aerospace & Electronic Systems
Magazine
Volume Twenty-Number Eight-August 2005

A REVIEW OF DISTRIBUTED POWER SYSTEMS PART I:
DC DISTRIBUTED POWER SYSTEM
SHIGUO LUO
ISSA BATARSEH, Senior Member, IEEE
University of Central Florida
The present development state in dc distributed power systems
(DPS) is comprehensively reviewed in this tutorial. Basic distributed structures and their characteristics are described. The system
level design considerations are discussed. The profile of current
technologies is drawn. Finally, the issues and challenges in this

IEEE A&E SYSTEMS MAGAZINE

Table of Contents for the Digital Edition of Aerospace and Electronic Systems Magazine July 2017 Tutorial XI