IEEE - Aerospace and Electronic Systems - May 2022 - Tutorial XV - 92

IEEE AES Tutorials
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 research area are
identified. These issues include not only improving efficiency,
but also increased concerns regarding the cost and
complexity ofpower supplying systems.
FUNDAMENTALS OF ENERGY-CONSTRAINED SENSOR
NETWORK SYSTEMS
BRIAN M. SADLER, Senior Member, IEEE
U.S. Army Research Laboratory
This article is an overview of energy-constrained sensor
networks, focusing on energy-conserving communications
and signal processing strategies. We assume batterydriven
nodes, employing robust communications, with little
or no fixed infrastructure. Our discussion includes
architectures, communications connectivity, capacity and
scalability, mobility, network localization and synchronization,
distributed signal processing, and cross-layer
issues. Because energy is a precious system resource, all
aspects of the network must be designed with energy savings
in mind. In particular, transmissions and idle listening
must be minimized, which implies the use of duty cycling
to the maximum extent possible. When external assets are
available, for tasks such as network synchronization and
node geolocation, these can greatly relieve the energy burden
and significantly enhance network lifetime.
PROBABILISTIC DATA ASSOCIATION TECHNIQUES FOR
TARGET TRACKING WITH APPLICATIONS TO SONAR, RADAR
AND EO SENSORS
Y. BAR-SHALOM, Fellow, IEEE
University of Connecticut
T. KIRUBARAJAN, Member, IEEE
McMaster University
Canada
X. LIN
University of Connecticut
We present an overview of the probabilistic data association
(PDA) technique and its application for different target
tracking scenarios, in particular for low observable (LO)
(low SNR) targets. A summary of the PDA technique is
presented. The use of the PDA technique for tracking low
observable targets with passive sonar measurements is presented.
This " target motion analysis " is an application of
the PDA technique, in conjunction with the maximum likelihood
(ML) approach, for target motion parameter estimation
via a batch procedure. The use of the PDA technique
for tracking highly maneuvering targets combined radar
resource management is described. This illustrates the
application of the PDA technique for recursive state
92
estimation using the interacting multiple model (IMM)
estimator with probabilistic data association filter (PDAF)
(IMMP- DAF). Then we present a flexible (expanding and
contracting) sliding-window parameter estimator using the
PDA approach for tracking the state of a maneuvering target
using measurements from an electro-optical (EO) sensor.
This, while still a batch procedure, has the flexibility of
varying the batches depending on the estimation results in
order to make the estimation robust to target maneuvers as
well as target appearance or disappearance.
NONLINEAR FILTERS: BEYOND THE KALMAN FILTER
FRED DAUM, Member, IEEE
Raytheon
Nonlinear filters can provide estimation accuracy that is
vastly superior to extended Kalman filters for some important
practical applications. We compare several types of
nonlinear filters, including: particle filters (PFs), unscented
Kalman filters, extended Kalman filters, batch filters and
exact recursive filters. The key practical issue in nonlinear
filtering is computational complexity, which is often called
" the curse ofdimensionality. " It has been asserted that PFs
avoid the curse of dimensionality, designed PFs with good
proposal densities sometimes avoid the curse ofdimensionality,
but not otherwise. Future research in nonlinear filtering
will exploit recent progress in quasi-Monte Carlo
algorithms (rather than boring old Monte Carlo methods),
as well as ideas borrowed from physics (e.g., dimensional
interpolation) and new mesh-free adjoint methods for solving
PDEs. This tutorial was written for normal engineers,
who do not have nonlinear filters for breakfast.
MULTIBASELINE CROSS-TRACK SAR INTERFEROMETRY:
A SIGNAL PROCESSING PERSPECTIVE
FULVIO GINI, Senior Member, IEEE
FABRIZIO LOMBARDINI, Senior Member, IEEE
University of Pisa
Italy
Synthetic aperture radar interferometry (InSAR) is a powerful
and increasingly expanding technique for measuringthe
topography ofa surface, its changes over both shortand
long-time scale, and other changes in the detailed characteristicsof
the surface. We provide a tutorial description
ofrecent results ofthe research activity at the University of
Pisa on multibaseline (MB) InSAR processing. The main
focus is on the problem ofretrieving both heights and radar
reflectivities of natural layover areas by means of a crosstrack
InSAR (XTI-SAR) system with a uniform linear array
(ULA). It is formulated as the problem of detecting and
estimating a multi-component signal corrupted by multiplicative
noise-the speckle in the radar imagingjargon-and by
additive white Gaussian noise. Application to the InSAR
problem of both nonparametric and parametric modern
IEEE A&E SYSTEMS MAGAZINE
MAY 2022
IEEE - Aerospace and Electronic Systems - May 2022 - Tutorial XV

Table of Contents for the Digital Edition of IEEE - Aerospace and Electronic Systems - May 2022 - Tutorial XV
