Aerospace and Electronic Systems Magazine October 2017 - 24

Feature Article:

DOI. No. 10.1109/MAES.2017.160035

Knowledge-Aided Processing for Multipath Exploitation
Radar (MER)
Louis B. Fertig, J. Michael Baden, Georgia Tech Research Institute, Smyrna, GA, USA
Joseph R. Guerci, Information Systems Laboratories, Inc., San Diego, CA, USA

INTRODUCTION
Truly persistent surveillance of moving vehicles in urban areas
spanning approximately 1,000 km2 is a desirable capability that
does not exist due to the generally non-line-of-sight (non-LOS)
nature of urban terrain. Radar is an attractive sensing modality
for this purpose due to its all-weather day or night operation and
the potential for a high area coverage rate. However, radar is not
achieving the goal of persistent urban surveillance for several reasons. First, urban buildings block LOS between radars mounted on
standoff platforms and large swaths of urban roadways. Overcoming the severe LOS blockage would force the sensors to very high
aspect ratios that in turn would drive the total number of required
platforms to an unacceptably large number. Second, existing airborne radar systems cannot properly function in an urban area due
to the complicated multipath environment. In addition to vehicles
moving in and out of LOS, reflections from buildings introduce
numerous other returns. A classical LOS interpretation of the detections obtained in a multipath environment results in the formation of tracks that typically do not match the number of true objects
in the scene or their positions and velocities. As an example, for
certain geometries, a multipath return from a retreating vehicle can
exhibit a Doppler consistent with a LOS return of an advancing
vehicle.

Authors' current addresses: L. B. Fertig, J. M. Baden, Georgia
Tech Research Institute, SEAL, 7220 Richardson Road, Bldg.
5, Smyrna, GA 30080 USA, E-mail: (louis.fertig@gtri.gatech.
edu). J. R. Guerci, Information Systems Laboratories, Inc., San
Diego, CA, USA.
Approved for public release, distribution unlimited. The
views, opinions, and/or findings expressed are those of the
authors and should not be interpreted as representing the
official views or policies of the Department of Defense or the
U.S. Government. This work was sponsored by the Defense
Advanced Research Projects Agency and supported by the Air
Force Research Laboratory.
Manuscript received February 8, 2016, revised July 27, 2016,
and ready for publication May 3, 2017.
Review handled by D. O'Hagen.
0885/8985/17/$26.00 © 2017 IEEE
24

In the Multipath Exploitation Radar (MER) program initiated
by the Defense Advanced Research Projects Agency (DARPA), it
is recognized that much of the radar energy blocked by buildings
is reflected into the street below. This multipath energy illuminates
the urban environment within the LOS shadows and provides an
opportunity to greatly extend the persistent area coverage of an airborne radar sensor. This additional information encoded in the multipath can only be exploited if knowledge-aided (KA) processing
is employed, such as that developed under the DARPA Knowledge
Aided Sensor Signal Processing and Expert Reasoning program
[1]. Fortunately, sufficient knowledge of urban environments can
be obtained from a variety of sources, such as light detection and
ranging (LIDAR) or radar synthetic aperture radar (SAR) imagery. Automated tools exist to extract three-dimensional city models
from these data. The multipath can be accurately predicted in real
time via the application of ray-tracing techniques implemented on
inexpensive commercial graphics processing units (GPUs). It is
envisioned that current ground moving target indication (GMTI)
radar systems will be upgraded with real-time MER technology
through the insertion of a MER postprocessor into the existing
GMTI signal processing architecture. MER processing could also
function in a postmission forensics mode.
In this article, evidence from the MER program that demonstrates the validity of the relevant concepts is described. First, a
summary is provided of the initial feasibility studies that motivated
the full program. The measurements that were collected during the
MER Phase I effort are then discussed. Next, the algorithms developed during the MER Phase II effort are illustrated. Finally, the
results obtained in the blind data test at the conclusion of Phase II
are presented. It is shown that the new algorithms yielded excellent
tracking performance in a challenging environment.

INITIAL MER FEASIBILITY STUDIES
Although it later became evident that MER offers many advantages relative to traditional radar signal processing approaches, initial
interest in MER was motivated by its capability to significantly
increase the area coverage associated with airborne radar in urban
environments. In other words, MER enables a significant extension of the range coverage that can otherwise be obtained by an

IEEE A&E SYSTEMS MAGAZINE

OCTOBER 2017



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