IEEE Geoscience and Remote Sensing Magazine - June 2019 - 102

imagers are consolidated into various military and defense
systems and platforms including vehicles, marine vessels,
drones, spacecrafts, missiles, and rockets. Analyzing the scene
using conventional imaging, whether monochrome or color,
depends on the spatial resolution of the image. HSI provides
significant additional information to the spatial dimension by
adding the spectrum to each position. This powerful method creates a "data cube" that contains information about the
physical and chemical properties of a target at tens to hundreds of narrow-wavelength bands within the system's field
of view. The image analyst cross-checks the obtained spectra
with known, uniquely referenced spectral fingerprints to detect, characterize, and identify materials, liquids, or chemical compositions with a precise location.
Because of its high multidimensional data, HSI requires
large data storage capacity, high computation cost, innovative processing techniques, and new analytical skills. These
limitations are why, prior to the 1980s, there were few industrial and military applications using HSI. However, in
the past two decades, advances in third-generation intrinsic
detectors, cryogenic cooling, computing technology, and
cost-effective fabrication techniques, as well as large investments mainly by the United States and the European Defence Agency (EDA), resulted in the transformation of HSI
from a bench-top scientific curiosity to a discipline with
operational and fielded demonstration systems. These advances have enabled the creation of HSI detectors in the
short-wave infrared (SWIR) (1-2.5 µm) to LWIR (7.5-14-µm)
wavelengths, compact systems, miniature optics, and
leading-edge machine-learning algorithms. These detectors enlarge the operability of the HSI and demonstrate the
delivery of timely, accurate, and responsive intelligence information for decision-making during crises and wartime.
The North Atlantic Treaty Organization (NATO) [1], [2], the
EDA [2], and the U.S. Department of Defense [4] identified
six promising and well-developed military applications of
hyperspectral technologies:
◗ gathering information about the battlefield
◗ discrimination between targets and decoys
◗ defeating camouflage
◗ early warning for long-range missiles and space surveillance
◗ detection of weapons of mass destruction (WMDs)
◗ detection of landmines.
This article reviews the main features of HSI technology
and outlines its utility for the six selected defense and security applications. In the literature, readers may find several
other reviews of HSI that address similar application fields.
Some of the reviews are not updated [4]-[9], others cover
the hyperspectral scanning modes and the pros and cons
of the technology [1], [10], [11], while others focus on the
processing models [10]. This article summarizes current
military applications of hyperspectral technologies and
discusses the phenomenology behind these applications.
Examples are provided in the context of military scenarios
that use HSI data collected during several measurement
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campaigns under NATO and EDA frameworks and research
conducted within the hyperspectral unit of the Belgian
Royal Military Academy. The advantages and limitations
of current spectral imaging technology are discussed, and
near-future technological perspectives are outlined.
GATHERING INFORMATION ABOUT
THE BATTLEFIELD
Imagery, along with geospatial and 3D products, is an increasingly critical element in the planning and decisionmaking efforts of commanders and military staffs at all
echelons [12]. Imagery intelligence (IMINT) refers to imagery-related information obtained by processing, exploiting,
analyzing, and fusing the image with other intelligence information. IMINT provides concrete, detailed, and precise
information on the location and physical characteristics of
both the threat and the environment. It aids commanders
and planners through strategic and tactical supports. Strategic support provides situational awareness for the terrain
including key terrain features, installations, and infrastructures, both natural and man-made, for preparation of the
battlefield through various studies such as landcover, land
use, and points of interest like helicopter landing zones,
airfields, bridges, ports, or airfields. HSI advances strategic knowledge by providing information about the physical and chemical properties of features in the scene [14]. In
other words, it allows detailed information to be gathered
about the covered materials that support transportability or
location of forces.
An example of this type of detailed IMINT landcover
map is shown in Figure 1. Imaging data sets, combining
very-high-resolution (VHR) hyperspectral, side-looking
visible, and 3D laser, were generated during the Detection
in Urban scenario using Combined Airborne imaging Sensors (DUCAS) campaign. DUCAS is an EDA project that
investigates the potential benefit of combining high spatial
and spectral resolution airborne imagery for defense applications in urban areas [15]. The urban scene was scanned
using an HSI sensor with 130 bands in the 0.4- to 1-µm
wavelength and with a spatial resolution of 0.4 cm, a VHR
visible with a spatial resolution of 0.05 cm, and a lidar
point density of 100 points/m2. Figure 1 shows how combining diverse information acquired from different sensors increases the information content and quality of the
extracted information. It provides detailed 3D landcover
mapping, horizontal and vertical texture information, and
access areas (such as doors and windows).
IMINT tactical support includes reconnaissance and battlefield surveillance. During reconnaissance missions, information about the activities and resources of an enemy or
potential enemy are collected. Battlefield surveillance is the
systematic observation of the battle area to provide timely
information and combat intelligence. The primary difference
between reconnaissance and surveillance is that reconnaissance is normally "single look," while surveillance denotes
continuous/multitemporal observation [12].
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

JUNE 2019

IEEE Geoscience and Remote Sensing Magazine - June 2019

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