IEEE Systems, Man and Cybernetics Magazine - July 2019 - 61

seasonal changes, and platform
combining the returns from a numinstabilities. These complications
ber of pings, SAS systems form a
The quality of
make detecting weak objects
virtual receive aperture array that
change detection
even more difficult. Additionally,
can be much larger, and therefore
because of benign clutter [22],
more directional, than the physical
using SAS imagery
false changes or detections conreceive aperture array. In past
is complicated by
tinue to be a n active a rea of
decades, SAS has become a mature
research. Ultimately, there are
technology that is capable of creatseveral factors.
several desirable properties that
ing high-resolution imagery of the
change-detection systems, regardsea floor and targets over ranges of
less of sensor, should possess.
several hundred meters.
These include the ability to effectively characterize the
Active SAS systems provide a powerful imaging techchanges due to manmade and natural activities, reduce
nique that coherently combines echoes from multiple
false-detection rates by rejecting repetitive activipings along the trajectory of a platform to construct a
ties that occur in the environment, and perform the
long virtual array. Applications in SAS are being investiabove operations in real time and in the presence of a
gated actively. Although synthetic aperture concepts
noisy environment.
originated in the radar community in the mid-20th centuTypically, change detection for persistence surveilry [16], it was not until the 1970s that the sonar communilance is applied where the same area is to be repeatedly
ty began to show the feasibility of applying these
monitored, such as surveys for port and harbor security,
concepts for underwater imaging applications [17]. With
deforestation, and glacier monitoring. Automating
evolutionary advances in enabling technologies, SAS
change-detection techniques makes it possible to
systems are now being implemented on a variety of platincrease recognition capabilities and reduce the workforms and over a wide range of commercial and military
load of a human operator tasked with identifying changapplications. Before SAS systems, change detection as
es in the sensor imagery. This article introduces an
applied to side-scan sonar typically relied on manually
image-based end-to-end ACD processing stream that
comparing new and old imagery or an operator or autowas recently developed by the Naval Surface Warfare
mated detector-flagging objects in new sonar imagery,
Center Panama City Division. The ACD-processing
followed with comparing contacts stored in a historical
stream discerns and presents man-made changes in the
database. Both processes proved to be very tedious and
sea floor from multipass SAS imagery [20], [23]. Ultitime consuming. With the advent of SAS systems, which
mately, this will reduce the workload of human operaprovided constant resolution over the swath and were
tors, who would otherwise have to compare multiple
deployed on actively navigated platforms capable of preimages manually.
cise track repetition, the automated comparison of multitemporal sea-bed images was demonstrated in recent
Overview of ACD Process
years [18]-[20].
The ACD process is carried out by comparing reference
The quality of change detection using SAS imagery is
and repeat-pass images that correspond to the same geocomplicated by several factors, including the presence
graphical location, but are collected at different times.
of random speckle patterns in the images [21] and
Automating this task involves five major components: refchanging environmental conditions such as ocean-floor
erence and repeat-pass data retrieval, reference and
sediment moving due to ocean currents, vegetation,

(a)

(b)

(c)

Figure 1. An example of the spot the difference game. (a) The initial pass and (b) a repeat pass represent the

two original images. (c) The ICD change map is the differences between the two images. (Source: [28].)

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IEEE Systems, Man and Cybernetics Magazine - July 2019

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