Aerospace and Electronic Systems Magazine September 2017 - 50

Focus Before Detection: Part I
ent integration in a long TOT. For these detection methods, target
tracks are also obtained frame by frame or CPI by CPI. Therefore,
track before detection (TBD) [23]-[27] is named for these methods. TBD-based methods make a final target existence decision
with a track via CPI-by-CPI or frame-by-frame target tracking and
have some ability to cope with ARC and ADC effects in a long
TOT. Nevertheless, HT can only deal with a linear motion by projecting an amplitude signal into a polar distance-angle space [38],
[39], without the consideration of high-order motion compensation. Furthermore, the performance of HT in a low signal-to-noise
ratio (SNR) scenario is limited via noncoherent integration. Meanwhile, DP and Bayesian-based methods can be applicable for a
maneuvering target with high-order motion, but their performance
is not satisfactory in a low SNR scenario because of the noncoherent integration. In this article, a new focus-before-detection (FBD)
RSP framework is introduced based on some novel RSP methods
like Radon-Fourier transform (RFT) and generalized Radon-Fourier transform (GRFT) [38], [39]. The proposed FBD methods can
accomplish long-time coherent integration and overcome ARC,
ADC, and even ABW effects by parametric signal modeling and
projecting echoes into a low-dimension parameter space.
In this article, the potential of modern RSP is investigated for
an increasingly challenging environment. Furthermore, three related
main aspects, i.e., accurate environment sensing from echoes, effective resource management for optimization, and advanced RSP
methods, are introduced. The FBD-based methods, as well as their
performance on high-speed and highly maneuvering target detection
and parameter estimation, are discussed in detail. Finally, a novel
FBD-based RSP framework is proposed. The aims of this article are
not only to demonstrate the effectiveness of FBD methods but also
to summarize the challenges for modern radar, to give optimized
solutions, and to show the necessity of advanced RSP methods.

CHALLENGES OF MODERN RADAR FROM A COMPLICATED
WORKING ENVIRONMENT
The modern radar target and detection environment are becoming increasingly challenging [1]-[3]. For down-looking radars
mounted in flying platforms, strong ground or sea clutter is always
a difficult problem for detecting weak slow-moving targets. Furthermore, with the fast development of electronic countermeasure
(ECM) technologies [18], [19], strong active jamming may affect
effective target detection. Apart from the quickly changed background, more high-speed, highly maneuvering, and weak targets,
like aerospace vehicles, satellites, ballistic missiles, and unmanned
aerial vehicles (UAVs), are emerging in air, in space, and on the
ground, which will inevitably cause challenges to target detection,
estimation, and tracking [1]-[3]. The main challenges of target
characteristics, as well as the environment, can be summarized for
modern radar as follows:
C

High speed: The velocities of some ultra-high-speed aerospace vehicles can approach Mach 5-25, which can pass
through a radar beam or range cell in a very short instant.
Therefore, the number of integrated pulses is limited in a
single range-Doppler-beam cell (Figure 1). However, the

scale effect [43] caused by the ultra-high speed of an air or
airspace target may cause significant SNR integration loss.
C

Low radar cross section (RCS): Aircraft, missiles, and
warships with an extremely low RCS have been widely used
in modern battlefields. Compared to conventional radar targets, the detection coverage will be reduced dramatically for
these low observable targets because of the RCS reduction.
Strong maneuver: The accelerations of aerospace vehicles
in near space may approach 2-4 g. Besides, they can use
corkscrew spin, sinusoid motion, large leap, and big-corner
turns to realize orbital transfer and collision avoidance.
These strong maneuverings may inevitably cause difficulties
on target detection, parameter estimation, continuous tracking, and target recognition.
Far range: Space targets of modern radar may move in low
orbit, middle orbit, and geostationary high orbit and even
near space, which implies that target detection should be
accomplished in the far range. Furthermore, more efficient
and effective RSP methods are needed for an extremely lowSNR far-range application.
Strong clutter: There are three typical challenges related
to clutter environment for modern radar. First, for downlooking radars mounted on airborne, airboat, and spaceborne
platforms, strong ground clutter caused by platform motion
[11], [12] is always a difficult problem. Second, strong sea
clutter requires effective clutter-suppressing methods for
weak marine target detection [28], [29]. Third, the time-
space varied ionosphere clutter may shelter radar targets
when they fly through the atmosphere layers.
Jamming: With the quick development of wideband, highpower, and intelligent active jammers [18], [19], strong active and/or passive jamming can affect the radar detection
performance in all dimensions, like time, space, frequency,
and polarization, which causes difficulties for real-time detection, accurate estimation, and effective recognition of a
radar target.

To overcome the above problems, the conventional solutions are
to optimize the radar carrier frequencies, to increase the antenna
transmitting power, to enlarge the antenna aperture, etc. That is, a
radar with a large power aperture product is preferred [1]-[3]. Nevertheless, these methods may cause problems of ECM and even
the radar's survivability, which is also related to the high cost, high
probability of interception, and high vulnerability. Therefore, it is
attractive to ask whether we can improve radar ability in a troublesome environment by changing its RSP without changing system
parameters.

THREE RELATED ASPECTS FOR MODERN RSP
In the last several decades, many effective RSP methods have been
proposed to deal with strong radar clutter and jamming, as well
as weak targets. However, most background-suppressing methods,
e.g., sidelobe cancellation (SLC) [10], [18], [19] in the space do-

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SEPTEMBER 2017

Table of Contents for the Digital Edition of Aerospace and Electronic Systems Magazine September 2017