Aerospace and Electronic Systems Magazine September 2017 - 52

Focus Before Detection: Part I

Figure 3.

Targets in different detection background. (a) Clear region. (b) Ground clutter region.

where Pt is the transmitting power, Ar is the antenna aperture, σ is
the RCS of the target to be detected, k is Boltzmann's constant, P0
is the system absolute temperature, Fn is the noise factor, SNRmin is
the needed minimum SNR for effective detection, and Pt/Ω is the
coherent integration time for a certain angle coverage Ω. The contributions of power, aperture, and time are directly reflected in (1).
The carrier frequency and polarization may affect the target RCS.
The waveform in Figure 4 means that there are many kinds of
transmitting waveforms in the waveform dictionary for a modern
radar to flexibly obtain a better target detection or background-suppressing performance in a complicated environment. After a radar
is designed, its resources in six domains are given, but they can be
optimized with different modes for different tasks, e.g., detection
in the clear region, detection in ground clutter, and detection in
weather clutter. The concept of cognitive radar [20]-[22] has been
widely discussed in recent years by introducing feedback from environment sensing to radar resource optimization. It offers a substantial increase in agility, particularly at the transmitter, such as
waveform agility in echo-locating mammals. Then, suitable radar
waveform design and related RSP algorithms should be adopted

Figure 4.

Radar resources in different domains.

that exploit the available environmental cognition on the reflectivity characteristic of the environment, weather conditions, the location of EM interferences, and their Doppler bandwidth. That is,
cognitive radar can adapt the T/R pair to the actual operating scenario. The importance of cognition in T/R optimization has been
justified as a way to optimize some relevant radar performance
measures, such as range-Doppler resolution, detection capabilities,
and clutter suppression, while accounting for the coexistence of the
radar with spectrally overlaid systems and signal-dependent interference [10], [18], [19]. Besides, cognitive CFAR strategies can be
considered, in addition to the standard CFAR techniques.

ADVANCED RSP METHODS
The next problem is whether the existing RSP framework, as shown
in Figure 1, can use this auxiliary sensing information and the optimized system resources to improve the performance. To answer this
question, let's take the RSP in the time domain as an example. There
are two problems related to the optimized RSP in this domain: one
is how to obtain long TOT, and the other is how to exploit a large
number of the target's echoes in a long
TOT. For the first problem, it is difficult
to jointly sustain wide coverage and high
data rate, i.e., the rate of the target detection reporting may cause the conventional mechanical scanning radar to allocate
too much time on a certain direction with
a single beam. Fortunately, digital beamforming (DBF) has been widely used for

IEEE A&E SYSTEMS MAGAZINE

SEPTEMBER 2017

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