1744 IEEE SIGNAL PROCESSING LETTERS, VOL. 24, NO. 11, NOVEMBER 2017
Adaptive Detection and Range Estimation of
Point-Like Targets With Symmetric Spectrum
Shefeng Yan, Senior Member, IEEE, Davide Massaro, Danilo Orlando , Senior Member, IEEE,
Chengpeng Hao
, Senior Member, IEEE, and Alfonso Farina, Life Fellow, IEEE
Abstract—In this letter, we address adaptive radar detection of
point-like targets in Gaussian clutter with an unknown covariance
matrix. To this end, we first exploit the symmetrically structured
power spectral density of the clutter to transfer data from the
complex to the real domain. Then, the spillover of target energy is
incorporated into the design criteria to come up with two architec-
tures capable of guaranteeing improved detection performances
and range estimation. The performance assessments, conducted
on both simulated data and real recorded datasets, demonstrate
the effectiveness of the newly proposed detectors compared with
the state-of-the-art counterparts, which ignore either the clutter
spectral symmetry or the energy spillover.
Index Terms—Adaptive radar detection, generalized likelihood
ratio test (GLRT), range estimation, symmetric spectrum.
I. INTRODUCTION
I
N the past decades, adaptive detection of point-like targets
embedded in Gaussian disturbance with an unknown co-
variance matrix has received a vibrant attention from the radar
community [1], [2]. As a consequence, many solutions have
been explored in the open literature, such as Reed, Mallet, and
Brennan detector [3], Kelly’s generalized likelihood ratio test
(GLRT) [4], the adaptive matched filter (AMF) [5], and the
Rao test [6]. All the aforementioned solutions are based on the
assumption that there is no spillover of the target energy to adja-
cent matched filter samples, namely, they suppose that the target
is exactly at the location corresponding to the sample time. In
practice, this assumption is not always met since the physical
spillover phenomenon often happens, as the centroid of the re-
ceived target pulse is somewhere between two consecutive range
bins [7], [8].
A significant loss in signal energy can be caused by the
spillover, which can make all the above detectors poor in per-
formance. In order to compensate for this energy leakage, some
Manuscript received August 7, 2017; revised September 4, 2017; accepted
September 5, 2017. Date of publication September 26, 2017; date of current
version October 13, 2017. This work was supported by the National Natural
Science Foundation of China under Grant 61571434. The associate editor coor-
dinating the review of this manuscript and approving it for publication was Dr.
Samuel Davey. (Corresponding author: Chengpeng Hao.)
S. Yan and C. Hao are with the Institute of Acoustics, Chinese Academy of
Sciences, 100190 Beijing, China (e-mail: sfyan@mail.ioa.ac.cn; haochengp@
mail.ioa.ac.cn).
D. Massaro is with ELETTRONICA S.p.A., 00131 Roma, Italy (e-mail:
davide.massaro@elt.it).
D. Orlando is with Universit
`
a degli Studi “Niccol
`
o Cusano,” 00166 Romam,
Italy (e-mail: danilor78@gmail.com).
A. Farina, retired, was with Selex-ES, 00131 Roma, Italy (e-mail: alfonso.
farina@outlook.it).
Digital Object Identifier 10.1109/LSP.2017.2756076
solutions have been proposed in [9]–[11]. Specifically, in [9], a
space-time spillover model for point-like targets has been de-
fined, and two decision schemes, which exploit the spillover to
provide accurate estimates of the target position within the cell
under test (primary data), have been devised. Such detectors
with the capability of target localization are referred to in the
following as the localization detectors. More recently, in [10],
the oversampling of radar returns has been exploited to further
improve the detection and localization performances, while, in
[11], the polarization diversity and spillover have been jointly
considered at the design stage.
It is worth mentioning that all the aforementioned detectors
have been devised assuming that a set of secondary data, free of
signal components and sharing the same spectral properties of
the primary data (this situation is also known as homogeneous
environment), is available for estimation purposes. However,
real scenarios are often nonhomogeneous due to environmental
factors and system considerations [12]. It is thus of primary
concern to exploit some aprioriinformation to decrease the
sample support required to achieve satisfactory performances
[13]–[21]. An example of such information is the symmetry in
the clutter spectral characteristics, which originates from the
shape of the power spectral density (PSD) and implies that
clutter autocorrelation function is real valued and even [22].
From a practical point of view, this assumption is suitable for
ground clutter observed by a stationary monostatic radar. In fact,
ground clutter often exhibits a symmetric PSD centered around
the zero-Doppler frequency [23]. In [24] and [25], this spectrum
symmetry has been exploited to improve detection performance.
In this letter, we address the problem of adaptive detection
jointly exploiting target spillover and the structure of clutter
PSD. More precisely, we link the model developed in [9] with
the symmetry constraint on the clutter PSD to come up with new
architectures with improved detection and localization perfor-
mances. The numerical examples, obtained by means of simu-
lated and real recorded data, show that the proposed detectors
overcome the counterparts that ignore either the spectrum sym-
metry or energy spillover.
The remainder of this letter is organized as follows. The next
section is devoted to the problem formulation. Section III fo-
cuses on the detector design, while Section IV provides illus-
trative examples. Finally, Section V contains some concluding
remarks and hints for future works.
II. P
ROBLEM FORMULATION
In this section, we first describe the discrete-time model for
the signal and the clutter. The interested readers are referred to
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