1
INTRODUCTION
Passive source localization by an array of sensors has been
widely used in sonar, radar, sensor networks and
microphone array[1]etc. Particularly, the context of
far-field sources has been widely investigated in the
literature[2]. Recently, some near-field source localization
methods have been developed[3-6]. However, these
algorithms are very sensitive to sensors’ errors, such as
position, orientation, gain and phase errors. The ability of
an array to measure bearing and range of incident source is
seriously affected by uncertainty concerning array shape
and orientation.
Although many near-field source localization methods
have been proposed, studies about the optimal performance
associated with this model are few. Moreover, less paper
works on the estimated performance under non-ideal gain
and phase response. The Cramér–Rao bound (CRB) is the
most popular tool to characterize the performance of an
estimator in terms of mean square error (MSE)[7]. Some
studies about the CRB of signal parameters have been
developed[8][9]. In [8], it derived the Cramer-Rao bound
(CRB) on DoA/RSS estimation based on sector-powers
and studied its asymptotic behavior and moreover, it
derived an analytical expression for the mean square error
(MSE) of a practical sectorized- antenna-based DoA
estimator. [9] investigated the influence of mutual coupling
to the CRB of DOA in the case of spatially coloured noise.
In [10] non-matrix closed-form expressions of the CRB in
the case of a single deterministic and stochastic
time-varying narrowband source in the near-field region
are derived and analyzed. On the basis of [10], this paper
This work is supported by National Natural Science Foundation of
China under Grant 61401174 and 61372064, Foundation for
Distinguished Young Talents in Higher Education of Guangdong,
China(2015KQNCX154), Scientific Research Plan of Huizhou under
Grant 2015B010002010.
investigates the optimal performance of multiple near field
sources location with non-ideal gain and phase response.
The CRB under the special case of single source is derived
and then we extend it to more general case of multiple
sources. The CRB of multiple-sources scenario can be
recursively calculated based on the single-source CRB
expressions. The CRB expressions of multiple-sources
scenario are in closed-form and only involve matrix
multiplications. Computationally costly matrix operation,
such as matrix inverse, can be avoided. Through CRB
analysis we obtain the characterization of the number of
near field sources relative degradation on bearing and
range accuracy. It enables us to deduce the influence of the
number of near field sources to performance of any
unbiased estimator. In this paper we derive the recurrence
relations for the CRB of multiple incident sources. From
the expression of recurrence relations it can be seen that
CRB increases with the increase in the number of incident
sources.
2
ARRAY SIGNAL MODEL
Suppose that K near-field, narrowband sources, impinge on
the uniform linear array (ULA) of M sensors with element
spacing d. When the uniform linear array is subject to a
priori unknown non-idealities in gain or phase, the signal
received by the array can be expressed as[5]:
( )= ( , ) ( )+ ( ) 1ttttN
ω
≤≤X īASN
(1)
2
2
1, , ,
M
jj
M
diag g e g e
φφ
=ī !
(2)
where
()
ϕω
,A
is an M
h
K array manifold matrix and
the (mth,kth) element is
()
2
)1()1( −+−
=
mmj
mk
kk
ea
ϕω
. In
addition,
k
ω
and
k
ϕ
are the so-called 2-dimensional
(2D) electric angles, which are connected to the physical
parameters
k
θ
and
k
r
by
()
kkk
d
λθπω
sin2−=
and
()( )
kkkk
rd
λθπϕ
22
cos=
for
Kk ≤≤1
. Set the first
Cramér-Rao Bounds for Multiple Near Field Sources Location under Unknown
Gain /Phase Response
Han Cui
1
, Wenjuan Peng
1
, Tong Liu
1
, Xiaohui Wei
1
1. Department of Electronic Science, Huizhou University, Huizhou 516007
E-mail: cuihan2010@qq.com
Abstract: In this paper the Cramer-Rao bound (CRB) for the estimation of nearfield source location under unknown
gain/phase responses is analyzed. We first derive the CRB under the special case of single source and then extend to
more general case of multiple sources. For single-source scenario we show that the CRB can be segmented into two
parts, which separately corresponds to gain responses and phase responses. For multiple-sources scenario, we show that
the CRB can be recursively calculated based on the single-source CRB expressions. The CRB expressions of
multiple-sources scenario are in closed-form and only involve matrix multiplications. We show that with the increase in
the number of incident sources, CRB increases.
Key Words: Bearing and range estimation, gain/phase response, Cramlr-Rao bound, performance analysis.
5169
978-1-5090-4657-7/17/$31.00
c
2017 IEEE