Research Article
DOA Estimation for Multiple Targets in MIMO Radar with
Nonorthogonal Signals
Zhenxin Cao,
1
Peng Chen ,
1
Zhimin Chen,
2
and Yi Jin
3
1
State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 210096, China
2
School of Electronic and Information Engineering, Shanghai Dianji University, Shanghai 201306, China
3
Xi’an Branch of China Academy of Space Technology, Xi’an 710100, China
Correspondence should be addressed to Peng Chen; chenpengdsp@seu.edu.cn
Received 27 November 2017; Revised 26 June 2018; Accepted 8 July 2018; Published 15 July 2018
Ac
ademic Editor: Raaele Solimene
Copyright © 2018 Zhenxin Cao et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
is paper addresses the direction of arrival (DOA) estimation problem in the colocated multiple-input multiple-output (MIMO)
radar with nonorthogonal signals. e maximum number of targets that can be estimated is theoretically derived as rank{𝑅
𝑠
},
where denotes the number of receiving antennas and 𝑅
𝑠
is the cross-correlation matrix of the transmitted signals. erefore,
with the rank-decient cross-correlation matrix, the maximum number that can be estimated is less than the radar with orthogonal
signals. en, a multiple signal classication- (MUSIC-) based algorithm is given for the nonorthogonal signals. Furthermore, the
DOA estimation performance is also theoretically analyzed by the Carm
´
er-Rao lower bound. Simulation results show that the
nonorthogonality degrades the DOA estimation performance only in the scenario with the rank-decient cross-correlation matrix.
1. Introduction
In the multiple-input multiple-output (MIMO) radar sys-
tem [1–3], the waveform diversity can be used to improve
the target detection and estimation performance [4–8]. In
the existing works, many methods have been proposed to
estimate the target direction of arrival (DOA). For example,
in the colocated MIMO radar system, a reduced-dimension
transformation is used to reduce the complexity in the DOA
estimation based on the estimation of signal parameters
via rotational invariance technique (ESPRIT) [9]; a com-
putationally ecient DOA estimation algorithm is given
for the monostatic MIMO radar based on the covariance
matrix reconstruction in [10]; a joint DOA and direction of
departure (DOD) estimation method based on ESPRIT is
proposed in [11]. Additionally, in the coprime MIMO radar
system, a reduced-dimension multiple signal classication
(MUSIC) algorithm is proposed [12] for both DOA and DOD
estimation; a combined unitary ESPRIT-based algorithm is
given for the DOA estimation [13]. In the bistatic MIMO
radar system, a joint DOD and DOA estimation method is
also proposed in the scenario with an unknown spatially
correlated noise [14].
In the existing papers about the MIMO radar systems,
mostpapersareabouttheorthogonalwaveformstoesti-
mate the DOA, such as the waveforms adopted in [15–20].
However, it is dicult to generate the orthogonal signals in
the practical radar systems, and the number of orthogonal
waveforms is much less than that of nonorthogonal wave-
forms. erefore, the traditional DOA estimation methods
and results with the orthogonal signals must also be modied.
In [21], the nonorthogonal waveforms are rst proposed,
and the method with prewhitening processing is proposed in
[22].However,tothebestofourknowledge,thetheoretical
analysis of the nonorthogonal waveforms in the MIMO radar
systems has not yet been addressed in the papers.
In this paper, the DOA estimation problem for multiple
targets is addressed, and the system model of MIMO radar
with nonorthogonal signals is given. en, the maximum
number of targets that can be estimated is derived accord-
ing to the cross-correlation matrix of transmitted signals,
and a MUSIC algorithm for the nonorthogonal signals is
Hindawi
Mathematical Problems in Engineering
Volume 2018, Article ID 6465856, 7 pages
https://doi.org/10.1155/2018/6465856