A Novel DOA Estimation Algorithm Using Array  Rotation Technique

Lan, Xiaoyu; Wan, Liangtian; Han, Guangjie; Rodrigues, Joel J. P. C.

doi:10.3390/fi6010155

Cited by 20 publications

(15 citation statements)

References 15 publications

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“…At present, DOA estimation algorithms can be divided into two categories: subspace-based algorithms and parameter estimation algorithms. The first group is based on the decomposition of covariance matrix such as the multiple signal classification (MUSIC) [10] and estimation of signal parameters via rotational invariance techniques (ESPRIT) [11]. The second group includes the deterministic maximum likelihood (DML) and stochastic maximum likelihood (SML) [7] algorithms, which have excellent DOA estimation performance.…”

Section: Introductionmentioning

confidence: 99%

Two Novel DOA Estimation Approaches for Real-Time Assistant Calibration Systems in Future Vehicle Industrial

Han

Wan

Shu

et al. 2017

IEEE Systems Journal

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Intelligent transportation systems (ITSs) of industrial systems have played an important role in Internet of things (IOT). The assistant calibration system (ACS) of vehicles is an emerging technology, which services the driver to drive the vehicle safely. To solve some existing problems in ACS such as frequency pairing, vehicle localization judgment, and driving in the curve road, two direction-of-arrival (DOA) estimation-based approaches are proposed to resolve these problems. However, the performance of most conventional DOA estimation algorithms is affected by the mutual coupling among the elements. The special structure of the mutual coupling matrix of the uniform linear array is applied to eliminate the effect of mutual coupling. Then, a novel on-grid DOA estimation algorithm based on compressive sensing (CS) strategies is proposed in the presence of unknown mutual coupling. In order to compensate the aperture loss of discarding information that the array receives, the array aperture is extended by the vectorization operator. In order to deal with the effect of grid mismatch, an offgrid DOA estimation algorithm based on sparse Bayesian learning (SBL) is proposed in this paper. The temporal correlation between the neighboring snapshot numbers is considered in the off-grid algorithm. The computer simulation verifies the effectiveness of the proposed algorithms.Index Terms-Compressive sensing (CS), direction-of-arrival (DOA) estimation, intelligent transportation systems (ITSs), sparse Bayesian learning (SBL).

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Section: Introductionmentioning

confidence: 99%

Two Novel DOA Estimation Approaches for Real-Time Assistant Calibration Systems in Future Vehicle Industrial

Han

Wan

Shu

et al. 2017

IEEE Systems Journal

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“…Among the two‐dimensional arrays, the uniform circular array (UCA) is usually preferred due to 360° azimuthal coverage, almost unchanged directional pattern and additional elevation angle information. The CRB analyzes in References 8,9 also assume that all incident signals to the UCA are pure FF or pure NF, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…Among the two-dimensional arrays, the uniform circular array (UCA) is usually preferred due to 360 • azimuthal coverage, almost unchanged directional pattern and additional elevation angle information. The CRB analyzes in References 8,9 also assume that all incident signals to the UCA are pure FF or pure NF, respectively. In some practical applications, such as seismic exploration, speaker localization using a microphone array, guidance systems, and electronic supervision, any source can be located in the NF or FF.…”

Section: Introductionmentioning

confidence: 99%

Derivation of multidimensional stochastic Cramer‐Rao bound for mixture of noncoherent and coherent near/far field signals

Molaei

Hoseinzade

2020

Trans Emerging Tel Tech

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The existing Cramer-Rao bound (CRB) expressions in the literature are not applicable to the problem of localization of mixed near-field (NF) and far-field (FF) sources, including noncoherent and coherent signals, using two-dimensional arrays. Given the unique properties of circular arrays, in this article, the mathematical model of received signals in multipath environments, including a mixture of noncoherent and coherent NF/FF signals, is introduced. Then, the stochastic CRBs associated with the above problem are derived. The compact closed-form expression of CRB extracted in this article can be used for the algorithms under the above scenario as a benchmark to evaluate the estimation accuracy of azimuth DOA, elevation DOA, and range parameters as well as fading coefficient parameter. The simulation results show that the CRBs of the azimuth DOAs, elevation DOAs, ranges, and FCs decrease, on average, at a rate of approximately O(M −1.9 ), O(M −1.9 ), O(M −1.2 ), and O(M −1.8 ) as M (number of sensors) goes to infinity, respectively, where O is the notation of the asymptotic growth rate.

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“…In contrast, a moving array, that is, an array whose element positions vary over time, has been exploited to tradeoff between processing time and hardware cost by time-divided sampling rather than simultaneous sampling as in static arrays. A large number of publications have reported on emitter parameter estimations with moving arrays for improving system performance [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. Instead of sampling incoming waves by placing many sensors and receiving channels, a passive synthetic array (PSA) comprises an aperture by temporally repositioning a relatively small number of sensors, sweeping a 1-D or 2-D aperture to realize a much larger virtual linear one.…”

Section: Introductionmentioning

confidence: 99%

“…Kawase proposed a method for circular synthetic array (CSA) applications [ 24 ], whereas it is only adaptable for a single target and a tracking system, since multiple sources and ambiguity resolution were not considered. Later on, Lan utilized two rotating sensors via Multiple signal classification (MUSIC) algorithms [ 25 ]. Nevertheless, only one frequency was considered and the sampling intervals are fixed, which restricts its applications, since in a passive system, sampling intervals and the associated sampling positions are determined by the arriving time of a signal and hence not necessarily uniformly distributed around a circular aperture.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors

Zuo

Pan

2018

Sensors

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This paper essentially focuses on parameter estimation of multiple wideband emitting sources with time-varying frequencies, such as two-dimensional (2-D) direction of arrival (DOA) and signal sorting, with a low-cost circular synthetic array (CSA) consisting of only two rotating sensors. Our basic idea is to decompose the received data, which is a superimposition of phase measurements from multiple sources into separated groups and separately estimate the DOA associated with each source. Motivated by joint parameter estimation, we propose to adopt the expectation maximization (EM) algorithm in this paper; our method involves two steps, namely, the expectation-step (E-step) and the maximization (M-step). In the E-step, the correspondence of each signal with its emitting source is found. Then, in the M-step, the maximum-likelihood (ML) estimates of the DOA parameters are obtained. These two steps are iteratively and alternatively executed to jointly determine the DOAs and sort multiple signals. Closed-form DOA estimation formulae are developed by ML estimation based on phase data, which also realize an optimal estimation. Directional ambiguity is also addressed by another ML estimation method based on received complex responses. The Cramer-Rao lower bound is derived for understanding the estimation accuracy and performance comparison. The verification of the proposed method is demonstrated with simulations.

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A Novel DOA Estimation Algorithm Using Array Rotation Technique

Cited by 20 publications

References 15 publications

Two Novel DOA Estimation Approaches for Real-Time Assistant Calibration Systems in Future Vehicle Industrial

Two Novel DOA Estimation Approaches for Real-Time Assistant Calibration Systems in Future Vehicle Industrial

Derivation of multidimensional stochastic Cramer‐Rao bound for mixture of noncoherent and coherent near/far field signals

Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors

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