Direction Finding for Bistatic Mimo Radar Using Em Maximum Likelihood Algorithm

Chen, Hao Wen; Yang, Dongkai; Wang, Shaoyi; Li, Xiang; Zhuang, Zhao Wen

doi:10.2528/pier13050102

Cited by 9 publications

(9 citation statements)

References 37 publications

(72 reference statements)

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“…The performance of the proposed and spectrum averaging schemes was shown when they are using a 1000 MHz bandwidth with = 3.6 GHz, while Silva's method was presented at several frequencies since it is a narrowband-based angle estimation. The performance bound calculated from the Cramér-Rao bound (CRB) when the DOD and DOA of a stationary target are estimated individually [26,27] was also plotted for reference.…”

Section: Simulation Resultsmentioning

confidence: 99%

Joint Direction-of-Departure and Direction-of-Arrival Estimation in a UWB MIMO Radar Detecting Targets with Fluctuating Radar Cross Sections

Pasya

Iwakiri

Kobayashi

2014

International Journal of Antennas and Propagation

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This paper presents a joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in a multiple-input multiple-output (MIMO) radar utilizing ultra wideband (UWB) signals in detecting targets with fluctuating radar cross sections (RCS). The UWB MIMO radar utilized a combination of two-way MUSIC and majority decision based on angle histograms of estimated DODs and DOAs at each frequency of the UWB signal. The proposed angle estimation scheme was demonstrated to be effective in detecting targets with fluctuating RCS, compared to conventional spectra averaging method used in subband angle estimations. It was found that a wider bandwidth resulted in improved estimation performance. Numerical simulations along with experimental evaluations in a radio anechoic chamber are presented.

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Section: Simulation Resultsmentioning

confidence: 99%

Joint Direction-of-Departure and Direction-of-Arrival Estimation in a UWB MIMO Radar Detecting Targets with Fluctuating Radar Cross Sections

Pasya

Iwakiri

Kobayashi

2014

International Journal of Antennas and Propagation

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“…By inserting (5) into (10), and exploiting the property Q y = J MN Q y *J MN characteristic of Hermitian symmetric Toeplitz matrix Q y , we have…”

Section: Covariance Differencingmentioning

confidence: 99%

“…The peak search methods, such as Capon‐based algorithm [6] and MUSIC‐based [7] algorithm, are first introduced to bi‐static MIMO radar. Then, reduced‐Capon [8], reduced‐MUSIC [9] and expectation‐maximisation (EM) maximum‐likelihood (ML) algorithms [10] are proposed to reduce the multi‐dimensional searching load. To bypass searching process, polynomial root MUSIC algorithm, DOA matrix method, estimation of signal parameters by rotational invariance techniques (ESPRIT) algorithm and PARAFAC‐based technique are applied to bi‐static MIMO radar [11–14].…”

Section: Introductionmentioning

confidence: 99%

Covariance differencing‐based matrix decomposition for coherent sources localisation in bi‐static multiple‐input–multiple‐output radar

Hong

Wan

Cheng

et al. 2015

IET Radar, Sonar & Navigation

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In this study, a covariance differencing-based matrix decomposition algorithm is proposed for locating coherent sources under spatially coloured noise in bi-static multiple-input-multiple-output (MIMO) radar. The method contains three steps. First, the covariance differencing technique is employed to eliminate sensor noise, especially the spatially coloured noise. Second, a block Toeplitz or block Hankel matrix is constructed for decorrelation with the covariance differenced matrix. The forward-only, backward-only and combined forward-backward block Toeplitz/Hankel matrix constructions are defined, respectively. Third, unitary estimation of signal parameters by rotational invariance techniques (ESPRIT) algorithm is applied to estimate directions-of-departure (DODs) and directions-of-arrival (DOAs) of sources. The proposed algorithm offers several advantages. First, it is more robust and provides better estimation performance than other methods. Then, the coloured noise problem is overcome in a simple and effective way. Further, the computational load is comparatively low. Simulation results demonstrate the validity of the proposed algorithm.

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“…Nevertheless, these methods still have some weaknesses which limit their practical application. An EM ML algorithm of DOA estimation for bistatic Multiple-Input Multiple-Output (MIMO) radar is present in [13], where it is shown that the DOA estimation problem can be described as a special case of ML estimation with incomplete data. Simulation results demonstrate the potential and asymptotic efficiency of this approach for MIMO radar systems.…”

Section: Introductionmentioning

confidence: 99%

An Improved Squirrel Search Algorithm for Maximum Likelihood DOA Estimation and Application for MEMS Vector Hydrophone Array

Wang¹,

Kong²,

He³

et al. 2019

IEEE Access

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Maximum likelihood (ML) method for direction of arrival (DOA) estimation achieves an excellent performance in array signal processing, but the complexity and computational load of searching the multidimensional nonlinear function prevented it from practical application. Based on squirrel search algorithm (SSA), an improved SSA (ISSA) for ML DOA estimation is proposed in this paper, which can reduces the computational complexity. The idea of spatial variation and diffuse inspired by the invasive weed optimization(IWO) algorithm is applied to ISSA. The simulation experiments compared ISSA with SSA, IWO, seeker optimization algorithm(SOA), sine cosine algorithm (SCA), genetic algorithm (GA), particle swarm optimization (PSO) and differential evolution (DE) method for ML DOA estimator show that the proposed algorithm has faster convergence speed, fewer iterations and lower root mean square error(RMSE) under different number of signal sources, different signal to noise ratio(SNR) and different population size. Therefor the proposed algorithm does not only ensure the estimation accuracy, but also greatly reduce the computation complexity of multidimensional nonlinear optimization for the ML method. Finally, the test experiment using Micro Electronic Mechanical Systems(MEMS) vector hydrophone array in Fenhe lake show the engineering practicability of proposed ML DOA estimator with ISSA.The results obtained will be valuable in the application of engineering. INDEX TERMS Direction of arrival (DOA) estimation, maximum likelihood (ML), squirrel search algorithm (SSA), invasive weed optimization (IWO), micro electronic mechanical systems (MEMS) vector hydrophone.

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Direction Finding for Bistatic Mimo Radar Using Em Maximum Likelihood Algorithm

Cited by 9 publications

References 37 publications

Joint Direction-of-Departure and Direction-of-Arrival Estimation in a UWB MIMO Radar Detecting Targets with Fluctuating Radar Cross Sections

Joint Direction-of-Departure and Direction-of-Arrival Estimation in a UWB MIMO Radar Detecting Targets with Fluctuating Radar Cross Sections

Covariance differencing‐based matrix decomposition for coherent sources localisation in bi‐static multiple‐input–multiple‐output radar

An Improved Squirrel Search Algorithm for Maximum Likelihood DOA Estimation and Application for MEMS Vector Hydrophone Array

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