Combined MUSIC with ESPRIT Algorithm for Angle Estimation in Bistatic MIMO Radar System

Liu, Xiaoli; Liao, Guisheng

doi:10.3724/sp.j.1146.2009.01459

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…In Figs. 4 to 7, we compare our algorithm with ESPRIT [8], 2D‐MUSIC [11], RD‐MUSIC [14] and combined MUSIC with ESPRIT algorithm of [26] in 3 × 3, 4 × 4, 5 × 5 transmitting and receiving arrays. In the case of the combination of MUSIC with ESPRIT, the DOD parameter is estimated by MUSIC and the DOA parameter is estimated by ESPRIT in a specific manner.…”

Section: Simulation Resultsmentioning

confidence: 99%

Joint estimation of direction of departure and direction of arrival for multiple‐input multiple‐output radar based on improved joint ESPRIT method

Li²,

Khodjaev

et al. 2015

IET Radar, Sonar & Navigation

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This study presents an improved joint estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm for low-complexity simultaneous estimation of direction of departure (DOD) and direction of arrival (DOA) in a multiple-input-multiple-output radar system. The proposed algorithm is based on a data matrix and estimates DOD and DOA without a pairing operation. The computational complexity of the proposed joint ESPRIT algorithm is derived to be less than that of conventional two dimension multiple signal classification (2D-MUSIC) and reduced dimension multiple signal classification. The authors' simulation results demonstrate that the proposed algorithm achieves performance very close to that of 2D-MUSIC and better performance than that of the ESPRIT algorithm.

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Section: Simulation Resultsmentioning

confidence: 99%

Joint estimation of direction of departure and direction of arrival for multiple‐input multiple‐output radar based on improved joint ESPRIT method

Li²,

Khodjaev

et al. 2015

IET Radar, Sonar & Navigation

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show abstract

“…The smoothed vectors are arranged in a reversed order (η, η − 1, …, 1) in (16), that is, the last forward spatially smoothed vector constitutes the first column, whereas the first forward spatially smoothed vector constitutes the last column. It is worth noting that the number and dimension of the forward spatially smoothed vectors are equal to η in Toeplitz construction.…”

Section: Forward/backward Block Toeplitz Matrix Constructionmentioning

confidence: 99%

“…The non‐parametric approaches are more computationally efficient, thus several representative algorithms are introduced into bi‐static MIMO radar. The algorithm using high‐order cumulant statistics [15] is applied to bi‐static MIMO radar in [16]. The cross‐correlation‐based decomposition technique [12] is conceptually introduced to bi‐static MIMO radar in [17].…”

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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“…The Capon algorithm can be assigned to the first group of algorithms [17][18][19][20]. The MUSIC (Multiple Signal Classification) and ESPRIT (Estimation of Signal Parameters via Rational Invariance Techniques) algorithms should be classified into the second [20][21][22][23][24]. A comparison of the indicated DoA algorithms is presented by the authors of this publication in [11].…”

Section: Introductionmentioning

confidence: 99%

Capon-like method for direction of arrival estimation using TDM MIMO radar

Ślesicka,

Kawalec,

Ślesicki

2023

Metrology and Measurement Systems

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This paper presents a novel measurement method and briefly discusses the basic properties of direction of arrival (DoA) measurement in a multiple-input multiple-output (MIMO) radar system by using orthogonality with time-division multiplexing (TDM), where only one transmitting antenna element is active in each time slot. This paper presents the mathematical model of the TDM-MIMO radar operating at 10 GHz, transmitting a string of pulses, the method of transmitting and receiving the signal, and the method of measuring the angle of arrival of the signal based on the use of the Capon algorithm and its modifications. Finally, the correctness of the theory, algorithm and method of measuring the direction of arrival of the signal is verified by experimental simulation. The work discussed in this paper is of great significance to practically demonstrate the capabilities of the TDM MIMO radar sensor in practical implementations like reconnaissance and electronic warfare systems.

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Combined MUSIC with ESPRIT Algorithm for Angle Estimation in Bistatic MIMO Radar System

Cited by 6 publications

References 6 publications

Joint estimation of direction of departure and direction of arrival for multiple‐input multiple‐output radar based on improved joint ESPRIT method

Joint estimation of direction of departure and direction of arrival for multiple‐input multiple‐output radar based on improved joint ESPRIT method

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

Capon-like method for direction of arrival estimation using TDM MIMO radar

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