Improved ESPRIT Method for Joint Direction-of-Arrival and Frequency Estimation Using Multiple-Delay Output

Wang, Xudong; Zhang, Xiaofei; Li, Jianfeng; Bai, Jinchao

doi:10.1155/2012/309269

Cited by 26 publications

(7 citation statements)

References 19 publications

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“…In this section, we mainly compare the performance of the following algorithms: TLS-ESPRIT, Root-MUSIC, AF-ESPRIT in [5], MS-KAI-ESPRIT in [7], VI-MUSIC in [15], and the proposed VI-LC-ESPRIT algorithm. K is the number of source signals, N is the number of total sensors, and L is the sample snapshots.…”

Section: Complexity Analysismentioning

confidence: 99%

See 1 more Smart Citation

Velocity-independent and low-complexity method for 1D DOA estimation using an arbitrary cross-linear array

Ning¹,

Jing²,

Li³

et al. 2020

EURASIP J. Adv. Signal Process.

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This paper focuses on a low-complexity one-dimensional (1D) direction-of-arrival (DOA) algorithm with an arbitrary cross-linear array. This algorithm is highly accurate without the performance error usually caused by the uncertainty factor of the wave velocity in the underwater environment. The geometric relationship between two crossed linear arrays is employed to derive the expression of DOA estimation with the finding that this algorithm is capable of excluding the wave velocity variable in the DOA estimation expression. A method without parameter pairing is also proposed to reduce the complexity of this algorithm. Additionally, the influence of wave velocity is analyzed in terms of RMSE c and the Cramer-Rao bound (CRB) for 1D DOA with the arbitrary cross-linear array is established. The simulation results demonstrate that the proposed algorithm can achieve better performance than the traditional algorithm under the condition of an inaccurate estimate of wave velocity. Compared with the velocity-independent DOA algorithm, it exhibits the feature of low complexity.

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Section: Complexity Analysismentioning

confidence: 99%

“…The MR-ESPRIT algorithm is superior at suppressing the impact of noise. An automatic pairing joint direction-of-arrival and frequency estimation, abbreviated as AF-ESPRIT, is presented in [5]. By using the multiple-delay output of a uniform linear antenna array (ULA), this algorithm can estimate joint angles and frequencies.…”

Section: Introductionmentioning

confidence: 99%

Velocity-independent and low-complexity method for 1D DOA estimation using an arbitrary cross-linear array

Ning¹,

Jing²,

Li³

et al. 2020

EURASIP J. Adv. Signal Process.

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“…As is shown in Fig. 2, we consider P − 1 levels delay where the p-th delay is τ p = pτ and τ satisfies 0 < τ < 1/(P − 1) max(f k ) [17].…”

Section: Data Modelmentioning

confidence: 99%

Joint 2-D DOA and Doppler Estimation for L-Shaped Array via Dual PARAFAC With Triple Matching Implementation

Zhang

et al. 2019

IEEE Access

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A dual parallel factor (PARAFAC)-based approach to jointly estimating the two-dimensional direction of arrival (2-D DOA) and Doppler is proposed in this paper, where an L-shaped array consisting of acoustic vector-sensor is used. First, we apply the PARAFAC decomposition to the data model formed by concatenating the outputs of multi-level delays of the observations, and we get the parameter matrix H, which accomplish the 2-D DOA estimation and pairing automatically, then the dual PARAFAC decomposition is applied to the achieved composite steering matrix from the first PARAFAC decomposition, and thus, the same permutation matrices link the estimates of steering matrices and delay matrices from X-subarray and Ysubarray, respectively. Following this, the Doppler and 2-D DOA matching information are obtained via triple matching implementation, e.g. 2-D DOA and frequency matching. Finally, Doppler is estimated by delay matrices. The proposed algorithm is computationally effective for both uniform and non-uniform L-shaped array as SNR exceeds 15dB, and its performance outperforms the joint angle and Doppler shift ESPRIT (JAD-ESPRIT) algorithm and the joint angle and Doppler shift PM (JAD-PM) algorithm. The simulation results justified the effectiveness of the proposed algorithm. INDEX TERMS Two-dimensional direction of arrival (2-D DOA), Doppler, L-shaped array, dual parallel factor (PARAFAC), triple matching implementation.

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“…As for compressed sensing-based algorithms [4], minimization of ℓ1-norm is imposed on the sensing matrix to determine the sparse coding. However, due to Doppler shift [5] or in applications of radar tracking [6] and cognitive radios [7,8], the carrier frequency of signal sources can be ambiguous.…”

Section: Introductionmentioning

confidence: 99%

Joint Estimation of DOA and Frequency of Multiple Sources with Orthogonal Coprime Arrays

Hsu

Kiang

2019

Sensors

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A two-stage method is proposed to jointly estimate the direction-of-arrival (DOA) and carrier frequency (CF) of multiple sources, by using two orthogonal coprime arrays (CPAs). The DOAs of CF-known sources are estimated first by applying a spatial smoothing MUSIC algorithm. The contribution of these source signals is then removed from the originally received signal by applying an orthogonal complement projector. Next, a joint-ESPRIT algorithm is applied to estimate the DOAs and CFs of the remaining CF-unknown sources. With two orthogonal CPA(5, 6), the RMSE of DOA and CF of applying the proposed method to 30 sources, 13 of which have unknown CF, is less than 1% at SNR >5 dB.

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Improved ESPRIT Method for Joint Direction-of-Arrival and Frequency Estimation Using Multiple-Delay Output

Cited by 26 publications

References 19 publications

Velocity-independent and low-complexity method for 1D DOA estimation using an arbitrary cross-linear array

Velocity-independent and low-complexity method for 1D DOA estimation using an arbitrary cross-linear array

Joint 2-D DOA and Doppler Estimation for L-Shaped Array via Dual PARAFAC With Triple Matching Implementation

Joint Estimation of DOA and Frequency of Multiple Sources with Orthogonal Coprime Arrays

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