Application of the Newton Method to Improve the Accuracy of Toa Estimation With the Beamforming Algorithm and the Music Algorithm

Lee, Joon-Ho; Jeong, Yun Seong; Cho, Sung‐Woo; Yeo, Woon-Young; Pister, Kristofer S. J.

doi:10.2528/pier10112608

Cited by 31 publications

(28 citation statements)

References 32 publications

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“…Subsequently, for two-dimensional (2D) DOA estimation, MUSIC algorithm performs a spectrum peak search for all angles in azimuth and elevation what causes demanding computations, and makes this algorithm unsuitable for real-time user tracking. To overcome this problem a number of algorithms have been developed [4][5][6][7][8][9][10][11][12][13][14][15][16]. For 2D scenarios, ESPRIT algorithm is extended in [10], to provide both azimuth and elevation estimates.…”

Section: Introductionmentioning

confidence: 99%

Efficient Neural Network Approach for 2d Doa Estimation Based on Antenna Array Measurements

Agatonovic¹,

Stankovic²,

Milovanović³

et al. 2013

PIER

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Abstract-In this paper, we present an efficient Artificial Neural Network (ANN)-based model to estimate both azimuth and elevation arrival angles of a signal source. To achieve this goal, the ANN model is constructed using measurement data obtained by a rectangular antenna array in the space-frequency domain. Unlike classical superresolution algorithms such as 2D MUSIC, the proposed model is capable to account for imperfections of measurement equipment as well as mutual couplings between array elements. The neural model has been verified for several angular positions and frequencies. It is shown that the use of ANN model to estimate angular positions of a signal source yields more accurate results when compared to 2D MUSIC. Moreover, the neural model significantly outperforms 2D MUSIC in terms of speed of computation.

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Section: Introductionmentioning

confidence: 99%

Efficient Neural Network Approach for 2d Doa Estimation Based on Antenna Array Measurements

Agatonovic¹,

Stankovic²,

Milovanović³

et al. 2013

PIER

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“…However, the GSC structure for beamforming makes the implementation much more efficient with adaptive algorithms, which assumes the DOAs of desired signals are prior known to receiver array according to signal estimation techniques [36] or other ways, such as inertial navigation system (INS) or ephemeris information of navigation receiver, etc.. And the LC-GSC weighting vector is expressed by…”

Section: Linear Multiple Constraint Generalized Sidelobe Canceller (Lmentioning

confidence: 99%

A Mixing Vector Based an Affine Combination of Two Adaptive Filters for Sensor Array Beamforming

Sun

Wang

2012

PIER

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Abstract-In this paper, a novel beamformer for adaptive combination of two adaptive filters is proposed for interference mitigation of sensor array. The proposed approach adaptively combines two individual filters by coefficient weights vector instead of one scale parameter and takes the constraint of affine combination into consideration rather than previous studies. Due to the more degrees of freedom offered by the mixing vector, the proposed beamformer significantly improves the convergence and tracking performances of the combined filter under both stationary and non-stationary environments, respectively. Based on the generalized sidelobe canceller (GSC) structure, the optimal mixing vector is derived by Lagrange method, and then several new effective iterative algorithms are developed for its updating in practical implementation. Furthermore, theoretical discussions of the convergent performances and complexities of the proposed iterative algorithms are also investigated to verify the feasibility of the proposed beamformer. Moreover, the proposed methods in application of beamforming for interference mitigation of antenna array are simulated based space-time processing technique. When compared to existing methods, the proposed approach exhibits faster convergence rate and higher output signal to interference plus noise ratio (SINR). Its good behavior is illustrated through simulation results.

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“…Most high resolution DOA estimation algorithms, such as multiple signal classification (MUSIC)-based and estimation of signal parameters via rotational invariance techniques (ESPRIT)-based algorithms, when used on uniform liner array with omni-direction antenna elements, always have high performances [17][18][19]. But usually, these algorithms cannot be used for conformal antenna array directly because of the varying curvature.…”

Section: Introductionmentioning

confidence: 99%

Fast Estimation of Frequency and 2-D Doas for Cylindrical Conformal Array Antenna Using State-Space and Propagator Method

Si¹,

Wan²,

Liu³

et al. 2013

PIER

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Abstract-The pattern of each element in conformal array has a different direction for the curvature of conformal carrier, which results in polarization diversity of conformal array antenna. Polarization parameters of incident signals are considered in snapshot data model in order to describe the polarization diversity of conformal array antenna. It is required that the polarization parameters and direction of arrival (DOA) of incident signals are estimated together. An integrated frequency and DOA estimation method is proposed in this paper for cylindrical conformal array antenna. The frequency estimation of signal source is obtained by constructing state-space matrix. Through well-designed configuration of elements on cylindrical carriers along with estimation of signal parameters via propagator method (PM), the decoupling scheme for DOA and polarization parameters is implemented. A novel parameter pairing method for frequency and DOA of multiple sources utilizing the interpolation technique is given, based on which the fast frequency-DOA estimation algorithm is developed. Effectiveness of the proposed method is demonstrated by simulation experimental results.

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Application of the Newton Method to Improve the Accuracy of Toa Estimation With the Beamforming Algorithm and the Music Algorithm

Cited by 31 publications

References 32 publications

Efficient Neural Network Approach for 2d Doa Estimation Based on Antenna Array Measurements

Efficient Neural Network Approach for 2d Doa Estimation Based on Antenna Array Measurements

A Mixing Vector Based an Affine Combination of Two Adaptive Filters for Sensor Array Beamforming

Fast Estimation of Frequency and 2-D Doas for Cylindrical Conformal Array Antenna Using State-Space and Propagator Method

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