Reduced-Complexity Direction of Arrival Estimation Using Real-Valued Computation with Arbitrary Array Configurations

Yan, Feng-Gang; Jun, Wang; Shuai, Liu; Shen, Yi; Jin, Minghe

doi:10.1155/2018/3284619

Cited by 8 publications

(7 citation statements)

References 40 publications

(58 reference statements)

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“…Step 3: Construct the projection matrix (i.e., U P ) using (32) Step 4: Construct the pseudo spectrum using (33) Step 5: Find the locations of the produced peaks to determine the AoAs…”

Section: Outputmentioning

confidence: 99%

“…A modified Real-Value MUSIC was proposed in Reference [33] to reduce the computational complexity of the Real MUSIC method without losing its suitability for an arbitrary array. This method uses only the real values of the measured covariance matrix in both the Eigen decomposition and spectral search stages, leading to significant complexity reduction.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

2019

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Several works show that the linear Angle of Arrival (AoA) methods such as Projection Matrix (PM) have low computational complexity compared to the subspace methods. Although the PM method is classified as a subspace method, it does not need decomposition of the measured matrix. This work investigates the effect of the sampled columns within the covariance matrix on the projection matrix construction. To the authors' knowledge, this investigation has not been addressed in the literature. Unlike the subspace methods such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Minimum Norm, Propagator, etc., which have to use a specific number of columns, we demonstrate this aspect is not applicable in the PM method. To this end, the projection matrix is formed based on a various number of sampled columns to estimate the arrival angles. A theoretical analysis is accomplished to illustrate the relationship between the number of the sampled columns and the degrees of freedom (DOFs). The analysis shows that with the same aperture size, the DOFs can be increased by increasing only the number of sampled columns in the projection matrix calculation step. An intensive Monte Carlo simulation for different scenarios is presented to validate the theoretical claims. The estimation accuracy of the PM method, based on the proposed selected sampling methodology outperforms all the other techniques with less complexity compared to the Capon and MUSIC methods. The estimation accuracy is evaluated in terms of Root Mean Square Error (RMSE) and the Probability of Successful Detection (PSD). The results are presented and discussed.

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“…Step 3: Construct the projection matrix (i.e., U P ) using (32) Step 4: Construct the pseudo spectrum using (33) Step 5: Find the locations of the produced peaks to determine the AoAs…”

Section: Outputmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

2019

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“…This follows the works in references [7]- [9] who devised different transformations to convert the complex data set to a real-valued data set in order to avoid complex value computation in the MUSIC algorithm. Similarly, [10] and [11] also considered only the amplitude of signal in MUSIC computation by separating the data set into real and imaginary parts and then using real parts for DoA estimation in order to reduce the computational complexity of the algorithm. All the designs proposed in [7] - [11] acquire complex data and perform some computation to obtain a real-valued data set at certain stage of the algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, [10] and [11] also considered only the amplitude of signal in MUSIC computation by separating the data set into real and imaginary parts and then using real parts for DoA estimation in order to reduce the computational complexity of the algorithm. All the designs proposed in [7] - [11] acquire complex data and perform some computation to obtain a real-valued data set at certain stage of the algorithm. Contrary to these approaches our proposed design does not require any complex data at any level.…”

Section: Introductionmentioning

confidence: 99%

Towards Low Latency and Resource-Efficient FPGA Implementations of the MUSIC Algorithm for Direction of Arrival Estimation

Butt

Khan

Ullah

et al. 2021

IEEE Trans. Circuits Syst. I

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The estimation of the Direction of Arrival (DoA) is one of the most critical parameters for target recognition, identification and classification. MUltiple SIgnal Classification (MUSIC) is a powerful technique for DoA estimation. The algorithm requires complex mathematical operations like the computation of the covariance matrix for the input signals, eigenvalue decomposition and signal peak search. All these signal processing operations make real-time and resource-efficient implementation of the MUSIC algorithm on Field Programmable Gate Arrays (FPGAs) a challenge.In this paper, a novel design approach is proposed for the FPGAimplementation of the MUSIC algorithm. This approach enables a significant reduction in both FPGA resources and latency. In more detail, the proposed design enables the estimation of DoA in real-time scenarios in 2µsec with 30% to 50% fewer resources as compared to existing techniques.

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“…Direction-of-Arrival (DOA) plays an important role in wireless communication, radar, sonar, and other areas. In the past few decades, many methods, such as subspace-based approaches, maximum likelihood methods, and sparserepresentation-based methods [1][2][3][4][5] have been studied extensively on this topic.…”

Section: Introductionmentioning

confidence: 99%

DOA Estimation for Highly Correlated and Coherent Multipath Signals with Ultralow SNRs

Zou

et al. 2019

International Journal of Antennas and Propagation

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In a typical multipath propagation environment, there exists a strong direct path signal accompanying with several weak multipath signals. Due to the strong direct path interference and other masking effects, the Direction-of-Arrival (DOA) of a weak multipath signal is hard to be estimated. In this paper, a novel method is proposed to estimate the DOA of multipath signals with ultralow signal-to-noise ratio (SNR). The main idea is to increase the SNR and signal-to-interference ratio (SIR) of the desired multipath signal in time-delay domain before DOA estimation processing. Firstly, the cross-correlation functions of the direct path signal and the received array signal are calculated. Then, they are combined and constructed to an enhanced array signal. Under certain conditions, the SNR and SIR of the desired signal can be significantly increased. Finally, the DOAs of multipath signals can be estimated by conventional technologies, and the associated time delays can be measured on the DOA-time-shift map. The SNR and SIR gains of the desired signal are analyzed theoretically, and theoretical analysis also indicates that the Cramer–Rao bound can be reduced. Simulation examples are presented to verify the advantages of the proposed method.

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Reduced-Complexity Direction of Arrival Estimation Using Real-Valued Computation with Arbitrary Array Configurations

Cited by 8 publications

References 40 publications

The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

Towards Low Latency and Resource-Efficient FPGA Implementations of the MUSIC Algorithm for Direction of Arrival Estimation

DOA Estimation for Highly Correlated and Coherent Multipath Signals with Ultralow SNRs

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