Spectral Domain Sparse Representation for DOA Estimation of Signals with Large Dynamic Range

Recently, we proposed a Spectral Domain Sparse Representation (SDSR) approach for the direction-of-arrival estimation of signals incident to an antenna array. In the approach, sparse representation is applied to the conventional Bartlett spectra obtained from snapshots of the signals received by the antenna array to increase the direction-of-arrival (DOA) estimation resolution and accuracy. The conventional Bartlett spectra has limited dynamic range, meaning that one may not be able to identify the presence of weak signals in the presence of strong signals. This is because, in the conventional Bartlett spectra, uniform weighting (window) is applied to signals received by various antenna elements. Apodization can be used in the generation of Bartlett spectra to increase the dynamic range of the spectra. In Apodization, more than one window function is used to generate different portions of the spectra. In this paper, we extend the SDSR approach to include Bartlett spectra obtained with Apodization and to evaluate the performance of the extended SDSR approach. We compare its performance with a two-step SDSR approach and with an approach where Bartlett spectra is obtained using a low sidelobe window function. We show that an Apodization Bartlett-based SDSR approach leads to better performance with just single-step processing.

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Application of Sparse Representation to Bartlett Spectra for Improved Direction of Arrival Estimation

Sensors ◽

10.3390/s21010077 ◽

2020 ◽

Vol 21 (1) ◽

pp. 77

Author(s):

Jacob Compaleo ◽

Inder J. Gupta

Keyword(s):

Sparse Representation ◽

Regularization Parameter ◽

Angular Separation ◽

Direction Of Arrival ◽

Doa Estimation ◽

Direction Of Arrival Estimation ◽

Small Signal ◽

Music Algorithm ◽

A New Technique ◽

Better Than

A new technique for high-resolution direction of arrival estimation is presented. The method utilizes the traditional Bartlett spectra and sparse representation to locate emitters in single and multiple emitter scenarios. A method for selecting the sparse representation regularization parameter is also presented. Using Monte Carlo simulations, we show that the proposed approach achieves accurate direction of arrival (DOA) estimations that are unbiased and a variance that approaches the Cramer–Rao lower bound. We show that our method outperforms the popular MUSIC algorithm, and is slightly better than the sparse representation based L1-SVD algorithm when angular separation between emitters is small, signal SNR is low, and a small number of snapshots are used in DOA estimation.

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Investigations on antenna array calibration algorithms for direction-of-arrival estimation

Advances in Radio Science ◽

10.5194/ars-14-181-2016 ◽

2016 ◽

Vol 14 ◽

pp. 181-190 ◽

Cited By ~ 5

Author(s):

Michael Eberhardt ◽

Philipp Eschlwech ◽

Erwin Biebl

Keyword(s):

Antenna Array ◽

Array Signal Processing ◽

Direction Of Arrival ◽

Doa Estimation ◽

Calibration Procedure ◽

Estimation Algorithms ◽

Modeling Errors ◽

Array Calibration ◽

History Of ◽

The Common

Abstract. Direction-of-arrival (DOA) estimation algorithms deliver very precise results based on good and extensive antenna array calibration. The better the array manifold including all disturbances is known, the better the DOA estimation result. A simplification or ideally an omission of the calibration procedure has been a long pursued goal in the history of array signal processing. This paper investigates the practicability of some well known calibration algorithms and gives a deeper insight into existing obstacles. Further analysis on the validity of the common used data model is presented. A new effect in modeling errors is revealed and simulation results substantiate this theory.

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New DOA Estimation Method for Wideband Coherent Signals in the Presence of Correlated Noise

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.263-266.157 ◽

2012 ◽

Vol 263-266 ◽

pp. 157-161 ◽

Cited By ~ 1

Author(s):

Jin Zhang ◽

Yun Xiang Mao ◽

Jian Yun Zhang

Keyword(s):

Numerical Simulation ◽

Antenna Array ◽

Covariance Matrix ◽

Estimation Method ◽

Direction Of Arrival ◽

Doa Estimation ◽

Correlated Noise ◽

Linear Antenna ◽

Coherent Signals ◽

Linear Antenna Array

With a uniform linear antenna array, a new direction-of-arrival (DOA) estimation method is proposed for wideband coherent signals in the presence of unknown correlated noise but with structured covariance matrix. Based on this proposed structure, i.e. Hermitian Toeplitz, a spatial differencing operation that exploits this symmetry is applied to remove the effect of the unknown noise and a new matrix is constructed accordingly at each frequency bin. Following this step, a focusing operation is performed to give the corresponding aligned covariance matrix. Finally, an eigenstructure-based DOA estimation method is applied. The validity of the method is supported by numerical simulation under various conditions.

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Hybrid Differential Evolution with Biogeography-Based Optimization for Design of a Reconfigurable Antenna Array with Discrete Phase Shifters

International Journal of Antennas and Propagation ◽

10.1155/2011/685629 ◽

2011 ◽

Vol 2011 ◽

pp. 1-12 ◽

Cited By ~ 12

Author(s):

Xiangtao Li ◽

Minghao Yin

Keyword(s):

Differential Evolution ◽

Antenna Array ◽

Antenna Arrays ◽

Dynamic Range ◽

Phase Shifters ◽

Main Beam ◽

Reconfigurable Antenna ◽

Reconfigurable Design ◽

Low Sidelobe ◽

Discrete Phase

Multibeam antenna arrays have important applications in communications and radar. This paper presents a new method of designing a reconfigurable antenna with quantized phase excitations using a new hybrid algorithm, called DE/BBO. The reconfigurable design problem is to find the element excitation that will result in a sector pattern main beam with low sidelobes with additional requirement that the same excitation amplitudes applied to the array with zero-phase should be in a high directivity, low sidelobe pencil-shaped main beam. In order to reduce the effect of mutual coupling between the antenna-array elements, the dynamic range ratio is minimized. Additionally, compared with the continuous realization and subsequent quantization, experimental results indicate that the performance of the discrete realization of the phase excitation value can be improved. In order to test the performances of hybrid differential evolution with biogeography-based optimization, the results of some state-of-art algorithms are considered, for the purposed of comparison. Experiment results indicate the better performance of the DE/BBO.

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Direction-of-Arrival Estimation of Electromagnetic Wave Impinging on Spherical Antenna Array in the Presence of Mutual Coupling Using a Multiple Signal Classification Method

Electronics ◽

10.3390/electronics10212651 ◽

2021 ◽

Vol 10 (21) ◽

pp. 2651

Author(s):

Oluwole John Famoriji ◽

Thokozani Shongwe

Keyword(s):

Electromagnetic Wave ◽

Fourier Series ◽

Antenna Array ◽

Mutual Coupling ◽

Direction Of Arrival ◽

Doa Estimation ◽

Signal Classification ◽

Multiple Signal Classification ◽

Multiple Signal ◽

Spherical Antenna

A spherical antenna array (SAA) is the configuration of choice in obtaining an antenna array with isotropic characteristics. An SAA has the capacity to receive an electromagnetic wave (EM) with equal intensity irrespective of the direction-of-arrival (DoA) and polarization. Therefore, the DoA estimation of electromagnetic (EM) waves impinging on an SAA with unknown mutual coupling needs to be considered. In the spherical domain, the traditional multiple signal classification algorithm (SH-MUSIC) is faced with a computational complexity problem. This paper presents a one-dimensional MUSIC method (1D-MUSIC) for the estimation of the azimuth and elevation angles. An intermediate mapping matrix that exists between Fourier series and the spherical harmonic function is designed, and the Fourier series Vandermonde structure is used for the realization of the polynomial rooting technique. This mapping matrix can be computed prior to the DoA estimation, and it is only a function of the array configuration. Based on the mapping matrix, the 2-D angle search is transformed into two 1-D angle findings. Employing the features of the Fourier series, two root polynomials are designed for the estimation of the elevation and azimuth angles, spontaneously. The developed method avoids the 2-D spectral search, and angles are paired in automation. Both numerical simulation results, and results from experimental measured data (i.e., with mutual coupling effect incorporated), show the validity, potency, and potential practical application of the developed algorithm.

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Spacial Filter of Weighting Method Based on Spectrum Analyse

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.605-607.1890 ◽

2012 ◽

Vol 605-607 ◽

pp. 1890-1896

Author(s):

Xian Mao Li ◽

Gao Ming Huang ◽

Dong Xia

Keyword(s):

Traditional Method ◽

Window Function ◽

Weighting Method ◽

Array Antennas ◽

Low Sidelobe ◽

Time Signals ◽

Selection Of ◽

Weighting Window ◽

Hardware Structure

The selection of a certain scope angle signal in the traditional method is to switch the hard switches in antennas, this paper proposes a method, which based on a weighting method to filter the signal in certain directions, namely spacial filter. With array antennas，the compositive signal can be acquired, by which the phrase and plus (weighting) of each unit antenna’s signal be adjusted and then the signals be added. In different time, signals can be selected in any scope of directions through adjusting each channels by different weighting. The weighting parameters can be obtained through the analysis of spacial signal and spacial spectrum, and then obtains an appropriate weighting window function. Simulation shows that Hamming window’s weighting is the best among the three representative windows functions. It can obtain a low sidelobe (-44dB) and less rising edge and declining edges. And the paper also give a hardware structure.

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Staring Spotlight SAR with Nonlinear Frequency Modulation Signal and Azimuth Non-Uniform Sampling for Low Sidelobe Imaging

Sensors ◽

10.3390/s21196487 ◽

2021 ◽

Vol 21 (19) ◽

pp. 6487

Author(s):

Wei Xu ◽

Lu Zhang ◽

Chonghua Fang ◽

Pingping Huang ◽

Weixian Tan ◽

...

Keyword(s):

Frequency Modulation ◽

Window Function ◽

Projection Algorithm ◽

Nonlinear Frequency ◽

Uniform Sampling ◽

Low Sidelobe ◽

Sampling Sequence ◽

Imaging Mode ◽

Non Uniform Sampling ◽

Weighting Window

In synthetic aperture radar (SAR) imaging, geometric resolution, sidelobe level (SLL) and signal-to-noise ratio (SNR) are the most important parameters for measuring the SAR image quality. The staring spotlight mode continuously transmits signals to a fixed area by steering the azimuth beam to acquire azimuth high geometric resolution, and its two-dimensional (2D) impulse response with the low SLL is usually obtained from the 2D weighted power spectral density (PSD) by the selected weighting window function. However, this results in the SNR reduction due to 2D amplitude window weighting. In this paper, the staring spotlight SAR with nonlinear frequency modulation (NLFM) signal and azimuth non-uniform sampling (ANUS) is proposed to obtain high geometric resolution SAR images with the low SLL and almost without any SNR reduction. The NLFM signal obtains non-equal interval frequency sampling points under uniform time sampling by adjusting the instantaneous chirp rate. Its corresponding PSD is similar to the weighting window function, and its pulse compression result without amplitude window weighting has low sidelobes. To obtain a similar Doppler frequency distribution for low sidelobe imaging in azimuth, the received SAR echoes are designed to be non-uniformly sampled in azimuth, in which the sampling sequence is dense in middle and sparse in both ends, and azimuth compression result with window weighting would also have low sidelobes. According to the echo model of the proposed imaging mode, both the back projection algorithm (BPA) and range migration algorithm (RMA) are modified and presented to handle the raw data of the proposed imaging mode. Both imaging results on simulated targets and experimental real SAR data processing results of a ground-based radar validate the proposed low sidelobe imaging mode.

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Detection and Direction-of-Arrival Estimation of Weak Spread Spectrum Signals Received with Antenna Array

Electronics ◽

10.3390/electronics10212566 ◽

2021 ◽

Vol 10 (21) ◽

pp. 2566

Author(s):

Jarosław Magiera

Keyword(s):

Antenna Array ◽

Spread Spectrum ◽

Additive White Gaussian Noise ◽

Direction Of Arrival ◽

Doa Estimation ◽

Probability Of Detection ◽

Joint Detection ◽

Wide Range ◽

To Receive ◽

Spread Spectrum Signals

This paper presents a method for the joint detection and direction of arrival (DOA) estimation of low probability of detection (LPD) signals. The proposed approach is based on using the antenna array to receive spread-spectrum signals hidden below the noise floor. Array processing exploits the spatial correlation between phase-delayed copies of the signal and allows us to evaluate the parameter used to make the decision about the presence of LPD transmission. The DOA estimation is based on the covariance between signals received by sensors for the fixed geometry of the antenna array. Moreover, the paper provides a method for mitigating narrowband interferences prior to signal detection. The presented methods were verified through simulations which proved that the confident detection of a one-second transmission in an additive white Gaussian noise channel is possible even when the noise is 24 dB higher than the power of the received signal. The performance of DOA estimation is analyzed in a wide range of signal-to-noise and interference-to-noise ratios. It is found that the DOA may be estimated with an RMS error not exceeding 10 degrees, even if interference occupies 15% of the analyzed frequency band.

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