Near field targets localization using bistatic MIMO system with spherical wavefront based model

Chargé, Pascal; Wang, Yide; Singh, Parth Raj

doi:10.23919/eusipco.2017.8081642

Cited by 13 publications

(4 citation statements)

References 21 publications

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“…Unlike the majority of existing approaches that are based on the approximate model, in [181][182][183], methods for NFSs localization are presented that consider the exact wavefront model. For the mixed sources scenario, there is a significant need for a comprehensive study of the errors caused by employing the approximate NF model, along with a solution to the problem when the exact model is considered [184].…”

Section: Approximate Near-field Modelmentioning

confidence: 99%

A Comprehensive Review of Direction-of-Arrival Estimation and Localization Approaches in Mixed-Field Sources Scenario

Molaei,

Zakeri,

Andargoli

et al. 2024

IEEE Access

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Direction-of-arrival (DOA) estimation plays a crucial role in array signal processing across various domains, including radar, sonar, wireless communications, and seismic exploration. However, traditional DOA techniques often assume either far-field (FF) or near-field (NF) propagation, limiting their applicability in scenarios involving mixed-field sources. DOA estimation and localization in scenarios involving mixed NF and FF sources is a complex and dynamic field that has garnered significant research attention in recent years. This multifaceted and evolving area holds promise for addressing challenges in radar, wireless communications, and acoustic sensing applications. This review paper provides a comprehensive overview of the methodologies, techniques, and advancements in this domain. We categorize existing methodologies, discussing their advantages and limitations. Furthermore, we delve into the mathematical modeling of mixed-field sources and essential signal processing techniques for parameter estimation. Special attention is given to technical issues such as aperture loss, computational complexity, and hardware considerations. The paper discusses the various sources of noise in the mentioned scenario and highlights the importance of modeling noise accurately for effective estimation. It also explores different scenarios and assumptions considered in the literature, ranging from non-Gaussian and nonstationary noise environments to scenarios involving multipath propagation and unknown mutual coupling effects. A detailed examination of the statistical approaches used in DOA estimation and localization reveals a diverse range of methods, including higher-order statistics and second-order statistics, each with its own advantages and applications. A comparative evaluation of various approaches highlights their performance in terms of estimation accuracy, resolution, aperture loss and computational efficiency. This provides insights into the trade-offs involved in choosing between different approaches. The review also identifies promising future research directions, such as the exploration of advanced signal processing techniques like compressive sensing and deep learning, exact NF modeling, estimation based on one-bit measurements, the integration of polarization diversity, employing metasurface antennas, tracking parameters, and the utilization of full-wave or experimental data for a more realistic representation of the challenges. By reviewing advances in methodologies and techniques, as well as outlining future research directions aimed at addressing the complexities of mixed-field scenarios, this paper paves the way for the development of more robust and reliable localization systems capable of handling real-world complexities.

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Section: Approximate Near-field Modelmentioning

confidence: 99%

A Comprehensive Review of Direction-of-Arrival Estimation and Localization Approaches in Mixed-Field Sources Scenario

Molaei,

Zakeri,

Andargoli

et al. 2024

IEEE Access

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“…The Fresnel approximation is employed to enhance the steering vector. The phase difference between the first and mth array element can be expressed as follows [30]:…”

Section: Near-field Focused Beamforming Modelmentioning

confidence: 99%

The Mitigation of Mutual Coupling Effects in Multi-Beam Echosounder Calibration under Near-Field Conditions

Zhang,

Yuan,

Sun

et al. 2024

JMSE

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The advancement of unmanned platforms is driving the miniaturization and cost reduction of the multi-beam echosounder (MBES). In the process of MBES array calibration, the mutual coupling significantly impacts the performance of parameter estimation. We propose a correction method to mitigate the mutual coupling effects in the calibration of MBES acoustic array. Initially, a near-field focused beamforming model is established to assess the influence of mutual coupling. Subsequently, the covariance matrix in the frequency domain is constructed to enhance algorithm efficiency and simplify solution procedures. This construction eliminates the need for a low-pass filtering step after heterodyning through extracting peak values near zero frequency in the signal frequency domain. Meanwhile, the Toeplitz property is leveraged to render the estimation results independent of the mutual coupling matrix. Finally, the mutual coupling coefficients and the direction of arrival (DOA) are joint-estimated and the Cramér–Rao bound is derived. The presented method effectively addresses the engineering challenge of MBES mutual coupling calibration. Additionally, the performance of the proposed method is verified through the measured data in simulation and tank experiments.

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“…However, it has a very high computational complexity due to the use of a 2D spectral search as well as a spatial smoothing operation. In [26], by considering the spherical wavefront, a subspace-based NF localization method is presented for the bistatic system in which the transmitter and receiver are separated by a distance comparable to the target distance. Based on an improved blind calibration algorithm, a NF source localization is proposed in [27].…”

Section: Introductionmentioning

confidence: 99%

“…}, one can reach a different output. In fact, the proper design and selection of the sensors number to calculate the correlation between them is the most important factor in defining a cumulant so that Applicable for the passive scenario, no reflectivity estimates [12] Spatial cumulants (with the aim of separating non-coherent and coherent components) Applicable for the passive scenario, no reflectivity estimates [21] LASSO LASSO cannot be solved efficiently, DOA estimates only [23] Spatial cumulants; ESPRIT-like estimator Applicable for the passive scenario, no reflectivity estimates [24] SOS Applicable for the passive scenario, no reflectivity estimates [22] Spatial/temporal full ESPRIT-like approach Applicable for the passive scenario, no reflectivity estimates [25] 2D-MUSIC processing Very high computational complexity, no reflectivity estimates [26] Cross-covariance matrices between the output data blocks Applicable for the bistatic system, no reflectivity estimates [27] Covariance matrix Iterative approach with high computational cost, applicable for the passive scenario, no reflectivity estimates [ the desired output is obtained and the information is sufficient to the end of the algorithm. For this purpose, a new special cumulant is defined in this paper.…”

Section: Introductionmentioning

confidence: 99%

Efficient Joint Estimation of DOA, Range and Reflectivity in Near-Field by Using Mixed-Order Statistics and a Symmetric MIMO Array

Molaei

Hougne

Fusco

et al. 2022

IEEE Trans. Veh. Technol.

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Most works in the literature on parameter estimation with multiple-input multiple-output (MIMO) systems are limited to estimating only the direction of arrival (DOA), and/or based on the far-field assumption. However, the joint estimation of DOA and range is an important challenge for near-field (NF) applications. In addition, backscatter coefficient estimation, as one of the most important parameters of radar systems, has been neglected in existing works. In this paper, the joint estimation of the DOA, range and reflectivity is presented for a MIMO array in the NF. By employing the symmetry property in the array, first, two special spatial expressions based on fourth-order and second-order statistics from the received data are defined so that the output of the first expression lacks targets' range information. By collecting the information of all the sensors and calculating all the interactions between the transmit and receive sensors based on the first expression, a spatial cumulant matrix is constructed. In two different approaches, with/without the use of eigendecomposition, the virtual steering vectors are extracted. Next, DOAs are estimated by a one-dimensional (1D) spectral search. The second expression, which contains both angle and range information, is used to construct several covariance submatrices and then to construct a covariance matrix with a size corresponding to the array's dimensions. Then, corresponding ranges are estimated by employing estimated DOAs, eigendecomposition and 1D spectral searches. Finally, the equations required to estimate the reflectivity are derived. The simulation results show the remarkable performance of the proposed method in terms of computational time and estimation accuracy.

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Near field targets localization using bistatic MIMO system with spherical wavefront based model

Cited by 13 publications

References 21 publications

A Comprehensive Review of Direction-of-Arrival Estimation and Localization Approaches in Mixed-Field Sources Scenario

A Comprehensive Review of Direction-of-Arrival Estimation and Localization Approaches in Mixed-Field Sources Scenario

The Mitigation of Mutual Coupling Effects in Multi-Beam Echosounder Calibration under Near-Field Conditions

Efficient Joint Estimation of DOA, Range and Reflectivity in Near-Field by Using Mixed-Order Statistics and a Symmetric MIMO Array

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