scholarly journals Computationally Efficient Sources Location Method for Nested Array via Massive Virtual Difference Co-Array

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1961
Author(s):  
Wei Wu ◽  
Yunfei Wang ◽  
Xiaofei Zhang ◽  
Jianfeng Li
Keyword(s):  
Fourier Transform ◽  
Parametric Method ◽  
Computational Cost ◽  
Dft Method ◽  
Doa Estimation ◽  
Practical Implementation ◽  
Computationally Efficient ◽  
Virtual Sensors ◽  
Phase Rotation ◽  
Array Aperture

In this paper, we derive the discrete Fourier transform (DFT) method for direction of arrival (DOA) estimation by generating the massive virtual difference co-array with the nested array. By contrast with the spatial smoothing (SS) subspace-based methods for nested array, which halve the array aperture, the proposed method can take full advantage of the total array aperture. Since the conventional DFT method is a non-parametric method and is limited by Rayleigh threshold, we perform the phase rotation operation to obtain the fine DOA estimates. Owing to the full utilization of the array aperture and phase rotation operation, the proposed method can achieve better performance than SS subspace-based methods for far-field sources especially with massive virtual difference co-arrays which possess a large number of virtual sensors. Besides, as the fast Fourier transform (FFT) is attractive in practical implementation, the proposed method lowers the computational cost, as compared with the subspace-based methods. Numerical simulation results validate the superiority of the proposed method in both estimation performance and complexity.

scholarly journals Three-Dimensional Coprime Array for Massive MIMO: Array Configuration Design and 2D DOA Estimation

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Pan Gong ◽  
Tanveer Ahmed ◽  
Jianfeng Li
Keyword(s):  
Computational Complexity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Three Dimensional ◽  
Doa Estimation ◽  
Configuration Design ◽  
Computationally Efficient ◽  
Estimation Performance ◽  
2D Doa Estimation ◽  
Array Aperture

In massive multiple-input multiple-output (MIMO) systems, it is critical to obtain the accurate direction of arrival (DOA) estimation. Conventional three-dimensional array mainly focuses on the uniform array. Due to the dense arrangement of the sensors, the array aperture is limited and severe mutual coupling effects arise. In this paper, a coprime cubic array (CCA) configuration design is presented, which is composed of two uniform cubic subarrays and can extend the interelement spacing with a selection of three pairs of coprime integers. Compared with uniform cubic array (UCA), CCA achieves the larger array aperture and less MC effects. And the analytical expression of Cramer–Rao Bound (CRB) for CCA is derived which verifies that the proposed CCA geometry outperforms the conventional UCA in two-dimensional (2D) DOA estimation performance in massive MIMO systems. Meanwhile, we propose a computationally efficient 2D DOA estimation algorithm with high accuracy for CCA. Specifically, we utilize array mapping to extract two uniform arrays from the nonuniform array by exploiting the relation derived from the signal subspace and the two directional matrices. Then, we operate a reduced dimension process on the uniform arrays and convert the 2D spectrum peak searching (SPS) problem into one-dimensional (1D) one, which significantly reduces the computational complexity. In addition, we employ the polynomial root finding technique with a lower complexity instead of 1D SPS to further relieve the computational complexity. Simultaneously, with coprime property, the phase ambiguity problem is solved, which results from the large interelement spacing. Numerical simulation results demonstrate that the proposed algorithm is very computationally efficient without degradation of DOA estimation performance.

Wavefield interpolation in the Fourier wavefield extrapolation

Geophysics ◽  
2004 ◽  
Vol 69 (1) ◽  
pp. 257-264 ◽  
Author(s):  
Li‐Yun Fu
Keyword(s):  
Fourier Transform ◽  
Computational Cost ◽  
Practical Implementation ◽  
Seismic Migration ◽  
Practical Applications ◽  
Depth Migration ◽  
Thick Slab ◽  
Frequency Components ◽  
The Fourier Transform ◽  
Wavefield Extrapolation

The computational cost for seismic migration relies heavily on the methods used for wavefield extrapolation. In general, seismic migration by current industry techniques extrapolates wavefields through a thick slab and then interpolates wavefields in small layers inside the slab. In this paper, I first optimize practical implementation of the Fourier wavefield extrapolation. I then design three interpolation algorithms: Fourier transform, Kirchhoff, and Born‐Kirchhoff for mild, moderate, and large to strong lateral heterogeneities, respectively. The Fourier transform interpolation simultaneously implements wavefield interpolation and imaging without needing to invoke the imaging principle by summing over all frequency components of the interpolated wavefield. The Kirchhoff interpolation is based on the traditional Kirchhoff migration formula and is performed by diffraction summation with a very limited aperture using the average velocity of a laterally heterogeneous slab. The Born‐Kirchhoff interpolation is based on the Lippmann‐Schwinger integral equation. It differs from the Kirchhoff interpolation in that it accounts not only for the obliquity, spherical spreading, and wavelet shaping factors but also for the relative slowness perturbation in a laterally heterogeneous slab. Recursive seismic migration usually accounts for a 20‐ to 40‐ms depth size for wavefield extrapolation in practical applications. Using the above interpolation techniques, Fourier depth migration methods are shown to tolerate a 40‐ to 60‐ms depth size with the SEG/EAGE salt model. Therefore, the Fourier depth migration techniques with thick‐slab extrapolation plus thin‐slab interpolation can be used to image structures with salt‐related complexes.

scholarly journals Compressed pseudo-SLAM: pseudorange-integrated compressed simultaneous localisation and mapping for unmanned aerial vehicle navigation

2021 ◽  
pp. 1-13
Author(s):  
Jonghyuk Kim ◽  
Jose Guivant ◽  
Martin L. Sollie ◽  
Torleiv H. Bryne ◽  
Tor Arne Johansen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Computational Cost ◽  
Satellite System ◽  
Measurement Unit ◽  
Electronic Systems ◽  
Computationally Efficient ◽  
Global Correlation ◽  
Aerial Vehicle ◽  
Correlation Information ◽  
Global Navigation Satellite

Abstract This paper addresses the fusion of the pseudorange/pseudorange rate observations from the global navigation satellite system and the inertial–visual simultaneous localisation and mapping (SLAM) to achieve reliable navigation of unmanned aerial vehicles. This work extends the previous work on a simulation-based study [Kim et al. (2017). Compressed fusion of GNSS and inertial navigation with simultaneous localisation and mapping. IEEE Aerospace and Electronic Systems Magazine, 32(8), 22–36] to a real-flight dataset collected from a fixed-wing unmanned aerial vehicle platform. The dataset consists of measurements from visual landmarks, an inertial measurement unit, and pseudorange and pseudorange rates. We propose a novel all-source navigation filter, termed a compressed pseudo-SLAM, which can seamlessly integrate all available information in a computationally efficient way. In this framework, a local map is dynamically defined around the vehicle, updating the vehicle and local landmark states within the region. A global map includes the rest of the landmarks and is updated at a much lower rate by accumulating (or compressing) the local-to-global correlation information within the filter. It will show that the horizontal navigation error is effectively constrained with one satellite vehicle and one landmark observation. The computational cost will be analysed, demonstrating the efficiency of the method.

Hybrid LES Approach for Practical Turbomachinery Flows—Part I: Hierarchy and Example Simulations

2011 ◽  
Vol 134 (2) ◽  
Author(s):  
Paul Tucker ◽  
Simon Eastwood ◽  
Christian Klostermeier ◽  
Richard Jefferson-Loveday ◽  
James Tyacke ◽  
...  
Keyword(s):  
Convex Surface ◽  
Computational Cost ◽  
Companion Paper ◽  
Navier Stokes ◽  
Computationally Efficient ◽  
Turbulent Structures ◽  
Hybrid Strategy ◽  
Eddy Simulation ◽  
Related Approach ◽  
Les Model

Unlike Reynolds-averaged Navier–Stokes (RANS) models that need calibration for different flow classes, LES (where larger turbulent structures are resolved by the grid and smaller modeled in a fashion reminiscent of RANS) offers the opportunity to resolve geometry dependent turbulence as found in complex internal flows—albeit at substantially higher computational cost. Based on the results for a broad range of studies involving different numerical schemes, large eddy simulation (LES) models and grid topologies, an LES hierarchy and hybrid LES related approach is proposed. With the latter, away from walls, no LES model is used, giving what can be termed numerical LES (NLES). This is relatively computationally efficient and makes use of the dissipation present in practical industrial computational fluid dynamics (CFD) programs. Near walls, RANS modeling is used to cover over numerous small structures, the LES resolution of which is generally intractable with current computational power. The linking of the RANS and NLES zones through a Hamilton–Jacobi equation is advocated. The RANS-NLES hybridization makes further sense for compressible flow solvers, where, as the Mach number tends to zero at walls, excessive dissipation can occur. The hybrid strategy is used to predict flow over a rib roughened surface and a jet impinging on a convex surface. These cases are important for blade cooling and show encouraging results. Further results are presented in a companion paper.

An Efficient Preconditioner for Linear System Solution in Multi-Domain Modeling of the Circulatory System

2013 ◽  
Author(s):  
Mahdi Esmaily Moghadam ◽  
Yuri Bazilevs ◽  
Tain-Yen Hsia ◽  
Alison Marsden
Keyword(s):  
Strong Coupling ◽  
Large Scale ◽  
Computational Cost ◽  
Circulatory System ◽  
Flow Simulation ◽  
Global Dynamics ◽  
Domain Modeling ◽  
Computationally Efficient ◽  
Lumped Parameter ◽  
System Solution

A closed-loop lumped parameter network (LPN) coupled to a 3D domain is a powerful tool that can be used to model the global dynamics of the circulatory system. Coupling a 0D LPN to a 3D CFD domain is a numerically challenging problem, often associated with instabilities, extra computational cost, and loss of modularity. A computationally efficient finite element framework has been recently proposed that achieves numerical stability without sacrificing modularity [1]. This type of coupling introduces new challenges in the linear algebraic equation solver (LS), producing an strong coupling between flow and pressure that leads to an ill-conditioned tangent matrix. In this paper we exploit this strong coupling to obtain a novel and efficient algorithm for the linear solver (LS). We illustrate the efficiency of this method on several large-scale cardiovascular blood flow simulation problems.

A Computationally Efficient Predictive Controller for Lane Keeping of Semi-Autonomous Vehicles

2014 ◽  
Author(s):  
Changchun Liu ◽  
Chankyu Lee ◽  
Andreas Hansen ◽  
J. Karl Hedrick ◽  
Jieyun Ding
Keyword(s):  
Autonomous Vehicles ◽  
Piecewise Linear ◽  
Computational Cost ◽  
Parametric Programming ◽  
Linear Feedback ◽  
Loop Model ◽  
Computationally Efficient ◽  
Feedback Function ◽  
Predictive Controller ◽  
Lane Keeping

Model predictive control (MPC) is a popular technique for the development of active safety systems. However, its high computational cost prevents it from being implemented on lower-cost hardware. This paper presents a computationally efficient predictive controller for lane keeping assistance systems. The controller shares control with the driver, and applies a correction steering when there is a potential lane departure. Using the explicit feedback MPC, a multi-parametric nonlinear programming problem with a human-in-the-loop model and safety constraints is formulated. The cost function is chosen as the difference between the linear state feedback function to be determined and the resultant optimal control sequence of the MPC problem solved off-line given the current state. The piecewise linear feedback function is obtained by solving the parametric programming with an approximation approach. The effectiveness of the controller is evaluated through numerical simulations.

scholarly journals Multi-Frequency Based Direction-of-Arrival Estimation for 2q-Level Nested Radar & Sonar Arrays

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3385 ◽  
Author(s):  
Hao Zhou ◽  
Guoping Hu ◽  
Junpeng Shi ◽  
Ziang Feng
Keyword(s):  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Research Area ◽  
Frequency Separation ◽  
Frequency Method ◽  
Virtual Sensors ◽  
Order Difference ◽  
Sonar Systems ◽  
Minimum Number

Direction finding is a hot research area in radar and sonar systems. In the case of q ≥ 2, the 2qth-order cumulant based direction of arrival (DOA) estimation algorithm for the 2q-level nested array can achieve high resolution performance. A virtual 2qth-order difference co-array, which contains O(N2q) virtual sensors in the form of a uniform linear array (ULA), is yielded and the Gaussian noise is eliminated. However, some virtual elements are separated by the holes among the 2qth-order difference co-array and cannot be fully used. Even though the application of the multi-frequency method for minimum frequency separation (MFMFS) can fill the holes with low computation complexity, it requires that the number of frequencies must increase with the number of holes. In addition, the signal spectra have to be proportional for all frequencies, which is hard to satisfy when the number of holes is large. Aiming at this, we further propose a multi-frequency method for a minimum number of frequencies (MFMNF) and discuss the best frequency choice under two specific situations. Simulation results verify that, compared with the MFMFS method, the proposed MFMNF method can use only one frequency to fill all the holes while achieving a longer virtual array and the DOA estimation performance is, therefore, improved.

scholarly journals Direction-of-Arrival Estimation of Closely Spaced Emitters Using Compact Arrays

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Hoi-Shun Lui ◽  
Hon Tat Hui
Keyword(s):  
Performance Evaluation ◽  
Matrix Pencil ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Antenna Element ◽  
Portable Devices ◽  
Estimation Algorithms ◽  
Half Wavelength ◽  
Matrix Pencil Method ◽  
Array Aperture

Performance evaluation of direction-of-arrival (DOA) estimation algorithms has continuously drawn significant attention in the past years. Most previous studies were conducted under the situation that antenna element separation is about half wavelength in order to avoid the appearance of grating lobes. On the other hand, recent developments in wireless communications have favoured the use of portable devices that utilize compact arrays with antenna element separations of less than half wavelength. Performance evaluation of DOA estimation algorithms employing compact arrays is an important and fundamental issue, but it has not been fully studied. In this paper, the performance of the matrix pencil method (MPM) that applies to DOA estimations is investigated through Monte Carlo simulations. The results show that closely spaced emitters can be accurately resolved using linear compact array with an array aperture as small as around half wavelength.

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