Angular Resolution Performance Research Articles

Perspective on active submillimeter electromagnetic wave imaging using CMOS integrated circuits technologies

The performance of CMOS transmitters and receivers operating at the submillimeter electromagnetic wave frequencies have sufficiently improved for use in active transmission and reflection-mode imaging applications that have the potential for broad deployment and utilization. Imaging integrated circuits have the potential to be large in area to support a high number of pixels along with digital backend processing circuits. For high volume imaging applications that may eventually be included in automobiles, smartphones, laptops, tablets, and others, a large manufacturing capacity to support the volume of large area ICs is necessary. For this, the use of CMOS technologies with a much larger manufacturing capacity is favored. It should be possible to improve the performance of CMOS circuits to increase the range, and operation margin and frequency. The electronically steerable submillimeter-wave reflector technology holds the promise for improving the performance and energy efficiency of submillimeter-wave imaging systems by multiple orders of magnitude, and it is a critical research area. Increasing the operating frequency from 430 to 850 GHz using CMOS integrated circuits to improve the angular resolution by 2X at a given form factor (∼0.15° for a reflector diameter of 15 cm) can make the submillimeter-wave imaging competitive to the LIDAR angular-resolution performance, while providing superior capabilities in visually impaired conditions and making the imaging devices more affordable.

Fast Direct Localization for Millimeter Wave MIMO Systems via Deep ADMM Unfolding

Massive arrays deployed in millimeter-wave systems enable high angular resolution performance, which in turn facilitates sub-meter localization services. Albeit suboptimal, up to now the most popular localization approach has been based on a so-called two-step procedure, where triangulation is applied upon aggregation of the angle-of-arrival (AoA) measurements from the collaborative base stations. This is mainly due to the prohibitive computational cost of the existing direct localization approaches in large-scale systems. To address this issue, we propose a deep unfolding based fast direct localization solver. First, the direct localization is formulated as a joint <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$l_{1}$ </tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$l_{2,1}$ </tex-math></inline-formula> norm sparse recovery problem, which is then solved by using alternating direction method of multipliers (ADMM). Next, we develop a deep ADMM unfolding network (DAUN) to learn the ADMM parameter settings from the training data and a position refinement algorithm is proposed for DAUN. Finally, simulation results showcase the superiority of the proposed DAUN over the baseline solvers in terms of better localization accuracy, faster convergence and significantly lower computational complexity.

RFI Localization via Reweighted Nuclear Norm Minimization in Microwave Interferometric Radiometry

Radio frequency interference (RFI) has become an increasing and challenging problem in microwave interferometric radiometry (MIR). Accurate localization of RFI sources is helpful to provide location information for switching off unauthorized transmitters causing RFI and mitigating the impact of these RFI sources. In this article, we propose a new RFI localization method based on reweighted nuclear norm minimization (RNNM). This method exploits the low-rank property of augmented covariance matrix (ACM) collecting visibility samples in MIR and introduces a singular value weighting strategy to consider different contributions of ACM components. First, ACM is constructed from the original covariance matrix of sparse array, which increases the degree of freedom (DOF) for array processing and hence improves the angular resolution performance. Second, we present a fixed point iteration (FPI)-based RNNM Algorithm, named FRA, to achieve low-rank approximation of ACM involving contribution degrees of ACM components. In this way, the ACM components corresponding to RFI signals are retained well and ones corresponding to background noises are suppressed. Third, we use a subspace-based direction-of-arrival (DOA) estimation approach, i.e., MUSIC algorithm, on the weighted completed ACM (WCACM) (obtained by FRA in the second stage) to locate the potential RFI sources. Retrieved results using synthetic data and real soil moisture and ocean salinity (SMOS) satellite data demonstrate that the proposed RNNM-based method not only has the superiority on improved detection performance, especially for identifying weak sources, but also shows better or competitive localization accuracy and angular resolution, compared with the existing commonly used RFI localization methods in MIR.

An overview of massive MIMO localization techniques in wireless cellular networks: Recent advances and outlook

The massive multiple-input-multiple-output (mMIMO) antenna systems are well known for their capability to achieve high spectral efficiency in wireless communication systems thanks to millimeter waves (mmWaves) which allow a large number of antennas to be deployed at the base stations (BSs). Aside from communication-based services, mMIMO BSs are presently being exploited for location estimation of user equipment due to their high angular resolution, low-cost implementation, and excellent performance in the indoor and clutter urban environments where line-of-sight may not be available. Although various mMIMO localization solutions have been proposed, there are still pressing issues yet to be resolved. To this end, this article first provides an overview of recent and relevant state-of-the-art survey papers on localization. Further to this, we provide various foundational background concepts based on the existing localization techniques applicable to mMIMO localization systems. Furthermore, we discuss various methods under each technique and we also identify some critical factors to be considered in a practical radio environment. Based on these techniques, we provide a comprehensive review of recent works on mMIMO localization. Finally, we suggest key research directions to be addressed in the future and also we discuss key enabling technologies that will enhance the performance of localization systems in 6G communication networks.

The Impact of Elevation Sidelobe Contamination on Radar Data Quality for Operational Interpretation

AbstractTo fulfill the evolving observational needs of the National Weather Service (NWS), future weather radar systems will have to meet demanding requirements. Designing such systems will likely involve trade-offs between system cost and operational performance. A potential cost driver for future weather radars that could cause significant data-quality impacts on forecasters is the required angular resolution and sidelobe performance, which are mainly dictated by the antenna radiation pattern. Typical antenna radiation patterns can be characterized by the width of the main lobe and their sidelobe levels, which are traditionally measured across the azimuthal and elevation dimensions. In this work, we study the impact of increasing sidelobe levels on NWS forecasters’ data interpretation during warning operations. The resulting impact model can be used by decision-makers to better understand the cost–benefit trade-offs inherent in any radar system design.

Unitary Matrix Completion-Based DOA Estimation of Noncircular Signals in Nonuniform Noise

In this paper, a novel direction-of-arrival (DOA) estimation algorithm is proposed for noncircular signals with nonuniform noise by using the unitary matrix completion (UMC) technique. First, the proposed method utilizes the noncircular property of signals to design a virtual array for approximately doubling the array aperture. Then, the virtual complex-valued covariance matrix with the unknown nonuniform noise is transformed into the real-valued one by utilizing the unitary transformation to improve the computational efficiency. Next, a novel UMC method is formulated for the DOA estimation to remove the influence of nonuniform noise. Finally, the DOA without the influence of the unknown noncircularity phase is obtained by using the modified estimation of signal parameters via rotational invariance technique (ESPRIT). Especially, for handling the coherent sources, the forward–backward spatial smoothing technique is utilized to reconstruct a full-rank covariance matrix so that the signal subspace and the noise subspace can be correctly separated. Due to utilizing the extended array aperture and the unitary transformation, the proposed method can identify more sources than the number of physical sensors and provides higher angular resolution and better estimation performance. Compared with the existing DOA estimation algorithms for noncircular signals, the proposed one can effectively suppress the influence of the nonuniform noise. The simulation results are provided to verify the effectiveness and superiority of the proposed method.

Experimental determination of the effects of boundary reflection on the angular resolution of microphone arrays

The Rayleigh criterion has long been considered the standard criterion for angular resolution of imaging systems, including microphone arrays. However, advanced beamforming methods have been developed in the past 20 years that have dramatically improved the angular resolution of microphone array systems. In this investigation, the angular resolution performance of three scaled microphone arrays and one alternative array geometry were tested with both approximately free-field and reflective boundary conditions. All of the arrays were subjected to a thorough regimen of testing with broadband acoustic sources. Beamforming analysis was performed with the Delay-and-Sum, TIDY, DAMAS, DAMAS2, and CLEAN-SC algorithms. The Delay-and-Sum algorithm is shown to offer the lowest angular resolution performance because it does not separate the acoustic source map from the point spread function of the array. The DAMAS algorithm offers the greatest angular resolution because it numerically deconvolutes the acoustic source map from the point spread function. However, deconvolution-based algorithms (DAMAS and DAMAS2) were the most negatively affected by boundary reflection effects. The logarithmic spiral array is shown to offer versatile performance across a wide range of frequencies, while an alternative quasi-periodic array yields results that are highly frequency-dependent. It is demonstrated that this is because of gaps in the source-to-element differences coverage, and the gaps in coverage correspond to half-wavelengths of frequency bands with significantly lower angular resolution performance.

LEAP: Looking beyond pixels with continuous-space EstimAtion of Point sources

Context. Two main classes of imaging algorithms have emerged in radio interferometry: the CLEAN algorithm and its multiple variants, and compressed-sensing inspired methods. They are both discrete in nature, and estimate source locations and intensities on a regular grid. For the traditional CLEAN-based imaging pipeline, the resolution power of the tool is limited by the width of the synthesized beam, which is inversely proportional to the largest baseline. The finite rate of innovation (FRI) framework is a robust method to find the locations of point-sources in a continuum without grid imposition. The continuous formulation makes the FRI recovery performance only dependent on the number of measurements and the number of sources in the sky. FRI can theoretically find sources below the perceived tool resolution. To date, FRI had never been tested in the extreme conditions inherent to radio astronomy: weak signal / high noise, huge data sets, large numbers of sources. Aims. The aims were (i) to adapt FRI to radio astronomy, (ii) verify it can recover sources in radio astronomy conditions with more accurate positioning than CLEAN, and possibly resolve some sources that would otherwise be missed, (iii) show that sources can be found using less data than would otherwise be required to find them, and (v) show that FRI does not lead to an augmented rate of false positives. Methods. We implemented a continuous domain sparse reconstruction algorithm in Python. The angular resolution performance of the new algorithm was assessed under simulation, and with visibility measurements from the LOFAR telescope. Existing catalogs were used to confirm the existence of sources. Results. We adapted the FRI framework to radio interferometry, and showed that it is possible to determine accurate off-grid point source locations and their corresponding intensities. In addition, FRI-based sparse reconstruction required less integration time and smaller baselines to reach a comparable reconstruction quality compared to a conventional method. The achieved angular resolution is higher than the perceived instrument resolution, and very close sources can be reliably distinguished. The proposed approach has cubic complexity in the total number (typically around a few thousand) of uniform Fourier data of the sky image estimated from the reconstruction. It is also demonstrated that the method is robust to the presence of extended-sources, and that false-positives can be addressed by choosing an adequate model order to match the noise level.

Two‐stage DOA estimation method for low SNR signals in automotive radars

In this study, the authors propose an effective two-stage direction-of-arrival (DOA) estimation method for low signal-to-noise (SNR) signals in automotive radar systems. When antenna elements in the array receive low SNR signals, the performance of subspace-based DOA estimation algorithms is degraded. Concerning this case, they propose an enhanced DOA estimation method that offers better angular resolution and estimation performance. The authors' proposed method is comprised of two stages. In the first stage, they roughly estimate the DOA using conventional subspace-based DOA estimation algorithms. Thereafter, the fine DOA estimation is performed in the next stage. The fine estimation includes a received signal calibration method using a priori information acquired from the previous stage. From simulation results, in terms of root mean square error and resolution probability, their proposed method exhibits a DOA estimation performance that is superior to that of the conventional method. Moreover, with actual measurement data, they verify that the proposed method can be applied to practical automotive radar systems.

Sparsity-Aware DOA Estimation Scheme for Noncircular Source in MIMO Radar.

In this paper, a novel sparsity-aware direction of arrival (DOA) estimation scheme for a noncircular source is proposed in multiple-input multiple-output (MIMO) radar. In the proposed method, the reduced-dimensional transformation technique is adopted to eliminate the redundant elements. Then, exploiting the noncircularity of signals, a joint sparsity-aware scheme based on the reweighted norm penalty is formulated for DOA estimation, in which the diagonal elements of the weight matrix are the coefficients of the noncircular MUSIC-like (NC MUSIC-like) spectrum. Compared to the existing norm penalty-based methods, the proposed scheme provides higher angular resolution and better DOA estimation performance. Results from numerical experiments are used to show the effectiveness of our proposed method.

Fourth-order cumulants-based sparse representation approach for DOA estimation in MIMO radar with unknown mutual coupling

In this paper, a sparse representation approach based on fourth-order cumulants (FOC) is proposed for direction of arrival (DOA) estimation in monostatic multiple-input multiple-output (MIMO) radar with unknown mutual coupling. For applying the sparse representation theory successfully, exploiting the special banded symmetric Toeplitz structure of mutual coupling matrices (MCM) in both transmit array and receive array, the unknown MCM in received data can be turned into a diagonal one to eliminate the mutual coupling. Then based on the new received data, a reduced dimensional transformation matrix is formulated, and the proposed method further constructs a FOC matrix with special formation, which reduce the computational complexity of sparse signal reconstruction. Finally a reweighted l1-norm constraint minimization sparse representation framework is designed, and the DOAs can be obtained by finding the non-zero rows in the recovered matrix. Owing to utilizing the fourth-order cumulants and reweighted sparse representation framework, compared with ESPRIT-Like, FOC-MUSIC and l1-SVD algorithms, the proposed method performs well in both white and colored Gaussian noise conditions, meanwhile it has higher angular resolution and better angle estimation performance. Simulation results verify the effectiveness and advantages of the proposed method.

European Solar Telescope: Progress status

AbstractIn this paper, the present status of the development of the design of the European Solar Telescope is described. The telescope is devised to have the best possible angular resolution and polarimetric performance, maximizing the throughput of the whole system. To that aim, adaptive optics and multi‐conjugate adaptive optics are integrated in the optical path. The system will have the possibility to correct for the diurnal variation of the distance to the turbulence layers, by using several deformable mirrors, conjugated at different heights. The present optical design of the telescope distributes the optical elements along the optical path in such a way that the instrumental polarization induced by the telescope is minimized and independent of the solar elevation and azimuth. This property represents a large advantage for polarimetric measurements. The ensemble of instruments that are planned is also presented (© 2010 WILEY‐VCH Verlag GmbH &amp; Co. KGaA, Weinheim)

Multidimensional adaptive beamforming for integrated active-passive sonar and medical imaging applications

The present investigation introduces an adaptive beamforming scheme that separates the computationally intensive multidimensional beamforming into two simple modules, which are line and circular array beamformers. This approach minimizes the number of degrees of freedom associated with the adaptation process and provides near instantaneous convergence, which is essential for integrated active-passive sonar and medical ultrasound imaging applications. The proposed adaptive processing concept has been implemented in an integrated active-passive real-time sonar deploying a cylindrical array. Preliminary efforts include also the application of a line array adaptive beamformer in medical ultrasound imaging systems. Real data results from the adaptive and conventional beamforming outputs of the cylindrical array sonar system and the line array of the ultrasound system demonstrate the superior performance of the adaptive beamformer in suppressing the reverberation and cluttering effects in active sonar and medical ultrasound applications. Moreover, for passive sonar applications, the adaptive processing provides substantially improved angular resolution performance as compared with that of the conventional beamformer. Both these two performance improvements for a line and a cylindrical array sonar are of particular importance for mine hunting operations.

Design and modeling of the Hybrid Portable Gamma Camera system

The combination of a mechanically-collimated camera with an electronically-collimated camera offers both the high efficiency and good angular resolution typical in a mechanically-collimated camera for lower energies and the uncoupling of spatial resolution and efficiency provided by an electronically-collimated camera at higher energies. The application is an industrial gamma-ray imaging system with good angular resolution and efficiency over a broad energy range: 50 keV to 3 MeV. The design and performance modeling of the Hybrid Portable Gamma Camera, currently being built, is described here. The optimization of the Anger-logic first detector module in terms of spatial and energy resolution is accomplished using a Monte Carlo optical photon modeling code and Cramer-Rao lower bound calculations. Approximately 6 mm spatial resolution and 7.5% FWHM (statistical contribution only) energy resolution for a 140 keV incident energy are expected for the 100/spl times/100/spl times/10 mm/sup 3/ NaI(Tl) first detector. Analytical calculations of angular resolution components and efficiency for the Hybrid Portable Gamma Camera are compared to Monte Carlo calculations of the same quantities. The expected angular resolution performance for on-axis point sources, a central scattering angle of 30/spl deg/ and a detector separation distance of 35 cm ranges from 3-5/spl deg/ FWHM over the sensitive energy range. Intrinsic efficiency results over the same energy range are also presented.

An adaptive processing structure for integrated active-passive sonars deploying cylindrical arrays

The paper details the development and implementation of an adaptive processing structure for integrated active–passive sonars deploying cylindrical arrays. The main concept includes decomposition of the computationally intensive multidimensional beamformer into two simple modules, which are line and circular array beamformers. Thus, the multidimensional beamforming process can now be divided into coherent subprocesses which lead to efficient implementation in real-time sonar systems. Furthermore, the application of spatial shading to reduce the side-lobe structures can now be easily incorporated. Moreover, the new approach makes the implementation of adaptive schemes in multidimensional sensor arrays practically achievable. The proposed adaptive processing concept has been implemented in an integrated active–passive real-time sonar deploying a cylindrical array. Real data results from the adaptive and conventional beamforming outputs of the cylindrical array sonar system demonstrate the superior performance of the adaptive beamformer in suppressing the reverberation and cluttering effects in active sonar applications. Moreover, for passive sonar applications, the adaptive processing provides substantially improved angular resolution performance as compared with that of the conventional beamformer. Both these two performance improvements for a cylindrical array sonar are of particular importance for mine hunting operations.

Implementation of adaptive beamforming processing schemes in a towed array sonar system

This experimental paper is concerned with the implementation of the minimum variance distortionless response (MVDR) method [IEEE Trans. 57(8), 1408–1418 (1969)] in a towed array sonar system. The paper discusses the issues associated with the implementation of the MVDR in a real time processing system and examines the robustness of the algorithm using a variety of sea trial data. The performance of an algorithm that pre-processes the data before the MVDR algorithm is applied is also discussed and compared with the standard approach. The experimental results obtained suggest that, as expected, the robustness of the MVDR algorithm is the key to its successful implementation in a real time system. When this condition is met, the MVDR has demonstrated the capability to enhance the conventional beamformer by providing improvements in both angular resolution and detection performance. The implementation of the MVDR algorithm in a real time towed array processing system has necessitated the development of

Implementation of a synthetic aperture processing scheme in a towed array sonar system

This experimental paper is concerned with the implementation of a passive synthetic aperture processing scheme in a towed array sonar system. It addresses theoretical and practical concerns, and the experimental results suggest that the concept of a synthetic aperture towed array system complements the conventional beamformer’s processing results. The acoustic synthetic aperture technique, which has been considered in this study, is the ETAM algorithm [i.e., extended towed array measurements, J. Acoust. Soc. Am. 87, 158–171 (1989)]. Theoretical and experimental studies have shown that the above technique compensates the random phase fluctuations in the data that are introduced by the tow path. This results is an effective extension of the physical aperture of a deployed towed array and consequently provides improved angular resolution performance equivalent to a fully populated long array. Also included in this presentation is a discussion of the development of the computing architecture requirements related to this kind of implementation. It is shown that the development of a next generation signal processor (NGSP) by the Defence Research Establishment Atlantic (DREA) overcomes the limitations normally associated with the implementation of nonlinear algorithms into parallel FFT-based vector processors.

Millimeter Wave Interferometry

Millimeter interferometers give high-resolution (few arc sec) information on cool (100-1000 K) matter, which cannot be easily studied by other techniques. The objects include regions of high extinction (Ay ~ 10–200 mag), planetary atmospheres, outflows from forming stars, mass loss from stellar envelopes and molecular clouds in galaxies. The advantages which mm arrays have over cm arrays are the greater number of molecular spectral lines and the larger linewidths, which allow a higher sensitivity for the same angular resolution and system performance. In the continuum mm arrays can observe solar system objects, stellar winds, compact HII regions, galaxies and quasars in thermal and synchrotron emission, and thermal radiation from dust in dense clouds. The main technical challenges are (1) sensitivity, which limits the longest usable antenna spacing, (2) small field of view, and (3) atmospheric effects, which introduce phase noise. For the next 5–10 years, the main arrays will be those of the Berkeley-Illinois-Maryland collaboration, Cal Tech, Nobeyama and IRAM. There are proposals to add more antennas to existing arrays, to build new ones, and to extend their cover to higher frequencies.