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Low-Cost, Wideband Ultrasonic Transmitter and Receiver for array signal processing Applications

IEEE SENSORS JOURNAL 2011年第5期11卷 1284-1292页

作者： Hernandez, Juan Ramon Gonzalez Bleakley, Chris J. Univ Coll Dublin Sch Comp Sci & Informat Complex & Adapt Syst Lab Dublin 4 Ireland

This paper presents a low-cost, wideband ultrasonic transmitter for in-air ultrasonic applications based on a conventional narrowband piezoceramic transducer with an L-R circuit modification. An analytic method for calculation of the optimum circuit parameters for bandwidth expansion of the ceramic ultrasonic transmitter is described, together with experimental data proving the viability of the method. A low-cost wideband ultrasonic receiver array is also presented. The results of the first characterization of microelectromechanical systems (MEMS) microphones in the ultrasonic band and their use in a sensor array for ultrasonic array signal processing applications is also presented. The paper presents examples of prototype transducer performance in ultrasonic indoor applications.

关键词： array signal processing microelectromechanical systems (MEMS) piezoelectric ultrasonic

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Digitally Adaptive High-Fidelity Analog array signal processing Resilient to Capacitive Multiplying DAC Inter-Stage Gain Error

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2019年第11期66卷 4095-4107页

作者： Joshi, Siddharth Kim, Chul Thomas, Chris M. Cauwenberghs, Gert Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA Korea Adv Inst Sci & Technol Dept Bio & Brain Engn Daejeon 34131 South Korea Boeing Satellite Syst Seal Beach CA 90740 USA Univ Calif San Diego Dept Bioengn La Jolla CA 92093 USA

This paper studies multi-stage capacitive mixed-signal matrix-vector multiplying digital-to-analog (MDAC) conversion topologies for highly energy-efficient, high-resolution, and high-dimensional MIMO analog processing systems. In order to mitigate nonlinearity due to radix errors and capacitive mismatch encountered in compact low-power MDAC realizations, we introduce stochastic successive approximation, or S(2)A, as an online optimization algorithm for adaptive array analog signal processing amenable to efficient implementation in massively parallel mixed-signal hardware. S(2)A offers a direct alternative to stochastic gradient descent overcoming several of its shortcomings, such as its sensitivity to model error, while improving on the rate and quality of convergence. S(2)A overcomes non-convergence typically encountered with gradient descent for non-convex optimization landscapes induced by a mismatch in capacitive multiplying digital-to-analog converter components when applied to adaptive analog signal processing. Experimental validation of S(2)A in mixed-signal hardware for real-time RF adaptive beamforming demonstrates 65 dB of over-the-air, multipath interferer suppression in fewer than 25 S(2)A iterations.

关键词： signal processing algorithms array signal processing Adaptive arrays Capacitors Adaptive systems Optimization Multiplying digital-to-analog conversion (MDAC) mixed-signal matrix-vector multiplication (MVM) analog signal processing (ASP) multi-input multi-output (MIMO) least-mean-squares (LMS) adaptive filtering non-convex optimization Internet-of-Things (IoT)

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An Overview of Enhanced Massive MIMO With array signal processing Techniques

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IEEE JOURNAL OF SELECTED TOPICS IN signal processing 2019年第5期13卷 886-901页

作者： Wang, Mingjin Gao, Feifei Jin, Shi Lin, Hai Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Tsinghua Univ Inst Artificial Intelligence Beijing 100084 Peoples R China Beijing Natl Res Ctr Informat Sci & Technol BNRis Beijing 100084 Peoples R China Tsinghua Univ Shenzhen Key Lab Digital TV Syst Guangdong Prov & Shenzhen Res Inst Shenzhen 518057 Peoples R China Southeast Univ Natl Commun Res Lab Nanjing 210096 Jiangsu Peoples R China Osaka Prefecture Univ Dept Elect & Informat Syst Grad Sch Engn Sakai Osaka 5998531 Japan

In the past ten years, there have been tremendous research progresses on massive MIMO systems, most of which stand from the communications viewpoint. A new trend to investigate massive MIMO, especially for the sparse scenario like millimeter wave (mmWave) transmission, is to re-build the transceiver design from array signal processing viewpoint that could deeply exploit the half-wavelength array and provide enhanced performances in many aspects. For example, the high dimensional channel could be decomposed into small amount of physical parameters, e.g., angle of arrival (AoA), angle of departure (AoD), multi-path delay, Doppler shift, etc. As a consequence, transceiver techniques like synchronization, channel estimation, beamforming, precoding, multi-user access, etc., can be re-shaped with these physical parameters, as opposed to those designed directly with channel state information (CSI). Interestingly, parameters like AoA/AoD and multi-path delay are frequency insensitive and thus can be used to guide the downlink transmission from uplink training even for FDD systems. Moreover, some phenomena of massive MIMO that were vaguely revealed previously can be better explained now with array signal processing, e.g., the beam squint effect. In all, the target of this paper is to present an overview of recent progress on merging array signal processing into massive MIMO communications as well as its promising future directions.

关键词： Massive MIMO array signal processing mmWave angle-delay-Doppler reciprocity beam squint

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Non-Integer arrays for array signal processing

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IEEE TRANSACTIONS ON signal processing 2022年 70卷 5457-5472页

作者： Kulkarni, Pranav Vaidyanathan, P. P. Calif Inst Technol Caltech Pasadena CA 91125 USA

Linear arrays with sensors at integer locations are widely used in array signal processing. This paper considers arrays where sensor locations can be rational numbers. It is demonstrated that such rational arrays have some important advantages over integer arrays. For example, they offer more flexibility and reduced DOA estimation error when a limited number of sensors are to be distributed in a fixed aperture. Sparse and coprime rational arrays are introduced to achieve this. Extensive Monte-Carlo simulations demonstrate that rational arrays can perform close to CRB even at low SNR and a small number of snapshots compared to the integer arrays. Furthermore, they can resolve the closely spaced sources and provide smaller MSE for almost all two-DOA configurations. Next, if the signals are impinging from a restricted spatial scope, rational arrays can better utilize this information and place sensors over a larger aperture while still maintaining unique identifiability property. Results on steering vector invertibility of general rational arrays and unique identifiability with rational coprime arrays are provided. In order to do this, some rational extensions of integer number theoretic concepts such as greatest common divisor and coprimality are required, which are introduced as well. The theoretical results are further extended to arbitrary arrays where sensor locations may even be irrational.

关键词： Sensor arrays Sensors Direction-of-arrival estimation array signal processing Estimation Multiple signal classification Apertures Rational arrays non-integer arrays identifiability direction of arrival (DOA) estimation MUSIC

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Ambient Interferences Suppressing for In-Situ Radiated Emissions Measurement Based on array signal processing and Adaptive Noise Cancellation

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IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY 2020年第4期62卷 1055-1067页

作者： Zhou, Zhongyuan Li, Peng Sheng, Mingjie Zhou, Qi Hu, Peng Southeast Univ Sch Mech Engn Electromagnet Compatibil Lab Nanjing 211189 Peoples R China

In this article, a method combining array signal processing and adaptive noise cancellation is proposed to suppress the ambient interferences of in-situ measurement. First, the directions of arrival and classes of all signals are obtained by performing blind source separation and sparse reconstruction on the received signals. Then, the received signals are reused to form two different data channels. In both channels, the interferences that are coherent with the radiated signals of the equipment under test and have larger amplitudes are eliminated based on null trap forming, whereas the coherent interferences with smaller amplitudes are ignored after being attenuated. Besides, the other interferences are suppressed by the adaptive noise cancellation based on their correlation in the two channels. For transient signals, overlapping window technique is used to avoid the losses of the spectrums. Each frame of the signals is cyclically extended to provide sufficient points for adaptive noise cancellation. The proposed method achieves the suppression of multisource ambient interferences with fewer array elements. Simulation and experiment results are given to verify the effectiveness and accuracy of the proposed method.

关键词： Adaptive noise cancellation array signal processing direction of arrival (DOA) in-situ measurement radiated emission sparse reconstruction

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UNIFIED ANALYSIS FOR DOA ESTIMATION ALGORITHMS IN array signal-processing

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signal processing 1991年第2期25卷 147-169页

作者： FU, L VACCARO, RJ Department of Electrical Engineering Portland State University Portland OR 97207 USA Department of Electrical Engineering University of Rhode Island Kingston RI 02881 USA

In this paper, a unified statistical performance analysis using perturbation expansions is applied to subspace-based algorithms for direction-of-arrival (DOA) estimation in array signal processing. The analysis assumes that only a finite amount of array data is available at high signal-to-noise ratio. The MUSIC, Min-Norm, State-Space Realization (TAM) and ESPRIT algorithms are analyzed in a common framework. A significant feature of this analysis is that it includes different types of error sources, such as the finite sample effect induced by additive observation noise, the sensor error effect induced by the inaccurate knowledge of sensor response and location, and the effect of a coherent noise field with unknown structure. All of the algorithms considered in this paper are based on a singular value decomposition of a data matrix. A general expression for the perturbation of singular vectors as a function of data matrix perturbations is derived and used to obtain an analytical expression for the mean-squared DOA estimation error in a simple and self-contained fashion. The tractable formulas provide insight into the algorithms. Simulation results verify the analytically predicted performance.

关键词： SINGULAR VALUE DECOMPOSITION array signal processing PERFORMANCE ANALYSIS DIRECTION-OF-ARRIVAL ESTIMATION

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Effects of nonzero bandwidth on direction of arrival estimators in array signal processing

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IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION 1998年第6期145卷 317-324页

作者： Sorelius, J Moses, RL Söderström, T Swindlehurst, AL Uppsala Univ Syst & Control Grp SE-75103 Uppsala Sweden Ohio State Univ Dept Elect Engn Columbus OH 43210 USA Brigham Young Univ Dept Elect & Comp Engn Provo UT 84602 USA

The authors consider the impact of a small but nonzero bandwidth on narrowband direction-of-arrival (DOA) estimation using an array of sensors. They derive expressions for the DBA error for three commonly used array processing algorithms: MUSIC, ESPRIT and weighted subpace fitting (WSF). The err-or expressions are found by a perturbation analysis of these algorithms for small relative bandwidths of the sources. The perturbation-based error predictions are compared to the exact deviation for some special cases of interest.

关键词： perturbation analysis signal processing theory weighted subspace fitting direction-of-arrival estimation array signal processing DOA estimation exact deviation Error analysis in numerical methods MUSIC perturbation-based error predictions error expressions error analysis perturbation techniques direction of arrival estimators small but nonzero bandwidth ESPRIT nonzero bandwidth signal processing and detection

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SENSOR array signal-processing VIA A PROCRUSTES ROTATIONS BASED EIGENANALYSIS OF THE ESPRIT DATA PENCIL

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND signal processing 1989年第6期37卷 832-861页

作者： ZOLTOWSKI, MD STAVRINIDES, D School of Electrical Engineering Purdue University West Lafayette IN USA

The authors propose the procrustes-rotation-based ESPRIT algorithm, PRO-ESPRIT, for estimating characteristic parameters associated with a scene of radiating sources, given data derived from two identical sensor arrays, the X and Y arrays, which are displaced relative to one another. PRO-ESPRIT uses the inherent redundancy built into the ESPRIT array system to compensate for deviations from the ideal array model. This redundancy is manifested by two fundamental properties of the noiseless X and Y data matrices comprising the ESPRIT data pencil: (a) they have the same row space, the signal subspace; and (2) they have the same column space, the source subspace. These properties are utilized by invoking two primary tools: (1) the solution to the procrustes problem for optimally approximating an invariant subspace rotation; and (2) the total-least-squares method for perturbing each of two estimates of a common subspace in a minimal fashion until the two perturbed spaces are the same.< >

关键词： Sensor arrays array signal processing signal processing algorithms Sensor phenomena and characterization Multiple signal classification Least squares methods Parameter estimation Least squares approximation Linear systems Differential equations

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An information theoretic approach to source enumeration in array signal processing

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IEEE TRANSACTIONS ON signal processing 2004年第5期52卷 1171-1178页

作者： Valaee, S Kabal, P Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 2A7 Canada

In this paper, a new information theoretic algorithm is proposed for signal enumeration in array processing. The approach is based on predictive description length (PDL) that is defined as the length of a predictive code for the set of observations. We assume that several models, with each model representing a certain number of sources, gill compete. The PDL criterion is computed for the candidate models and is minimized over all models to select the best model and to determine the number of signals. In the proposed method, the correlation matrix is decomposed into two orthogonal components in the signal and noise subspaces. The maximum likelihood (ML) estimates of the angles-of-arrival are used to find the projection of the sample correlation matrix onto the signal and noise subspaces. The summation of the ML estimates of these matrices is the ML estimate of the correlation matrix. This method can detect both coherent and noncoherent signals. The proposed method can be used online and can be applied to time-varying systems and target tracking.

关键词： adaptive signal detection array signal processing information theoretic signal resolution information theory maximum likelihood detection minimum description length modeling predictive description length signal detection signal resolution stochastic complexity time-varying systems

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Covariance matrix estimation with pipeline structure in array signal processing

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The Journal of China Universities of Posts and Telecommunications 2024年第6期31卷 88-94页

作者： Chen Ligang Cai Weijie Liu Zhihui Dong Tao Zeng Hao School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China Space Star Technology Co. Ltd.Beijing 100095China

Estimating the covariance matrix of the received signal is a vital step in array signal processing. The traditional estimation method is completed generally by offline way after receiving the continuous sampling snapshots, which cannot meet requirements of real-time performance. In this paper, the calculation of covariance matrix is divided into four pipeline operations, which are multiplication, accumulation, subtraction and division, *** new method leverages the parallel computing function of field programmable gate array(FPGA) to calculate the covariance matrix adopting a pipeline estimation method at each time when the array receives a new sampling snapshot. Compared with the traditional method, the new method not only improves the real-time performance, but also reduces the error in calculation caused by the rapid direction of arrival(DOA) change of the interested signal when the target is highly maneuverable.

关键词： array signal processing covariance matrix estimation pipeline real-time performance snapshot

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