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Gradient-Based Optimization of Coherent distributed arrays

IEEE SENSORS JOURNAL 2025年第4期25卷 7417-7430页

作者： Lipski, Michael V. Kompella, Sastry Narayanan, Ram M. US Naval Res Lab Washington DC 20375 USA Nexcepta Inc Gaithersburg MD 20878 USA Penn State Univ Sch Elect Engn & Comp Sci State Coll PA 16802 USA

In a coherent communication system consisting of an open-loop distributed transmit array sending messages to a distributed receive array, the combined transmit-receive gain is characterized by the coherent communication gain (CCG). We consider the problem of optimizing CCG using the positions of the individual transmitter and receiver nodes as well as the beam angle of the transmit array as degrees of freedom. We focus on the use of gradient descent to find locally optimal configurations for node positions, which is motivated by two observations: first, the NP-hardness of the problem precludes an exhaustive search for the globally optimal configuration of node positions;and second, the positions of the network nodes are likely not arbitrary. That is, the initial, nonoptimized node placement is intentional and is determined by higher-layer network objectives. The hypothesis is that the CCG of a communication network can be improved in a deterministic fashion using the steepest descent algorithm to make relatively small adjustments to node positions. We develop the closed-form expressions for the rate of change of CCG with respect to node positions and transmit array beam angle. Next, we use the expressions to implement a spherical quadratic steepest descent (SQSD) algorithm and use simulations to test SQSD alongside pattern search and particle swarm optimization to determine theoretical gain improvements achieved by the algorithms, as well as the expected average node displacement.

关键词： Gain Receivers Array signal processing Transmitters Synchronization Wireless sensor networks Optimization Sensor arrays Sensors Collaboration Coherent arrays collaborative beamforming distributed arrays mobile ad hoc network (MANET) optimization wireless sensor network (WSN)

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Direct localization of wideband sources using distributed arrays: A subspace focusing and dimension reduction approach

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SIGNAL PROCESSING 2025年 232卷

作者： Li, Dawei Li, Jianfeng You, Mingyi Tang, Wanghao Zhang, Xiaofei Qin, Wutao Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Dynam Cognit Syst Electromagnet Spectrum Minist Ind & Informat Technol Nanjing 211106 Peoples R China NO36 Res Inst CETC Jiaxing 314000 Peoples R China Natl Key Lab Electromagnet Space Secur Jiaxing 314000 Peoples R China Purple Mt Lab Nanjing 211111 Peoples R China

To enhance the localization performance of wideband sources with distributed arrays, this paper proposes a subspace focusing and dimension reduction approach. Firstly, the received sensor data are subjected to data segmentation and frequency domain transformation, and the processed data are fused into a dataset. Then, utilizing the subspace focusing algorithm, a focusing matrix is constructed to concentrate the data from each frequency point onto the reference frequency point, which can solve the problem of rank deficient covariance matrix caused by signal coherence. Thereafter, the cost function is established by utilizing the subspace orthogonality, and dimensionality reduction is employed to avoid the problem of unknown attenuation coefficients. Finally, the estimated position of the wideband sources are obtained by searching for the spectral peaks of the cost function. Simulation results show the effectiveness of the proposed method, whose positioning performance is improved compared to other algorithms.

关键词： Direct localization distributed arrays Wideband sources Subspace focusing Data fusion

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Spotforming: Spatial Filtering With distributed arrays for Position-Selective Sound Acquisition

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2016年第7期24卷 1291-1304页

作者： Taseska, Maja Habets, Emanuel A. P. Univ Erlangen Nurnberg Int Audio Labs Erlangen D-91058 Erlangen Germany Fraunhofer IIS D-91058 Erlangen Germany

Hands-free capture of speech often requires extraction of sources from a certain spot of interest (SOI), while reducing interferers and background noise. Although state-of-theart spatial filters are fully data-dependent and computed using the power spectral density (PSD) matrices of the desired and the undesired signals, the existing solutions to extract sources from a SOI are only partially data-dependent. Estimating the timevarying PSD matrices from the data is a challenging problem, especially in dynamic and quickly time-varying acoustic scenes. Hence, the spot signal statistics are often pre-computed based on a near-field propagation model, resulting in suboptimal filters. In this work, we propose a fully data-dependent spatial filtering framework for extraction of speech signals that originate from a SOI. To achieve position-based spatial selectivity, distributed arrays are used, which offer larger spatial diversity compared to arrays of closely spaced microphones. The PSD matrices of the desired and the undesired signals are updated at each time-frequency bin by using a minimum Bayes risk detector that is based on a probabilistic model of narrowband position estimates. The proposed framework is applicable in challenging multitalk situations, without requiring any prior information, except the geometry, location, and orientation of the arrays.

关键词： Source extraction distributed arrays spatial filtering PSD matrix estimation signal detection

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Open-Loop Coherent distributed arrays

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IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2017年第5期65卷 1662-1672页

作者： Nanzer, Jeffrey A. Schmid, Robert L. Comberiate, Thomas M. Hodkin, Jason E. Michigan State Univ Elect & Comp Engn Dept E Lansing MI 48824 USA Johns Hopkins Univ Appl Phys Lab Laurel MD 20723 USA

The ability to cohere the wireless operations between separate, moving microwave systems enables significant increases in capability for remote sensing, radar, communications, and other microwave wireless applications. Open-loop coherent distributed arrays, which are distributed systems of nodes that coherently coordinate without external signal inputs from the destination, are introduced in this paper. A model of the signal received from a coherent distributed array is derived, and a statistical analysis of the variation in signal power in the presence of coordination errors is presented. Requirements on the tolerable errors for internode range measurement, beamsteering angle measurement, and internode clock phase synchronization are given as a function of the probability of achieving a given signal power. Approaches for achieving the necessary internode range and angle measurements are presented, and the experimental results of a novel one-way clock transfer approach to phase synchronization are shown. These examples demonstrate the feasibility of implementing coherent distributed arrays on moving platforms operating at frequencies extending into the microwave region.

关键词： Coherent distributed arrays coherent distributed radio frequency (RF) systems coherent RF networks distributed arrays distributed transmit beamforming

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An implementation framework for HPF distributed arrays on message-passing parallel computer systems

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 1996年第9期7卷 897-914页

作者： vanReeuwijk, K Denissen, W Sips, HJ Paalvast, EMRM TNO TPD NL-2600 DELFT NETHERLANDS

Data parallel languages, like High Performance Fortran (HPF), support the notion of distributed arrays. However, the implementation of such distributed array structures and their access on message passing computers is not straightforward. This holds especially for distributed arrays that are aligned to each other and given a block-cyclic distribution. In this paper, an implementation framework is presented for HPF distributed arrays on message passing computers. Methods are presented for efficient (in space and time) local index enumeration, local storage, and communication. Techniques for local set enumeration provide the basis for constructing local iteration sets and communication sets. It is shown that both local set enumeration and local storage schemes can be derived from the same equation. Local set enumeration and local storage schemes are shown to be orthogonal, i.e., they can be freely combined. Moreover, for linear access sequences generated by our enumeration methods, the local address calculations can be moved out of the enumeration loop, yielding efficient local memory address generation. The local set enumeration methods are implemented by using a relatively simple general transformation rule for absorbing ownership tests. This transformation rule can be repeatedly applied to absorb multiple ownership tests. Performance figures are presented for local iteration overhead, a simple communication pattern, and storage efficiency.

关键词： HPF message passing message aggregation distributed arrays parallel computers

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Nearfield spot-beamforming with distributed arrays

Nearfield spot-beamforming with distributed arrays

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1st IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2000)

作者： Flaig, A Arce, GR Univ Delaware Newark DE 19716 USA

ISBN: (纸本)0780363396

The concept of spot-beamforming with distributed arrays (DAs) is introduced. DAs are array-source configurations whose array elements are spatially dispersed submerging the sources in the nearfield of the array, where they can be distinguished not only by their angular but also by their range signature. The resulting enhanced spatial discrimination capabilities reflected in a beampattern characterized by spot-like mainlobes lend DAs optimality properties. A gradient based algorithm for the joint optimization of the array geometry and the shading coefficients of a narrowband spot-beamformer in a stationary multiple source system is derived, and its convergence and performance are discussed. An important subclass of DAs, namely distributed linear arrays are introduced. This class is of practical significance and has the important property of being ambiguity-free in the limit for high SNR. For DAs with an arbitrary geometry, which can suffer from spatial aliasing, a set description of the ambiguities is given.

关键词： near-field spot-beamforming distributed arrays optimal array geometries gain resolution ambiguity

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SPEECH ENHANCEMENT WITH A LOW-COMPLEXITY ONLINE SOURCE NUMBER ESTIMATOR USING distributed arrays 22

SPEECH ENHANCEMENT WITH A LOW-COMPLEXITY ONLINE SOURCE NUMBE...

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22nd European Signal Processing Conference (EUSIPCO)

作者： Taseska, Maja Khan, Affan Hasan Habets, Emanuel A. P. Int Audio Labs Erlangen Wolfsmantel 33 D-91058 Erlangen Germany

ISBN: (纸本)9780992862619

Enhancement of a desired speech signal in the presence of background noise and interferers is required in various modern communication systems. Existing multichannel techniques often require that the number of sources and their locations are known in advance, which makes them inapplicable in many practical situations. We propose a framework which uses the microphones of distributed arrays to enhance a desired speech signal by reducing background noise and an initially unknown number of interferers. The desired signal is extracted by a minimum variance distortionless response filter in dynamic scenarios where the number of active interferers is time-varying. An efficient, geometry-based approach that estimates the number of active interferers and their locations online is proposed. The overall performance is compared to the one of a geometry-based probabilistic framework for source extraction, recently proposed by the authors.

关键词： Source extraction PSD matrix estimation distributed arrays number of sources

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SPATIAL COHERENCE MODEL FOR PASSIVE RANGING USING distributed arrays

SPATIAL COHERENCE MODEL FOR PASSIVE RANGING USING DISTRIBUTE...

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46th Asilomar Conference on Signals, Systems and Computers

作者： Ge, Hongya Kirsteins, Ivars P. New Jersey Inst Technol Dept ECE Newark NJ 07102 USA Naval Undersea Wafare Ctr Newport RI 02841 USA

ISBN: (纸本)9781467350518

This work presents our data analysis results on modeling spatial coherence in a distributed passive array ranging system consisting of three volumetric module arrays. We show that a simple analytical approximation that was previously derived for modeling signal spatial coherence losses in wireless system which represented the random medium effects by a random scatter field can accurately model the spatial coherence losses measured in actual underwater acoustic data. We also discuss its implications in wavefront curvature range estimation.

关键词： Spatial Coherence distributed arrays Passive Source Localization

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Source separation and localisation via tensor decomposition for distributed arrays

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JOURNAL OF ENGINEERING-JOE 2019年第20期2019卷 6616-6619页

作者： Cheng, Yuanbing He, Yapeng Nanjing Res Inst Elect Technol Nanjing Jiangsu Peoples R China China Acad Space Technol Xian Branch Xian Shaanxi Peoples R China

This study focuses on the problem of power spectra separation and localisation of multiple sources using distributed arrays. First, the array structure and signal model are discussed. By cross-correlating the multi-channel received signals in timedomain, a third tensor is constructed. Then, utilising the multi-dimensional characteristic, the tensor is decomposed to separate the array manifold matrix and the power spectra matrix through alternating least square (ALS) method. Finally, the sources are located using the relative x-y plane relationship between the distributed arrays and the direction of arrival (DOA), which can be estimated by spectrum analysis of each column of the array manifold matrix. The effectiveness and superiority of the proposed method is demonstrated by simulation results.

关键词： array signal processing matrix algebra direction-of-arrival estimation tensors spectral analysis least squares approximations correlation methods source separation multidimensional signal processing tensor decomposition distributed arrays power spectra separation array structure signal model multichannel received signals array manifold matrix power spectra matrix multidimensional characteristics source separation source localisation cross-correlation alternating least square method ALS method direction of arrival DOA spectrum analysis

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Informed Spatial Filtering for Sound Extraction Using distributed Microphone arrays

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2014年第7期22卷 1195-1207页

作者： Taseska, Maja Habets, Emanuel A. P. Univ Erlangen Nurnberg Int Audio Labs Erlangen D-91058 Erlangen Germany Int Audio Labs Erlangen D-91058 Erlangen Germany

Hands-free acquisition of speech is required in many human-machine interfaces and communication systems. The signals received by integrated microphones contain a desired speech signal, spatially coherent interfering signals, and background noise. In order to enhance the desired speech signal, state-of-the-art techniques apply data-dependent spatial filters which require the second order statistics (SOS) of the desired signal, the interfering signals and the background noise. As the number of sources and the reverberation time increase, the estimation accuracy of the SOS deteriorates, often resulting in insufficient noise and interference reduction. In this paper, a signal extraction framework with distributed microphone arrays is developed. An expectation maximization (EM)-based algorithm detects the number of coherent speech sources and estimates source clusters using time-frequency (TF) bin-wise position estimates. Subsequently, the second order statistics (SOS) are estimated using bin-wise speech presence probability (SPP) and a source probability for each source. Finally, a desired source is extracted using a minimum variance distortionless response (MVDR) filter, a multichannel Wiener filter (MWF) and a parametric multichannel Wiener filter (PMWF). The same framework can be employed for source separation, where a spatial filter is computed for each source considering the remaining sources as interferers. Evaluation using simulated and measured data demonstrates the effectiveness of the framework in estimating the number of sources, clustering, signal enhancement, and source separation.

关键词： distributed arrays EM algorithm PSD matrix estimation source extraction spatial filtering

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