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IEEE 7th sensor array and multichannel signal processing workshop (SAM)

作者： Pavlidi, Despoina Griffin, Anthony Puigt, Matthieu Mouchtaris, Athanasios FORTH ICS GR-70013 Iraklion Crete Greece

ISBN: (纸本)9781467310710

Recently, we proposed an approach inspired by Sparse Component Analysis for real-time localization of multiple sound sources using a circular microphone array. The method was based on identifying time-frequency zones where only one source is active, reducing the problem to single-source localization for these zones. A histogram of estimated Directions of Arrival (DOAs) was formed and then processed to obtain improved DOA estimates, assuming that the number of sources was known. In this paper, we extend our previous work by proposing three different methods for counting the number of sources by looking for prominent peaks in the derived histogram based on: (a) performing a peak search, (b) processing an LPC-smoothed version of the histogram, (c) employing a matching pursuit-based approach. The third approach is shown to perform very accurately in simulated reverberant conditions and additive noise, and its computational requirements are very small.

关键词： Additive noise

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Enhanced DOA Estimation Exploiting Multi-Frequency Sparse array

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IEEE TRANSACTIONS ON signal processing 2021年 69卷 5935-5946页

作者： Zhang, Shuimei Ahmed, Ammar Zhang, Yimin D. Sun, Shunqiao Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA Univ Alabama Dept Elect & Comp Engn Tuscaloosa AL 35487 USA

In this paper, we develop a general framework of multi-frequency sparse array to estimate the direction-of-arrival (DOA) of a significantly higher number of targets than the number of physical sensors. The multi-frequency sparse arrays are designed to offer zero lag redundancy in the rendered difference coarray so that the available degrees of freedom are fully utilized to enable high-resolution DOA estimation. A modified sensor interpolation technique is developed to accurately estimate the signal correlation matrix so that the effect of holes in the difference coarray is mitigated. The proposed technique accounts for both self-lags between signals corresponding to the same frequencies and the cross-lags between signals corresponding to different frequencies. As such, it enhances the DOA estimation performance compared to existing methods that either perform array interpolation utilizing only the self-lags or carry out group sparse reconstruction without exploiting array interpolation. Simulation results verify the offerings of the multi-frequency sparse arrays.

关键词： sensor arrays array signal processing Estimation Direction-of-arrival estimation Correlation Sparse matrices Redundancy array interpolation direction-of-arrival estimation multi-frequency sparse array zero lag redundancy group sparsity

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A GNSS Structural Interference Mitigation Technique Using Antenna array processing

A GNSS Structural Interference Mitigation Technique Using An...

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8th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Daneshmand, Saeed Jafarnia-Jahromi, Ali Broumandan, Ali Lachapelle, Gerard Univ Calgary Schulich Sch Engn Posit Locat & Nav PLAN Grp Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781479914814

Position solutions provided by Global Navigation Satellite Systems (GNSS) can be completely misled by structural interference or spoofing threats. An approach utilizing an antenna array is proposed in order to suppress spoofing attacks. The proposed method is based on the assumption that all spoofing signals are transmitted from a single point source. A spatial domain processing technique is proposed to extract the spoofing signal steering vector and consequently to discard the spoofing signals. This method is implemented before despreading and acquisition stage of a GNSS receiver. Hence, it does not impose a heavy computational load on the receiver operational process since it does not require any extensive search in the code and Doppler domains to separately despread individual authentic and spoofing signals. Moreover, the proposed method does not require any antenna array calibration process. This pre-despreading interference mitigation technique is further extended to maximize signal-to-noise ratio (SNR) of each individual authentic GNSS signal. Simulation results show that the proposed method effectively countermeasures spoofing attacks for a wide range of received spoofing power.

关键词： Spoofing disturbance suppression computer information security Antenna arrays Global Navigation Satellite System array processing signal to noise ratios

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A Variational Bayesian Approach to Direction Finding of Correlated Targets Using Coprime array 11

A Variational Bayesian Approach to Direction Finding of Corr...

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IEEE 11th sensor array and multichannel signal processing workshop (SAM)

作者： Yang, Jie Yang, Yixin Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Shaanxi Peoples R China

ISBN: (纸本)9781728119465

In this paper, we develop a sparsity-aware algorithm for direction-of-arrival (DOA) estimation of correlated targets in the context of coprime array processing. The idea is to iteratively interpolate the observed data to a virtual nonuniform linear array (NLA) in order to raise the degrees of freedom (DOF). We derive the estimation procedures using variational inference for fully Bayesian estimation, where the current parameter estimates are used to interpolate the observed data better and thus increase the likelihood of the next parameter estimates. The novelties of our method lies in its capacity of detecting more correlated sources than the number of physical sensors. Simulated data from coprime arrays are used to illustrate the superior performance of the proposed approach as compared with other state-of-the-art compressed sensing reconstruction algorithms.

关键词： Direction-of-arrival (DOA) estimation Coprime array Degrees of freedom (DOF) Variational inference

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Sound Source Localization for Hearing Aid Applications using Wireless Microphones 10

Sound Source Localization for Hearing Aid Applications using...

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10th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Farmani, Mojtaba Pedersen, Michael Syskind Jensen, Jesper Oticon AS Smorum Denmark Aalborg Univ Dept Elect Syst Aalborg Denmark

ISBN: (纸本)9781538647523

State-of-the-art hearing aids (HAs) can connect to a wireless microphone worn by a talker of interest. This ability allows HAs to have access to almost noise-free sound signals of the target talker. In this paper, we aim to estimate the direction of arrival (DoA) of the target signal, given access to the noise-free target signal. Knowing the DoA of the target signal enables HAs to spatialize the wirelessly received target signals. The proposed estimator is based on a maximum likelihood (ML) approach and a database of DoA-dependent relative transfer functions (RTFs), and it supports both monaural and binaural microphone array configurations. For binaural configurations, we propose an information fusion strategy, which decreases the number of parameters required to be wirelessly transferred between the HAs. Further, we show that the proposed method not only has lower computational complexity, but also performs better than recent DoA estimators, which have access to the noise-free target signal.

关键词： Microphones Direction-of-arrival estimation Wireless communication Maximum likelihood estimation Databases Wireless sensor networks"

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Optimal Virtual array Length Under Position Imperfections

Optimal Virtual Array Length Under Position Imperfections

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8th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Mannesson, Anders Bernhardsson, Bo Yaqoob, Muhammad Atif Tufvesson, Fredrik Lund Univ Dept Automat Control S-22100 Lund Sweden Lund Univ Dept Elect & Informat Technol S-22100 Lund Sweden

ISBN: (纸本)9781479914814

This article contains a study of how spatial errors and receiver imperfections affect the angle of arrival estimation accuracy for virtual antenna arrays. A virtual antenna array consists of one receiver element whose location is tracked as the element is moved and in this work, linear arrays are studied. If the location of the receiver is tracked using an inertial measurement unit, an interesting trade-off emerges. The array should extend as far as possible but since the position estimates from the unaided inertial measurement unit become increasingly uncertain over time, the angle of arrival estimation will deteriorate. Several algorithms are available for estimating the angle of arrival in such a scenario but the one used for evaluation here is a sparse enforcing least squares method.

关键词： Angle of arrival Antenna arrays Measurement units Receivers INERTIAL MEASUREMENT UNITS Virtual Elements

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Online Mutual Coupling Calibration Using a signal Source at Unknown Location 10

Online Mutual Coupling Calibration Using a Signal Source at ...

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10th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Wei, Tong Liao, Bin Huang, Huiping Quan, Zhi Shenzhen Univ Coll Informat Engn Shenzhen 518060 Guangdong Peoples R China

ISBN: (纸本)9781538647523

The effect of mutual coupling among the antenna elements will degrade the performance of array signal processing methods, and hence, mutual coupling calibration has attracted many research interests. However, existing approaches to deal with this problem either require the angular information of the calibration source(s) or require computationally expensive procedures to determine the mutual coupling coefficients. To this end, we propose an efficient method to calibrate the mutual coupling with a single source at unknown location. In particular, by exploiting the fact that mutual coupling is inversely related to their separation and is negligible when they are separated by a few wavelengths and the mutual coupling matrix (MCM) of uniform linear array (ULA) can be approximated as a banded symmetric matrix, it is shown that both the signal direction-of-arrival (DOA) and mutual coupling coefficients can be estimated in closed-form without any spectral grid search. Simulation results indicate that the proposed methods is able to provide promising performance compared with existing approaches.

关键词： Mutual coupling Calibration array signal processing Direction-of-arrival estimation Antenna arrays signal to noise ratio sensor arrays"

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Simultaneous Communication and Tracking in Arbitrary Trajectories via Beam-Space processing 12

Simultaneous Communication and Tracking in Arbitrary Traject...

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IEEE 12th sensor array and multichannel signal processing workshop (SAM)

作者： Pedraza, Fernando Dehkordi, Saeid K. Kobayashi, Mari Caire, Giuseppe Tech Univ Berlin Berlin Germany Tech Univ Munich Munich Germany

ISBN: (纸本)9781665406338

In this paper, we develop a beam tracking scheme for an orthogonal frequency division multiplexing (OFDM) Integrated Sensing and Communication (ISAC) system with a hybrid digital analog (HDA) architecture operating in the millimeter wave (mmWave) band. Our tracking method consists of an estimation step inspired by radar signal processing techniques, and a prediction step based on simple kinematic equations. The hybrid architecture exploits the predicted state information to focus only on the directions of interest, trading off beamforming gain, hardware complexity and multistream processing capabilities. Our extensive simulations in arbitrary trajectories show that the proposed method can outperform state of the art beam tracking methods in terms of prediction accuracy and consequently achievable communication rate, and is fully capable of dealing with highly non-linear dynamic motion patterns.

关键词： Integrated Sensing and Communication (ISAC) Beam Tracking OFDM Hybrid Digital Analog (HDA)

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Planar spherical diffraction-arrays: Linear sound localization algorithms

Planar spherical diffraction-arrays: Linear sound localizati...

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4th IEEE sensor array and multichannel signal processing workshop

作者： Handzel, Amir A. 42 Hillcrest Circle Watertown MA 02472 USA

ISBN: (纸本)1424403081

Sound source localization systems typically measure differences in time-of-arrival between microphones in free field arrays. Using a different concept, we previously designed and built a localization system that mimics nature's solution of harnessing wave diffraction about the head while relying only on two sensors positioned antipodally. Departing from the biological constraint of two sensors, I recently showed that for broadband sources, a high acuity array could be designed with merely three microphones. Yet adding more microphones may further increase acuity and robustness. The localization algorithm we have developed uses pair-wise comparisons between microphones, the number of which increases quadratically with the number of microphones, N. In order to minimize calculations in time sensitive applications, choosing a subset of pairs may be important. I examine this issue here through simulations of a hexagonal array. Thanks to the redundancy of spatial information contained in multiple microphone measurements, algorithms that are linear in N allow high acuity localization of broadband sources.

关键词： array processing

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Distributed Posterior Cramer-Rao Lower Bound for Nonlinear Sequential Bayesian Estimation

Distributed Posterior Cramer-Rao Lower Bound for Nonlinear S...

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IEEE 7th sensor array and multichannel signal processing workshop (SAM)

作者： Mohammadi, Arash Asif, Amir York Univ Toronto ON M3J 1P3 Canada

ISBN: (纸本)9781467310710

In distributed sensor networks, the posterior Cramer-Rao lower bound (PCRLB) has recently been used [1] as a selection criteria for sensor management decisions, where new sensor nodes are deployed or existing ones reactivated to optimize the network's performance. Previous algorithms to compute the PCRLB are derived for the centralized [2] and hierarchical architectures [3] using a fusion centre that makes them inappropriate for distributed sensor management. Only recently a suboptimal expression [1] for the distributed architecture has been proposed, which can at times lead to large errors especially in systems with highly non-linear dynamics. The paper derives the optimal PCRLB for the distributed architecture. In other words, we derive a recursive procedure to determine the overall Fisher information matrix (FIM), i.e., the inverse of the PCRLB, from local FIMs of the distributed estimators. The proposed distributed PCRLB is independent of the filtering mechanism used and closely follows its centralized counterpart.

关键词： Bayesian Estimation Distributed signal processing Particle Filters Posterior Cramer Rao Lower Bounds

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