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检索条件"任意字段=2008 IEEE Sensor Array and Multichannel Signal Processing Workshop"

共 1267 条记录，以下是411-420 订阅

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Efficient Relative Fingerprinting Based UAV Localization via Tensor Completion

Efficient Relative Fingerprinting Based UAV Localization via...

引用

sensor array and multichannel signal processing workshop

作者： Changju Kan Guoru Ding Fei Song Junfei Qiu College of Communications Engineering Army Engineering University of PLA Nanjing China Department of Electronic Engineering University of York York U.K.

Recently, unmanned Aerial Vehicles (UAVs) localization is becoming a major research focus. In this paper, we propose a novel efficient relative fingerprinting-based passive UAV localization algorithm via a tensor completion approach. We first introduce a new relative fingerprint framework by exploring the correlations between the UAV fingerprint and the fingerprint database, the correction factors can be achieved to apply the fingerprint idea into the passive localization case. Then, we exploit the spatial correlation of the RSS data and propose a new training scheme which utilizes tensor completion. Simulation results highlight the superior performance of the proposed algorithm in terms of reconstruction error and localization accuracy.

关键词： Correlation Tensile stress sensors Databases Training Unmanned aerial vehicles signal processing algorithms

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Cramér-Rao Bounds for a Coupled Mixture of Polynomial Phase and Sinusoidal FM signals

Cramér-Rao Bounds for a Coupled Mixture of Polynomial Phase...

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sensor array and multichannel signal processing workshop

作者： Pu Wang Philip V. Orlik Kota Sadamoto Wataru Tsujita Yoshitsugu Sawa Mitsubishi Electric Research Laboratories Cambridge MA 02139 USA Mitsubishi Electric Corporation Advanced Technology R&D Center Amagasaki City 661-8661 Japan

This letter introduces a new coupled mixture of polynomial phase signal (PPS) and sinusoidal frequency modulated (FM) signal, motivated by real-world applications, for example, contactless linear encoders. Specifically, the coupling is introduced to express the sinusoidal FM frequency as a function of the PPS-related parameters. Given the coupling mixture, it generalizes two existing models: the pure PPS model and the independent mixture model. Performance bounds of parameter estimation for the coupled mixture model are established in terms of the Cramér-Rao bound (CRB). Unlike the pure PPS case, the derived CRB shows its dependence on the PPS-related and sinusoidal FM-related parameters due to the coupling mixture. On the other hand, the derived CRBs for the PPS-related parameters are lower than their counterparts of the independent mixture model, as the sinusoidal FM frequency provides additional information on the PPS parameters.

关键词： Frequency modulation Mixture models Couplings Indexes array signal processing sensor arrays

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Non-Linear Source Separation Under the Langmuir Model for Chemical sensors

Non-Linear Source Separation Under the Langmuir Model for Ch...

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sensor array and multichannel signal processing workshop

作者： Pierre Maho Simon Barthelmé Pierre Comon CNRS Univ. Grenoble Alpes Grenoble France

Electronic nose is a promising bio-inspired instrument for the detection of Volatil Organic Compounds (VOCs), meaning a compound containing carbon which easily evaporates. One of the most important parts of these devices is a set of non-specific chemical sensors, which will interact with the VOC and output valuable information for its identification. The nonspecificity of these chemical sensors ensures the universality of the instrument. The main task achieved by this instrument is the detection of individual VOC. However, in many real-life applications, mixtures of VOCs are observed. The recovery of the mixture composition, meaning the individual signatures and their relative contribution, is a challenging task which can be studied in a Blind Source Separation framework. In this paper, we propose a non-linear mixture model for a particular type of chemical sensors. This model is based on the Langmuir isotherm for a multi-component gas. We study the joint identifiability of signatures and concentrations, and propose a necessary identification condition. Finally, we propose an algorithm for the blind estimation of the parameters and assess its performance through simulations.

关键词： Chemical and biological sensors sensor arrays Chemicals array signal processing signal processing algorithms Mathematical model

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2D MIMO Radar with Coprime arrays

2D MIMO Radar with Coprime Arrays

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sensor array and multichannel signal processing workshop

作者： Conghui Li Lu Gan Cong Ling Department of EEE Imperial College London London UK School of Engineering and Design Brunel University London UK

In this contribution, a new class of planar coprime MIMO radar systems based on quadratic integers is proposed where the antenna locations are represented by lattice points generated by prime integers in quadratic number fields. By exploiting the coprimality of certain quadratic integers, the virtual coarrays of proposed structures enjoy a quadratic gain in parameter identifiability according to the Chinese Remainder Theorem (CRT). To avoid holes in the coarray, we present Hole-free CRT arrays with guaranteed full-rank autocorrelation matrices for subspace-based target estimation. The ring of Gaussian integers and the ring of Eisenstein integers are chosen as examples of designing coprime MIMO radar systems. It is shown that the proposed arrays achieve enhanced angular resolutions and improve the side lobe suppression. In the context of target estimation, simulations show the superior performance of the coprime MIMO structures based on CRT.

关键词： Cathode ray tubes Antenna arrays array signal processing Lattices Antenna radiation patterns Radar antennas Transmitting antennas

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Experimental Evaluation of a Universal Dominant Mode Rejection Beamformer

Experimental Evaluation of a Universal Dominant Mode Rejecti...

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sensor array and multichannel signal processing workshop

作者： kathleen E. Wage John R. Buck Electrical and Computer Engineering Dept. George Mason University Fairfax VA USA Electrical and Computer Engineering Dept. University of Massachusetts Dartmouth Dartmouth MA USA

The Dominant Mode Rejection (DMR) beamformer is designed to operate in non-stationary environments where few snapshots are available to estimate the sample covariance matrix (SCM). DMR assumes that the covariance can be split into orthogonal subspaces defined by the SCM eigenvectors: the first contains the loud interferers and the second contains the remaining signals and noise. The DMR approach requires an estimate of the rank of the interference subspace. Motivated by universal linear prediction, Buck and Singer propose a universal DMR beamformer that computes its weight vector as a linear combination of weight vectors for a set of fixed rank DMR beamformers. This universal DMR beamformer eliminates the need to explicitly estimate the rank of the interference subspace. Under reasonable mathematical assumptions, the universal DMR beamformer is guaranteed to converge to the performance of the best fixed rank beamformer in the set. This paper explores the performance of the universal DMR beamformer for a passive sonar data set acquired with a vertical line array deployed in the Philippine Sea.

关键词： Eigenvalues and eigenfunctions Standards sensor arrays Narrowband array signal processing Covariance matrices Interference

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Sound Source Localization for Hearing Aid Applications Using Wireless Microphones

Sound Source Localization for Hearing Aid Applications Using...

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sensor array and multichannel signal processing workshop

作者： Mojtaba Farmani Michael Syskind Pedersen Jesper Jensen Oticon A/S SmØrum Denmark

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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Time Difference of Arrival (TDOA)-Based Acoustic Source Localization and signal Extraction for Intelligent Audio Classification

Time Difference of Arrival (TDOA)-Based Acoustic Source Loca...

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sensor array and multichannel signal processing workshop

作者： Mingsian R. Bai Shih-Syuan Lan Jong-Yi Huang Department of Power Mechanical Engineering National Tsing Hua University Hsinchu Taiwan

An intelligent system is proposed to locate and classify audio source signals in large spaces. The system is composed of a sparsely distributed microphone array and an artificial intelligence (AI) system. A sparse array aimed for acoustic source localization and signal extraction is configured. The localization method is based on time difference of arrival (TDOA). This method begins with estimation of the TDOAs among at least 4 sensors, with the aid of a subspace-based time delay estimation algorithm. Next, a constrained least squares (CLS) algorithm is applied to locate the source in accord with the estimated TDOAs. Once the source is located, the source signal is extracted by using the minimum variance distortionless response (MVDR) beamformer and a postfilter. The extracted audio signals are further classified in light of machine learning. Convolutional Long Short-Term Memory (ConvLSTM) plays a central role in the AI-based classifier. Mel-Frequency Spectral Coefficients (MFSC) serves as the input layer in the ConvLSTM. The performance of the proposed system is quantified by using localization error, audio quality, and F 1 scores. Simulations are undertaken to validate the proposed TDOA-based localization and separation technique.

关键词： Microphones array signal processing sensor arrays signal processing algorithms Conferences Time difference of arrival

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Compressive Measurements Exploiting Coprime Frequencies for Direction Finding

Compressive Measurements Exploiting Coprime Frequencies for ...

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sensor array and multichannel signal processing workshop

作者： Muran Guo Yimin D. Zhang Tao Chen Department of Electrical and Computer Engineering Temple University Philadelphia PA USA College of Information and Communication Engineering Harbin Engineering University Harbin China

Sparse arrays are considered as an effective solution to reduce the system complexity for direction-of-arrival (DOA) estimation as they can resolve more sources than the number of sensors. Inspired by such techniques, the coprime frequency-based array structure was recently proposed to further reduce the number of required sensors. Multiple sensing signals with mutually coprime carrier frequencies are transmitted, and the reflected signals are used to estimate the target DOAs. The cross-correlation obtained from each pair of frequencies provides additional degrees of freedom (DOFs). On the other hand, a compression matrix can be designed to reduce the dimension of the received signal vector, thereby effectively reducing the number of front-end circuit chains. In this paper, we use the compressive measurements of the received signal vector obtained from a coprime frequency-based array structure to estimate the signal DOAs. The proposed scheme can obtain an increased number of DOFs and high estimation accuracy because of the coarray operation and the large array aperture of the coprime frequency-based array structure. Meanwhile, the system complexity is also significantly reduced. The effectiveness of the proposed scheme is validated using simulation results.

关键词： Direction-of-arrival estimation Estimation Frequency estimation sensor arrays array signal processing Covariance matrices

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Gridless Sound Field Decomposition Based on Reciprocity Gap Functional in Spherical Harmonic Domain

Gridless Sound Field Decomposition Based on Reciprocity Gap ...

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sensor array and multichannel signal processing workshop

作者： Yuhta Takida Shoichi Koyama Natsuki Ueno Hiroshi Saruwatari The University of Tokyo Graduate School of Information Science and Technology Tokyo Japan CNRS UMR E-SPCI Paris Diderot University Paris France

A gridless sound field decomposition method based on the reciprocity gap functional (RGF) is proposed. An intuitive and powerful way of reconstructing a sound field inside a region including sound sources is to decompose the sound field into Green's functions. Current methods based on sparse representation require discretization of the reconstruction region into grid points to construct the dictionary matrix; however, this procedure causes an off-grid problem and has a high computational cost. We apply the RGF, which was first proposed in the field of inverse problems, to sound field decomposition in the spherical harmonic domain. The proposed method enables a sound field to be decomposed in a gridless manner with a computationally efficient algorithm. Numerical simulation results indicated that the reconstruction accuracy as well as the source localization accuracy can be improved by the proposed method compared with current methods, especially at low frequencies.

关键词： Harmonic analysis Mathematical model Microphone arrays Position measurement array signal processing sensor arrays

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A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar

A Multi-Channel Partial-Update Algorithm for Sea Clutter Sup...

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sensor array and multichannel signal processing workshop

作者： Yahui Ma Shengheng Liu Jun Lu School of Information and Electronics Beijing Institute of Technology Beijing China China Academy of Electronics and Information Technology Beijing China

Sea clutters with Doppler-varying spectrum exert a notable negative impact on the detection performance, especially with low-velocity targets, when a passive bistatic radar is employed to detect sea-surface targets. One feasible solution is to modulate the reference signal onto the Doppler dimension and, as such, a filter with a wide notch and sharp edges can be obtained to suppress the residual clutters. However, to achieve this goal, a considerably high computational complexity is demanded in the existing two-dimensional (2D) adaptive filters. In this context, a novel 2D partial-update normalized least mean square algorithm is proposed to reduce the computational load, as well as to yield a superior clutter suppression performance. The effectiveness of the proposed approach is verified by real-data experiments.

关键词： Clutter signal processing algorithms Doppler effect Computational complexity Receiving antennas Bistatic radar Surveillance

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