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LINEAR-TIME JOINT PROBABILISTIC DATA ASSOCIATION FOR MULTIPLE EXTENDED OBJECT TRACKING 10

LINEAR-TIME JOINT PROBABILISTIC DATA ASSOCIATION FOR MULTIPL...

引用

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

作者： Yang, Shishan Thormann, Kolja Baum, Marcus Univ Passau Fac Comp Sci & Math Chair Sensor Technol Passau Germany

ISBN: (纸本)9781538647523

The Joint Probabilistic Data Association (JPDA) filter for multiple object tracking is based on the assumption that at most one measurement originates from a target object. However, with the development of high-resolution sensors, it is often the case that multiple spatially distributed detections are obtained from a single object. To tackle this emerging data association challenge, this paper presents a JPDA method based on the Poisson spatial measurement model for extended objects. As the constraint that one target gets at most one measurement is relaxed, the marginal association probabilities can be obtained with linear complexity in the number of measurements and targets. The proposed method is compared to a partition-based multiple extended object tracking algorithm.

关键词： Shape Object tracking Clutter Target tracking Probabilistic logic Shape measurement Time measurement"

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Performance Evaluation of Bluetooth in a Wireless Body Area Network for Practical Applications 11

Performance Evaluation of Bluetooth in a Wireless Body Area ...

引用

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

作者： Reich, Olaf Hubner, Erik Ghita, Bogdan Wagner, Matthias Schafer, Jorg Frankfurt Univ Appl Sci Dept Comp & Engn Sci Frankfurt Germany Univ Plymouth Plymouth Devon England

ISBN: (纸本)9781728119465

This work focuses on practical research in the field of Bluetooth 5.0 and the maximum number of Bluetooth sensors nodes in a wireless body area network (WBAN) for human activity recognition (HAR). As network topology M:1 multi-pairing is used. For the best of our knowledge no direct related work in this field can be found. We investigated how many Bluetooth connections can be simultaneously connected with different smartphones (iOS) with real sensor data and in which time intervals the data can still be processed and stored. Our results show that a maximum of 14 Bluetooth devices can be connected under practical conditions. A stable transmission with 48 bytes per package are found with most reliability in an minimal interval of 40 ms per node.

关键词： Bluetooth Internet of Things (IoT) performance-evaluation wireless body area network (WBAN) Special Interest Group (SIG) NINA sensor networks

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Distributed Binary Geometric sensor arrays for Low-Data-Throughput Human Gait Biometrics

Distributed Binary Geometric Sensor Arrays for Low-Data-Thro...

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

作者： Yue, Tianyao Hao, Qi Brady, David J. Duke Univ Dept Elect & Comp Engn Box 90291 Durham NC 27708 USA Univ Alabama Dept Elect & Comp Engn Tuscaloosa AL 35487 USA

ISBN: (纸本)9781467310710

We present a novel sensing paradigm of measuring human gait. The goal of the research is to achieve low-cost gait biometrics systems with minimum data throughput for various sensing modalities. The binary measurements of the system are achieved by using both (1) periodic and (2) pseudo-random sampling structures. As a result, either static or dynamic gait features can be estimated from a one-bit data stream. The simulation results demonstrate the gait information acquisition capability of the proposed binary sensing technology.

关键词： Biometrics

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Interferometric array Design Under Regularized Antenna Placements for Interference Suppression 10

Interferometric Array Design Under Regularized Antenna Place...

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

作者： Wang, Xiangrong Amin, Moeness Aboutanios, Elias Beihang Univ Sch Elect & Informat Engn Beijing Peoples R China Villanova Univ Ctr Adv Commun Villanova PA 19085 USA Univ New South Wales Sch Elect Engn Sydney NSW Australia

ISBN: (纸本)9781538647523

Interference suppression is an important task in extensive sensor array applications, including large interferometric arrays in radio astronomy. The interferometric array design in terms of maximizing output signal-to-interference-plus-noise ratio (MaxSINR) calls for freely placing antennas on grid points without imposing any regularity conditions on the array structure. The configured sparse array exhibits multiple drawbacks, most notably, uncontrollable beampatterns with high sidelobes. To overcome these shortcomings, we add conventional beampattern sidelobe constraints in the design formulation. The resulting array is referred to as restricted beampattern array configuration (RBAC). Alternatively, we consider a new regularized placement array configuration (RPAC) strategy, where antenna position constraints are imposed as means for sidelobe control. In this case, the antenna selection is performed such that each segment of grid points must include one antenna, preventing very large inter-element spacing. We formulate the new RPAC problem and compare its solution to that of the RBAC.

关键词： Interferometric array Regularized sensor Placement Sidelobe Suppression Beampattern

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Angular Information Resolution Limit of sensor arrays

Angular Information Resolution Limit of Sensor Arrays

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

作者： Cheng, Yongqiang Wang, Xuezhi Moran, Bill Natl Univ Def Technol Sch Elect Sci & Engn Beijing Peoples R China Univ Melbourne Melbourne Sch Engn Dept Elect & Elect Engn Melbourne Vic 3010 Australia Univ Melbourne Melbourne Sch Engn Def Sci Inst Melbourne Vic 3010 Australia

ISBN: (纸本)9781479914814

A measure of the ability of a sensor array to resolve two closely spaced point sources in angle is proposed here based on the framework of information geometry. The consideration of the geometric structure of a measurement model leads to the concept of information resolution which serves as a new metric to measure intrinsic similarities and differences between signal distributions that generate the manifold geometry. The statistical divergence between two sources is characterized in terms of the geodesic distance induced by the Fisher information metric. An analytical expression of the angular information resolution limit (AIRL) is derived using the constraints on the probability of error for a binary hypothesis test associated with the resolution of two sources. The influence of the detection error as well as the signal-to-noise ratio (SNR) on resolvability are demonstrated. The proposed AIRL can be used as a performance measure for sensor arrays in localizing remote sources and is applicable to various applications (e.g. radar, sonar, or astronomy).

关键词： Geometry

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A Sparse Regularization Technique for Source Localization with Non-uniform sensor Gain

A Sparse Regularization Technique for Source Localization wi...

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

作者： Weiss, Christian Zoubir, Abdelhak M. Tech Univ Darmstadt Germany Signal Proc Grp D-64283 Darmstadt Germany Grad Sch Computat Engn D-64293 Darmstadt Germany

ISBN: (纸本)9781479914814

A robust sparse regularization technique with applications to source localization in the presence of non-uniform gain distribution is presented. As a key component in sparse optimization, a proper choice of the regularization parameter is crucial. It renders high impact on the localization performance and has to account for any kind of model perturbation. Our proposed technique utilizes a statistical framework to provide a direct relation between the physical system parameters and the regularization parameter of the resulting optimization problem. It addresses the joint effects of sensor gain variations and noise. As a figure of merit, we consider the mean-squared error (MSE) between the perturbed measurements and the assumed underlying model. An upper bound of the MSE is attained in order to estimate the regularization parameter. The presented method shows good performance for moderate gain variances even in low SNR regimes.

关键词： sparse regularization model errors source localization robust model non-uniform sensor gain

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Tracking Simplified Shapes Using a Stochastic Boundary

Tracking Simplified Shapes Using a Stochastic Boundary

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

作者： Zea, Antonio Faion, Florian Baum, Marcus Hanebeck, Uwe D. Karlsruhe Inst Technol KIT Inst Anthropomat & Robot Intelligent Sensor Actuator Syst Lab ISAS Karlsruhe Germany Univ Connecticut Storrs CT USA

ISBN: (纸本)9781479914814

When tracking extended objects, it is often the case that the shape of the target cannot be fully observed due to issues of visibility, artifacts, or high noise, which can change with time. In these situations, it is a common approach to model targets as simpler shapes instead, such as ellipsoids or cylinders. However, these simplifications cause information loss from the original shape, which could be used to improve the estimation results. In this paper, we propose a way to recover information from these lost details in the form of a stochastic boundary, whose parameters can be dynamically estimated from received measurements. The benefits of this approach are evaluated by tracking an object using noisy, real-life RGBD data.

关键词： EXTENDED OBJECTS information loss Ellipsoid tracking Stochastic Boundary boundary layer Shape Targets Noise tracking objects

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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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Calibration of Polarimetric Antenna arrays Using Neural Networks 13

Calibration of Polarimetric Antenna Arrays Using Neural Netw...

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13rd ieee sensor array and multichannel signal processing workshop (SAM)

作者： Springer, Jannik Mikus, Philipp Oispuu, Marc Koch, Wolfgang Knott, Peter Fraunhofer Inst Commun Informat Proc & Ergon FKIE Fraunhoferstr 20 D-53343 Wachtberg Germany Fraunhofer Inst High Frequency Phys & Radar Tech Fraunhoferstr 20 D-53343 Wachtberg Germany

ISBN: (纸本)9798350344820;9798350344813

This paper addresses the problem of calibration for antenna arrays with multi-port polarimetric elements. Model-based array signal processing techniques require an accurate model of the complex array response and model errors can, for example, cause significant systematic direction finding errors. Modeling the response of polarimetric antenna arrays can be particularly challenging due to cross-polarization and mutual coupling effects in the multi-port antenna elements. This work proposes a new calibration technique for polarimetric antenna arrays using neural networks that learn any mismatches between the modeled and the actual array response. The technique is evaluated based on the measured response of a five-element dual-polarized antenna array and outperforms conventional calibration techniques like mutual coupling calibration or local polynomial approximation. Its performance is studied exemplarily for the direction finding problem.

关键词： antenna array polarization calibration machine learning neural network direction finding

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sensor Network Distributed Computation for Direct Position Determination

Sensor Network Distributed Computation for Direct Position D...

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

作者： Pourhomayoun, Mohammad Fowler, Mark L. SUNY Binghamton Dept Elect & Comp Engn Binghamton NY 13902 USA

ISBN: (纸本)9781467310710

Classical localization systems based on TDOA/FDOA use a two-stage estimation approach. In the first stage, pairs of sensors share data to estimate TDOA/FDOA. Then, the extracted TDOA/FDOA measurements are used to estimate the emitter location. In some recently published methods, an optimal single-stage approach named Direct Position Determination (DPD) has been proposed to improve the position estimation accuracy. However, unlike the classical two-stage method where the TDOA/FDOA estimation can be distributed across all sensors, DPD processes all the received signals together at a single sensor node. However, when sensors have limited computational capabilities it is desirable to distribute the computation across all sensors. Furthermore, concentrating all the processing into a single node makes the location system less robust to the loss of sensors. In this paper, we develop a distributed localization method with the goal of reducing the computational load on each sensor and increasing the reliability of the system.

关键词： Time difference of arrival

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