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检索条件"任意字段=8th Sensor Signal Processing for Defence Conference, SSPD 2019"

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2019 sensor signal processing for defence conference, sspd 2019

2019 Sensor Signal Processing for Defence Conference, SSPD 2...

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8th sensor signal processing for defence conference, sspd 2019

ISBN: (纸本)9781728105031

the proceedings contain 21 papers. the topics discussed include: tradeoffs in detection and localization performance for mobile sensor scanning strategies;detection of incumbent radar in the 3.5 GHz CBRS band using support vector machines;measuring smoothness of real-valued functions defined by sample points on the unit circle;accuracy of Adcock Watson-Watt DF in the presence of channel errors;dual-functional radar-communication waveform design under constant-modulus and orthogonality constraints;message passing for joint registration and tracking in multistatic radar;prediction of sensor performance required for reliable aircraft target discrimination;and designing linear FM active sonar waveforms for continuous line source transducers to maximize the fisher information at a desired bearing.

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Research on Gravity Compensation Algorithm for Six-axis Force sensor based on Unscented Kalman Filter 8

Research on Gravity Compensation Algorithm for Six-axis Forc...

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8th International conference on Intelligent Computing and signal processing, ICSP 2023

作者： Li, Feifan Luo, Yangyu Li, Xiang Cao, Zhiyong Cheng, Guang Beijing Union University College of Urban Rail Transit and Logistics China Chinese Academy of Sciences Institute of Automation Beijing China Beijing Union University Institute of Intelligent Technology Beijing China

ISBN: (纸本)9798350302455

To address the problem of inaccurate measurements caused by the gravity effect on six-axis force sensors in human-robot interaction, this paper proposes a method for error correction of six-axis force sensors based on Unscented Kalman Filter (UKF) algorithm. By processing and estimating the sensor data, the proposed method achieves accurate estimation and correction of sensor errors, reducing the sensor error to between 0-0.175N. Experimental results demonstrate that the proposed method significantly improves the measurement accuracy of six-axis force sensors, providing reliable technical support for precise force control in human-robot interaction. the contribution of this study is to provide a reliable and efficient method to enhance the accuracy of six-axis force sensors. © 2023 IEEE.

关键词： Human robot interaction

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the Maximal Eigengap Estimator for Acoustic Vector-sensor processing 10

The Maximal Eigengap Estimator for Acoustic Vector-Sensor Pr...

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10th conference of the sensor-signal-processing-for-defence (sspd)

作者： Bassett, Robert Foster, Jacob Gemba, Kay L. Leary, Paul Smith, Kevin B. Naval Postgraduate Sch Operat Res Dept Monterey CA 93943 USA US Naval Res Lab Acoust Div Code 7160 Washington DC 20375 USA Naval Postgrad Sch Phys Dept Monterey CA 93943 USA

ISBN: (纸本)9781665433143

this paper introduces the maximal eigengap estimator for finding the direction of arrival of a wideband acoustic signal using a single vector-sensor. We show that in this setting narrowband cross-spectral density matrices can be combined in an optimal weighting that approximately maximizes signal-to-noise ratio across a wide frequency band. the signal subspace resulting from this optimal combination of narrowband power matrices defines the maximal eigengap estimator. We discuss the advantages of the maximal eigengap estimator over competing methods, and demonstrate its utility in a real-data application using signals collected in 2019 from an acoustic vector-sensor deployed in the Monterey Bay.

关键词： direction of arrival acoustic vector-sensor signal subspace eigengap

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Detection of Weak Transient signals Using a Broadband Subspace Approach 10

Detection of Weak Transient Signals Using a Broadband Subspa...

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10th conference of the sensor-signal-processing-for-defence (sspd)

作者： Weiss, Stephan Delaosa, Connor Matthews, James Proudler, Ian K. Jackson, Ben A. Univ Strathclyde Dept Elect Elect Engn Glasgow G1 1XW Scotland PA Consulting Global Innovat & Technol Ctr Cambridge Melbourn SG8 6DP England UK Def Sci & Technol Lab Dstl Salisbury SP4 0JQ England

ISBN: (纸本)9781665433143

We investigate the detection of broadband weak transient signals by monitoring a projection of the measurement data onto the noise-only subspace derived from the stationary sources. this projection utilises a broadband subspace decomposition of the data's space-time covariance matrix. the energy in this projected 'syndrome' vector is more discriminative towards the presence or absence of a transient signal than the original data, and can be enhanced by temporal averaging. We investigate the statistics, and indicate in simulations how discrimination can be traded off with the time to reach a decision, as well as with the sample size over which the space-time covariance is estimated.

关键词： Correlation Computational modeling signal processing Broadband communication Reliability Noise measurement Transient analysis

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How Noise Radar Technology Brings Together Active Sensing and Modern Electronic Warfare Techniques in a Combined sensor Concept 8

How Noise Radar Technology Brings Together Active Sensing an...

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8th sensor signal processing for defence conference (sspd)

作者： Wasserzier, Christoph Worms, Josef G. O'Hagan, Daniel W. Fraunhofer Inst High Frequency Phys & Radar Tech Fraunhoferstr 20 Wachtberg Germany

ISBN: (纸本)9781728105031

Research on modern EW algorithms follows a trend of increasing digital hardware implementations. the powerful features of these digital algorithms allow detection, location, identification and jamming of hostile radars. this paper presents a sensor concept in which mature EW features are expanded by an active sensing component using noise radar technology. It is shown that the flawless integration of noise radar into the EW functionality is accompanied with effective separation of all concurrent but different tasks of the combined sensor. Experimental results are presented which underline the basic idea of noise radar technology being the key enabler of this combined sensor concept.

关键词： Electronic Warfare Resource Management Multi-Function RF sensors Software-Defined Radar Software-Defined EW Spectrum Sharing Noise Radar

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Detection of Incumbent Radar in the 3.5 GHz CBRS Band Using Support Vector Machines 8

Detection of Incumbent Radar in the 3.5 GHz CBRS Band Using ...

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8th sensor signal processing for defence conference (sspd)

作者： Caromi, Raied Souryal, Michael NIST Commun Technol Lab Gaithersburg MD 20899 USA

ISBN: (纸本)9781728105031

In the 3.5GHz Citizens Broadband Radio Service (CBRS), 100MHz of spectrum will be dynamically shared between commercial users and federal incumbents. Dynamic use of the band relies on a network of sensors dedicated to detecting the presence of federal incumbent signals and triggering protection mechanisms when necessary. this paper uses field-measured waveforms of incumbent signals in and adjacent to the band to evaluate the performance of support vector machine (SVM) classifiers for these sensors. We find that a peak analysis classifier and a higher-order statistics classifier perform comparably when the signal is in white Gaussian noise or commercial long term evolution (LTE) emissions, but with out-of-band emissions of adjacent-band systems the peak analysis classifier is far superior. this result also highlights the importance of including adjacent-band emissions in any performance evaluation of 3.5GHz sensors.

关键词： 3.5GHz CBRS radar detection machine learning sensor

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Training and Validation of Automatic Target Recognition Systems using Generative Adversarial Networks 8

Training and Validation of Automatic Target Recognition Syst...

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8th sensor signal processing for defence conference (sspd)

作者： Karjalainen, Antti Ilari Mitchell, Roshenac Vazquez, Jose SeeByte Ltd Edinburgh Midlothian Scotland

ISBN: (纸本)9781728105031

this research provides advances aiming to improve the adaptability and usability of Automatic Target Recognition (ATR) algorithms in new environments. We propose to use a Generative Adversarial Networks (GAN) based approach to add simulated contacts into real sidescan sonar images. Our results show that the GAN approach is able to create realistic contacts. We carried out a visual experiment to validate that a trained operator was unable to distinguish real objects from simulated objects. In addition, we demonstrate that an ATR tuned using simulated objects, generated by the GAN, achieves a comparable performance to an ATR tuned using real data.

关键词： GAN (Generative Adversarial Networks) Deep neural networks Image processing Automatic Target Recognition (ATR)

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TWO STAGE AUDIO-VIDEO SPEECH SEPARATION USING MULTIMODAL CONVOLUTIONAL NEURAL NETWORKS 8

TWO STAGE AUDIO-VIDEO SPEECH SEPARATION USING MULTIMODAL CON...

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8th sensor signal processing for defence conference (sspd)

作者： Xian, Yang Sun, Yang Wang, Wenwu Naqvi, Syed Mohsen Newcastle Univ Intelligent Sensing & Commun Res Grp Newcastle Upon Tyne Tyne & Wear England Univ Surrey Ctr Vis Speech & Signal Proc Surrey England

ISBN: (纸本)9781728105031

the performance of the audio-only neural networks based monaural speech separation methods is still limited, particularly when multiple-speakers are active. the very recent method [1] used the audio-video (AV) model to find the non-linear relationship between the noisy mixture and the desired speech signal. However, the over-fitting problem always happens when the AV model is trained. Hence, the separation performance is limited. To address this limitation, we propose a system with two sequentially trained AV models to separate the desired speech signal. In the proposed system, after the first AV model is trained, its output is used to calculate the training target of the second AV model, which is exploited to further improve the separation performance. the GRID audiovisual sentence corpus is used to generate the training and testing datasets. the signal to distortion ratio (SDR) and short-time objective intelligibility (STOI) proved the proposed system outperforms the state-of-the-art method.

关键词： speech separation mapping relation AV model sequentially AV models

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TRADEOFFS IN DETECTION AND LOCALISATION PERFORMANCE FOR MOBILE sensor SCANNING STRATEGIES 8

TRADEOFFS IN DETECTION AND LOCALISATION PERFORMANCE FOR MOBI...

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8th sensor signal processing for defence conference (sspd)

作者： Spyrou, Loukianos Chambersy, Pat Sellathuraiy, Mathini thompson, John Univ Edinburgh Sch Engn IDCOM Edinburgh EH9 3JL Midlothian Scotland Heriot Watt Univ Engn & Phys Sci Edinburgh EH14 4AS Midlothian Scotland

ISBN: (纸本)9781728105031

Wireless sensor networks enjoy many advantages over wired networks due to their ability to be deployed easily and flexibly in many scenarios. However, they suffer from the drawback that the environment may be unknown and hence the sensor network cannot easily be optimised for it. Furthermore, state-of-the-art studies only consider the detection and localisation performance separately. the main novelty of this work is that we compare the theoretical properties of three scanning strategies both in terms of their detection and localisation performance. We consider: a) sequential scanning, where all sensors scan the channels in sequence, b) groupwise scanning, where the sensors are split into groups with each one performing a sequential scan, and c) random scanning, where each sensor is assigned a channel at random. We demonstrate the theoretical properties of the strategies and perform a numerical evaluation for a typical radio surveillance scenario. the tradeoffs of the methods between detection and localisation performance are demonstrated to be dependent on the detection and localisation accuracy with respect to the number of sensors. Approximate knowledge of those curves can aid in the design of an optimal sensor scanning strategy.

关键词： sensor networks sensor scanning multiuser detection localisation

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Adaptive Detection With Diffuse Multipath Exploitation in Partially Homogeneous Environments 8

Adaptive Detection With Diffuse Multipath Exploitation in Pa...

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8th sensor signal processing for defence conference (sspd)

作者： Gulen, Seden Hazal Hayvaci, Harun Taha TOBB Univ Econ & Tech ETU Dept EEE Ankara Turkey

ISBN: (纸本)9781728105031

In this paper, we deal with the problem of detecting point-like targets in the presence of multipath under the assumption of a partially homogeneous Gaussian disturbance with unknown covariance matrix. therefore, we introduce an unknown scaling factor which represents the mismatch between the noise covariance matrices of test and training signals. Besides, we model the target echo as a combination of direct and multipath components where multipath echoes are thought of as scattered signals from a glistening surface which is referred to as diffuse multipath environment. Hence, the total multipath return is also represented as a Gaussian distributed random vector with an unknown covariance matrix. At the design stage, we construct a constrained Generalized Likelihood Ratio Test (GLRT) by assuming that the total primary data covariance structure, in the target present case, resembles to the covariance matrix obtained from secondary data up to a degree (related to noise scaling factor and multipath contribution). Finally, at the analysis stage, we compared the developed algorithm with the existing solutions available in the open literature. the results highlight that the new detector copes well with severe multipath conditions and has considerable scale-invariance.

关键词： Covariance matrices Detectors Clutter Random variables Data models Probability density function signal to noise ratio

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