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Multi-sensor feature fusion methods and results

Multi-sensor feature fusion methods and results

引用

conference on Sensor Fusion - Architectures, Algorithms, and Applications V

作者： Heagy, D Barnes, R Bechhoefer, E Mitre Corp MS W967 Mclean VA 22101 USA

ISBN: (纸本)0819440809

Analysts responsible for supporting time dominated threat decisions are faced with a growing volume of sensor data. Most efforts to increase discrimination among targets using multiple types of sensors encounter the same problems: Sensor data are received in large volumes. Sensor data are highly variable. Signature features are represented by many dimensions. Feature values are intercorrelated, random or not related to target differences. Decision rules for classifying new target data are difficult to define. This paper describes a new methodology for solving several problems: selecting signature features, reducing variability, increasing discrimination accuracy, and developing decision rules for classifying new target signatures. The results from using a combination of exploratory and multivariate statistical techniques show potential improvements over the traditional Dempster-Shafer approach. This project uses data from operational prototype sensors and vehicles of interest for threat analysis. Acoustic and seismic sensor data came from an unattended ground sensor and three military vehicles. Although the resulting algorithms are specific to the data set, the data screening and fusion methods tested in this project may be useful with other types of sensor and target data.

关键词： feature fusion multisensor classification data screening signal processing pattern recognition feature templates multivariate statistics Dempster-Shafer threat analysis

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Automated Evaluation of Non-Native English Pronunciation Quality: Combining Knowledge- and data-Driven Features at Multiple Time Scales 16

Automated Evaluation of Non-Native English Pronunciation Qua...

引用

16th Annual conference of the International-Speech-Communication-Association (INTERSPEECH 2015)

作者： Black, Matthew P. Bone, Daniel Skordilis, Zisis I. Gupta, Rahul Xia, Wei Papadopoulos, Pavlos Chakravarthula, Sandeep Nallan Xiao, Bo Van Segbroeck, Maarten Kim, Jangwon Georgiou, Panayiotis G. Narayanan, Shrikanth S. Univ Southern Calif Signal Anal & Interpretat Lab Los Angeles CA 90089 USA Univ Southern Calif Informat Sci Inst Marina Del Rey CA USA Behav Informatix LLC Los Angeles CA USA

ISBN: (纸本)9781510817906

Automatically evaluating pronunciation quality of non-native speech has seen tremendous success in both research and commercial settings, with applications in L2 learning. In this paper, submitted for the INTERSPEECH 2015 Degree of Nativeness Sub-Challenge, this problem is posed under a challenging cross corpora setting using speech data drawn from multiple speakers from a variety of language backgrounds (L1) reading different English sentences. Since the perception of non-nativeness is realized at the segmental and suprasegmental linguistic levels, we explore a number of acoustic cues at multiple time scales. We experiment with both data-driven and knowledge-inspired features that capture degree of nativeness from pauses in speech, speaking rate, rhythm/stress, and goodness of phone pronunciation. One promising finding is that highly accurate automated assessment can be attained using a small diverse set of intuitive and interpretable features. Performance is further boosted by smoothing scores across utterances from the same speaker;our best system significantly outperforms the challenge baseline.

关键词： Behavioral signal processing (BSP) computational paralinguistics Goodness of Pronunciation (GOP) speech assessment non-native speech prosody challenge

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A Hotelling T-squared GIP test for detection of over resolved targets

A Hotelling T-squared GIP test for detection of over resolve...

引用

European Wireless conference (EW)

作者： Michael C. Wicks Yuhong Zhang Richard Schneible James Paul Browning AFRL Rome NY USA Stiefvater Consultants Rome NY USA

A new technique for detection and discrimination of stationary or slow-moving over-resolved targets on the ground, based upon a Hotelling T-squared test/generalized inner product (GIP) approach to signal analysis is presented. This robust detector separates radar returns from interference via a coherent process. This GIP-based processing can be applied to single-receiver channel systems, multiple spatial channel systems, multiple polarization channel systems or systems with multiple spatial and polarization channels.

关键词： Testing Radar signal processing Radar detection Clutter signal processing Frequency Wireless sensor networks Delay data analysis Adaptive signal processing

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A dynamic model for generating actuator specifications for small arms barrel active stabilization

A dynamic model for generating actuator specifications for s...

引用

Smart Structures and Materials 2006 conference

作者： Pathak, Anupam Brei, Diann Luntz, Jonathan Lavigna, Chris Univ Michigan Mech Engn 2250 G G Brown Ann Arbor MI 48109 USA Techno Sci Inc Lanham MD 20706 USA

ISBN: (纸本)0819462195

Due to stresses encountered in combat, it is known that soldier marksmanship noticeably decreases regardless of prior training. Active stabilization systems in small arms have potential to address this problem to increase soldier survivability and mission effectiveness. The key to success is proper actuator design, but this is highly dependent on proper specification which is challenging due to the human/weapon interaction. This paper presents a generic analytical dynamic model which is capable of defining the necessary actuation specifications for a wide range of small arms platforms. The model is unique because it captures the human interface - shoulder and arm - that introduces the jitter disturbance in addition to the geometry, inertial properties and active stabilization stiffness of the small arms platform. Because no data to date is available for actual shooter-induced disturbance in field conditions, a method is given using the model to back-solve from measured shooting range variability data the disturbance amplitude information relative to the input source (arm or shoulder). As examples of the applicability of the model to various small arms systems, two different weapon systems were investigated: the M24 sniper weapon and the M16 assault rifle. In both cases, model based simulations provided valuable insight into impact on the actuation specifications (force, displacement, phase, frequency) due to the interplay of the human-weapon-active stabilization interface including the effect of shooter-disturbance frequency, disturbance location (shoulder vs. arm), and system parameters (stiffness, barrel rotation).

关键词： rifle stabilization active damping active isolation INSTAR

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Generalized likelihood ratio test for distributed targets in heterogeneous environments

Generalized likelihood ratio test for distributed targets in...

引用

International conference on signal processing Proceedings (ICSP)

作者： Xiuqin Shang Hongjun Song SMRSS GUCAS Beijing China SMRSS IECAS Beijing China

Adaptive detection for distributed target or targets in non-homogeneous environments is studied in this paper. It is assumed that the covariance matrix of the secondary data M s is a random matrix following inverse Wishart distribution with its conditional expectation proportional to that of the primary data, i.e. E(M s | M p )= γM p . Firstly, the maximum likelihood estimator (MLE) of M p , γ and target amplitudes are given and the generalized likelihood ratio test (GLRT) are proposed subsequently, which turns out to be in the form of the summed adaptive coherence estimator (ACE). The detector is coincident with the generalized adaptive subspace detector (GASD) based on deterministic unknown covariance matrix and it has CFAR property. When the target exists only in one range bin, the detector is boiled down into the ACE based on the partial homogeneous environments.

关键词： Covariance matrix Detectors Maximum likelihood estimation Bayesian methods Clutter Artificial neural networks signal to noise ratio

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A compact data acquisition system for multi-detectors: Time encoding for both time and energy measurement

A compact data acquisition system for multi-detectors: Time ...

引用

2000 IEEE Nuclear Science Symposium conference Record

作者： Pinot, L. Sellem, R. Cuzon, J.C. Lesage, A. Mastrippolito, R. Valentin, L. Institut de Physique Nucleaire 91406 Orsay Cedex France

We have developed an acquisition chain, that steers the detection of events characterized by the deposited energy and the arrival time. All analog informations are first converted into temporal informations by means of translators plugged inside each detector, then only logical signals (containing : way number, arrival time, energy) are processed by the system (transmission, multiplexing-dispatching) and are coded by a Fast Multi-hit Time to Digital Converter (FTDC) with a 225 ps resolution and a 24 ns dead time. The FTDC runs without trigger and assigns "absolute value" to each temporal signal. A Digital signal Processor (DSP) processes these values and extracts the events in coincidence according to energy and time gates. So the data are saved on hard disk and the experiment can be reloaded every time it is necessary with different parameters (time and energy windowing). The absolute time saving has the advantage of not making a hardware time adjustment. All processing components are mounted in a dedicated PC board. The system was validated and is currently used for TOHR (French acronym of High Resolution Tomograph), a tomograph developed for high resolution in vivo imaging adapted to small animal models studies. The quadruple coincidences throughput (with 15 detectors) is more than 200,000 events/second. Figure 1 shows the architecture of complete system. The acquisition control and data saving program is written in Labview.

关键词： Particle detectors

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Application of broadband, wide-azimuth and high-density BWH seismic data processing technology in complex structure imaging of Songliao basin

Application of broadband, wide-azimuth and high-density BWH ...

引用

Abu Dhabi International Petroleum Exhibition and conference 2019, ADIP 2019

作者： Su, Qin Zeng, Huahui Zhang, Xiaomei Lv, Lei Qie, Shuhai Meng, Huijie Research Institute of Petroleum Exploration and Development-Northwest NWGI Petro China China

ISBN: (纸本)9781613996720

With the continuous development of oil and gas exploration technology, the remaining exploration targets in the middle and shallow areas of the land are becoming less and less, and the deep complex targets have become an important replacement area for oil and gas growth. In order to enhance the deep tight gas exploration potential of the Songliao Basin in China, structural interpretation and reservoir prediction of deep volcanic rocks and glutenite lithologic gas reservoirs are carried out, while the basic requirements for seismic data acquisition in complex reservoir exploration in the middle-deep layers are: higher sampling density, even distribution of space, appropriate offset. In the face of particularly complex reservoirs, it is necessary to fully strengthen the acquisition parameters, ensure the reservoir prediction needs, and avoid the waste caused by the inability to solve the geological problems. However, due to the weak signal and strong interference, the conventional narrow-azimuth three-dimensional observation system in the Songliao Basin is affected by factors such as low folds, large grid bin, and low reception of complex structural information, which affects the middle-deep layers. The imaging effect has restricted the development of tight gas exploration in the middle-deep layers. Therefore, the broadband, wide-azimuth and high-density (BWH) 3D seismic exploration technology has been developed. BWH refers to a wider excitation and reception frequency band, a wider reception orientation, and a higher sampling density. Generally, broadband acquisition requires signals with an octave of more than 5 times;wide-azimuth observation systems should have an aspect ratio greater than 0.5, where an aspect ratio greater than 0.85 is called an omnidirectional observation system;when using an explosive source, sampling densities greater than 500,000 channels/km2 can be referred to as high-density sampling. The application of actual data shows that the BWH data no

关键词： Aspect ratio

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Feature Analysis of Passive Underwater targets Recognition Based on Deep Neural Network

Feature Analysis of Passive Underwater Targets Recognition B...

引用

OCEANS - Marseille conference

作者： Ren, Jiawei Huang, Zhaoqiong Li, Chen Guo, Xinyi Xu, Ji Chinese Acad Sci Inst Acoust Key Lab Speech Acoust & Content Understanding Beijing Peoples R China Chinese Acad Sci Inst Acoust Key Lab Underwater Environm Beijing Peoples R China

ISBN: (纸本)9781728114507

As an important research direction of sonar signal processing, the research on taking deep neural network (DNN) as a classifier for underwater target recognition has become a hotspot. Feature extraction methods are adapted to the classifier and WPCE, FBANK and MFCC features was normally used as input for DNN. In this paper, a time-delayed neural network (TDNN) based classification system has been proposed to compare the recognition effects of different features. The wavelet packet component spectrum (WPCS) was proposed as a new feature extraction method based on WPCE, since the wave packet transform separating noise for line spectrum extraction. The experiments on the real recorded data of two type of vessels indicate that the proposed system using WPCS features provides higher recognition accuracy than using WPCE, FBANK and MFCC features. Feature vector extension and average were used to optimize WPCE features which achieved 2.93% and 9.76% improvement respectively.

关键词： underwater target recognition wavelet packet component spectrum feature optimization deep neural network

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Multi-Aspect Target Classification and Detection via the Infinite Hidden Markov Model

Multi-Aspect Target Classification and Detection via the Inf...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Kai Ni Yuting Qi Lawrence Carin Department of Electrical and Computer Engineering Duke University Durham NC USA

A new multi-aspect target detection method is presented based on the infinite hidden Markov model (iHMM). The scattering of waves from multiple targets is modeled as an iHMM with the number of underlying states treated as infinite, from which a full posterior distribution on the number of states associated with the targets is inferred and the target-dependent states are learned collectively. A set of Dirichlet processes (DPs) are used to define the rows of the HMM transition matrix and these DPs are linked and shared via a hierarchical Dirichlet process (HDP). Learning and inference for the iHMM are based on an effective Gibbs sampler. The framework is demonstrated using measured acoustic scattering data.

关键词： Hidden Markov models Acoustic scattering Object detection Electromagnetic scattering Physics Training data Acoustic measurements Electromagnetic measurements Acoustic signal detection Acoustic emission

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COMPRESSIVE SENSING FOR WIFI-BASED PASSIVE BISTATIC RADAR

COMPRESSIVE SENSING FOR WIFI-BASED PASSIVE BISTATIC RADAR

引用

European signal processing conference

作者： Patrick Maechler Norbert Felber Hubert Kaeslin Integrated Systems Laboratory ETH Zurich

ISBN: (纸本)9781467310680

Passive radars using WiFi base stations as illuminators are a promising option for local area surveillance. Unfortunately, the reflections of WiFi signals from a large object can easily mask any nearby objects making it difficult to detect all targets within range. Using the fact that most target scenes are only very sparsely populated makes it possible to apply compressive sensing (CS) for target detection. We analyze how well WiFi signals fit into the CS framework, propose corresponding detection schemes, and show how detection accuracy is increased and receiver complexity is reduced. It turns out that CS enables the detection of closely spaced targets with only a small number of recorded WiFi frames.

关键词： Localization Passive radar Compressive sensing Sparse approximation Wi-Fi illuminators targets Object detection CONTAINMENT SPRAY carbon monosulfide Cesium Passive radar conditioned stimulus Compressed sensing

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