The purpose of this chapter was to establish an important extension of the techniques provided in the preceding two chapters toward fully decentralized numerical schemes for the sensor scheduling task. Making an explicit use of the so-called randomized gossip algorithms, it was possible to develop efficient approaches for networks with scanning and mobile nodes, which distribute the computational burden across the network. In the context of parameter estimation for DPSs, such an idea has not been exploited yet.

关键词：光机电；传感器；调度；随机八卦算法

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The paper considers the problem of distributed estimation of an unknown deterministic scalar parameter (the target signal) in wireless sensor networks (WSNs), in which each sensor receives a single snapshot of the field. The observation or sensing mode is only partially known at the corresponding nodes, perhaps, due to their limited sensing capabilities or other unpredictable physical factors. Specifically, it is assumed that the observation process at a node switches stochastically between two modes, with mode one corresponding to the desired signal plus noise observation mode (a valid observation), and mode two corresponding to pure noise with no signal information (an invalid observation). With no prior information on the local sensing modes (valid or invalid), the paper introduces a learning-based distributed estimation procedure, the mixed detection-estimation (MDE) algorithm, based on closed-loop interactions between the iterative distributed mode learning and estimation. The online learning (or sensing mode detection) step re-assesses the validity of the local observations at each iteration, thus refining the ongoing estimation update process. The convergence of the MDE algorithm is established analytically. Simulation studies show that, in the high signal-to-noise ratio (SNR) regime, the MDE estimation error converges to that of an ideal (centralized) estimator with perfect information about the node sensing modes. This is in contrast with the estimation performance of a naive average consensus based distributed estimator (with no mode learning), whose estimation error blows up with an increasing SNR.

关键词：光机电；传感器；分布式；信息模型

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This report describes basic research to analyze and investigate methods for automatic detection and mitigation of sensor and perception data. Specifically, the PI will investigate (1) Metrics for sensor performance in context using multi-modal redundancy and information theoretic approaches; (2) Detection, localization and mitigation of faults and failures using hierarchical causal reasoning for diagnosis; (3) Develop methods for using low- level (e.g., sensor data fusion filter) versus high-level (autonomous inference) processes for automated selection of data to use for perception.

关键词：光机电；传感器；感知故障；数据完整性

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Applying external magnetic fields to arc discharges in gas circuit breakers is very helpful for facilitating arc extinguishing process. However, there has never been a report on decreases in arc electron densities under external magnetic fields. Here, 2-dimensional electron density distribution over an arc channel under an external magnetic field were obtained by only a single measurement using a Shack-Hartmann type laser wavefront sensor. The electron densities around a gap centre of about 10~(22)m~(-3) were lower than those without external magnetic fields when an instantaneous current decreased to 20A.

关键词：光机电；传感器；激光波；二维电子

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This project supports the capability to perform accurate infrasound sensor calibrations using a piston source and large volume chamber whose output has been independently determined and for which the error budget has been accurately assessed. Since the mid 1980s, Los Alamos National Laboratory (LANL) has operated an infrasound sensor calibration chamber that operates over a frequency range of 0.02 to 4 Hz. This chamber has provided sensitivities, volts/Pa, for sensors used by Los Alamos and others. Under the current program we will restore the chamber function, interrupted by an unexpected move, collaborate with researchers at the Sandia National Laboratory (SNL) Facility for Acceptance, Calibration, and Testing (FACT) Site on sensor issues, calibrate sensors as needed and research new methods for sensor response determination.

关键词：光机电；传感器；校准；响应

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One-dimensional fiber-bundle arrays may prove useful in a number of radiation sensing applications where radiation detection over large areas is needed. Tests have been performed to evaluate the light generation and transmission characteristics of 15-meter long, 10-fiber bundles of BCF-10, BCF-12, and BCF-20 scintillating fibers (Saint Gobain) exposed to collimated gamma-ray sources. The test set-up used one R9800 (Hamamatsu) photomultiplier tube (PMT) at each end, with a high-speed waveform digitizer to collect data. Time constraints were imposed on the waveform data to perform time-of-flight analysis of the events in the fiber bundles, eliminating spurious noise pulses in the high gain PMTs and also allowing 1-dimensional localization of interactions along the lengths of the fiber bundles. This paper will present the results of these measurements including the attenuation coefficients of the three fiber types and the timing resolution (position uncertainty) possible for each fiber bundle when using the R9800 PMTs.

关键词：光机电；传感器；光纤阵列；单维

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There is no doubt that preparation of experimental conditions in the sense of choosing a suitable observational strategy has great influence on the expected accuracy of parameter estimates, especially in the context of DPSs. The first part of the chapter contains a brief overview of the parameter identification problem and optimal experimental design for linear and nonlinear lumped dynamic systems. In particular, the notion of continuous designs is intro-duced, which dramatically reduces the problem dimensionality. Furthermore, generalization of some classical results from experimental design theory to multi-response systems with possibly correlated outputs is presented for the purpose of providing fundamental results which characterize the solutions and thus indicate possible numerical procedures. The inherent nonlinearity of DPSs with respect to the estimated parameters is certainly a problem of paramount importance and one of main complications in the delineated approach. However, under some assumptions, the results derived for systems linear in parameters can be extended to the class of nonlinear models based on suitable approximations of the FIM. Such a generalized classical theory paves the way to numerous applications of DPSs and, being crucial for specific problems, constitutes close connection with the chapters which follow.

关键词：光机电；传感器；调度；设计

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The Landsat Data Continuity Mission (LDCM) is being developed by NASA and USGS and is currently planned for launch in January 2013 (1). Once on-orbit and checked out, it will be operated by USGS and officially named Landsat-8. Two sensors will be on LDCM: the Operational Land Imager (OLI), which has been built and delivered by Ball Aerospace & Technology Corp (BATC) and the Thermal Infrared Sensor (TIRS)(2), currently being built and tested at Goddard Space Flight Center (GSFC) with a planned delivery of Winter 2012. The OLI covers the Visible, Near-IR (NIR) and Short-Wave Infrared (SWIR) parts of the spectrum; TIRS covers the Thermal Infrared (TIR). This paper discusses only the OLI instrument and its pre-launch characterization; a companion paper covers TIRS.

关键词：光机电；传感器；陆地卫星；陆地成像仪

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Both the public sector and the military are working on developing drowsiness detection systems, as driver fatigue is a significant contributor to motor vehicle accidents. Individually, electroencephalography (EEG) and eye- tracking measures are tenuous indicators of driver fatigue and impairment. This project proposes to integrate multiple sensor modalities in order to improve drowsiness level assessment and driver performance prediction. There is substantial evidence supporting the correlation of alpha bursts in EEG (narrowband alpha power density increases lasting 500 ms to several seconds) and eye-tracking measures, such as pupil diameter and gaze distribution, with drowsiness. As a step towards multi-sensory data fusion, we aim to implement in real time an optimized version of an existing algorithm for the automatic detection of alpha bursts using a single EEG channel and ascertain correlations between alpha bursts, eye-tracking measures, and behavioral indicators of fatigue that include standard deviation of both lane position and acceleration. The ability to reliably detect alpha bursts in real-time combined with established correlations will allow an algorithm to accurately predict driver performance in a simulation environment.

关键词：光机电；传感器；生理监测；融合

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关键词：光机电；传感器；扫描；激活

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