We consider the problem of distributed detection in a large network of sensors under network communication constraints. Sensor nodes are randomly deployed and follow a random sleep/wake schedule. When awake, sensor nodes perform local detection tests and communicate detections over a multiple-access channel to a fusion center. The fusion center can detect both successful communications and communication collisions in the channel. We derive fusion rules for perfect communications and a delay-constrained protocol and show that each are functions of count statistics only. We derive analytical expressions that characterize the performance of the system in terms of energy consumption and detection probability. Simulation examples compare theoretical predictions with numerical results.

关键词：通信和广播系统；多路访问网络；二进制处理器；分布式计算

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This project was dedicated to solving basic scientific issues and developing the scientific basis that underlies the improvement of super-dense memories, towards the terabit per square inch goal and the engineering of chemical and biological sensors. Both applications rely on porous materials among which porous alumina is the most promising. The research under this project in each of the objectives has lead to major advances. We have improved considerably the size distribution of the porous alumina used for masks using a double anodization process. We have also developed an unconventional bootstrapping method, which uses self-supporting porous membranes. This allowed fabrication and research on the properties of very well ordered array of small magnetic nanodots on different substrates, which could not be done otherwise. It also permitted us to develop new concepts of storage and explore the interaction between magnetic dots. Due to this technology we had also several major advances in the field of DNA sequencing and in the development of biosensors. This project leverages funding from AFOSR through extensive collaboration with colleagues at UC San Diego, UC Davis and Los Alamos National Labs and no cost, contribution of researchers that are spending extended periods of times at UCSD.

关键词：传感器；内存；探测器；纳米磁性；磁场

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Our long-term goal is to use remote sensing observations to constrain a data assimilation model of wave and circulation dynamics in an area characterized by a river mouth or tidal inlet and surrounding beaches. As a result of this activity, we will improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments.

关键词：传感器融合；远程检测；多维传感；深度测量法

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Laser Radar sensors can be designed to provide two-dimensional and three-dimensional (3-D) images of a scene from a single laser pulse. Currently, there are various data recording and presentation techniques being developed for 3-D sensors. While the technology is still being proven, many applications are being explored and suggested. As technological advancements are coupled with enhanced signal processing algorithms, it is possible that this technology will present exciting new military capabilities for sensor users. The goal of this work is to develop an algorithm to enhance the utility of 3-D Laser Radar sensors through accurate ranging to multiple surfaces per image pixel while minimizing the effects of diffraction. Via a new 3-D blind deconvolution algorithm, it will be possible to realize numerous enhancements over both traditional Gaussian mixture modeling and single surface range estimation. While traditional Gaussian mixture modeling can effectively model the received pulse, we know that its shape is likely altered due to optical aberrations from the imaging system and the medium through which it is imaging. Simulation examples show that the multi-surface ranging algorithm derived in this work improves range estimation over standard Gaussian mixture modeling and frame-by-frame deconvolution by up to 89and 85respectively.

关键词：传感器；光学雷达；激光雷达；脉冲激光器

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The SWARMS project brings together experts in artificial intelligence, control theory, robotics, systems engineering and biology with the goal of understanding swarming behaviors in nature and applications of biologically-inspired models of swarm behaviors to large networked groups of autonomous vehicles. The main goal is to develop a framework and methodology for the analysis of swarming behavior in biology and the synthesis of bio-inspired swarming behaviors for engineered systems. We are interested in such questions as: Can large numbers of autonomously functioning vehicles be reliably deployed in the form of a 'swarm' to carry out a prescribed mission and to respond as a group to high-level management commands. Can such a group successfully function without a designated leader, with limited communications between its members, and with dynamically changing 'role', for its members. Is there a hierarchy of 'compatibls' models appropriate to swarming/schooling/flocking which is rich enough to explain these behaviors at various 'resolution' ranging from aggregate characterizations of emergent behavior to detailed descriptions which model individual vehicle dynamics.

关键词：传感器；仿生学；机器人；人工智能；自主导航

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Summary: Proof-of-concept of Artificial Hair Sensor with CNT mechano- resistive elements demonstrated. CNT arrays examined that initially appear mechanically different by length, but DIC reveal a common failure criteria. Observed carbon hair deflection in-phase with gust-like disturbances without vibration - mapped the flow regime steady/unsteady. Computed frequency response plots for carbon hair structure in quasi-steady regime 2nd order like response. Found that elasticity and drag dominated the force balance in the carbon hair structure. Established criteria based on dimensionless groups to control hair dynamic response through selection of material and geometric properties.

关键词：传感器；探测器；发动机空气系统组件；动力学

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Enhanced maritime situational awareness is a common need for maritime authorities interested in security, safety, border control, and marine environment protection. To have enhanced maritime situation awareness, it is recognized that there is a need for advanced and innovative surveillance and information-sharing technologies. This study presents an open and interoperable maritime surveillance framework that utilizes ontology-based operations and domain rules to integrate data from a combination of systems and sensors, and performs behavior analysis of detected targets of any size. In this system, seamless information exchange among systems and sensors leads to better and more cost-effective maritime surveillance. Behavioral analysis enables intelligent decision making and reduces time-to-act. Within the scope of this study, a Maritime Situational Awareness Ontology is created as a common model to mediate different information sources, and a rule repository is formed for storing suspicious vessel criteria. The presented work is undertaken within the scope of the RECONSURVE (Reconfigurable Surveillance System with Communicating Smart Sensors) project, which is supported by the EUREKA ITEA2 cluster.

关键词：传感器；决策支持系统；指挥控制系统；数据融合

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National defense security systems constantly face cyber attack, espionage, and hacking. The primary objective of this paper is to explore the application of a modified discrimination model to replace current encrypted user id and password authentication. This discrimination model will be based on minimum distance as compared to the traditional discrimination model which is based on maximum probability. The modified discrimination model treats user id and password as a multisensor information fusion technology problem. The model converts the input user id and password into a digital pattern feature vector. The model then processes the newly converted vector for distance between all known feature vectors stored in the secure knowledge database. The new pattern feature vector with the minimum distance generated by the modified discrimination model will be the authorized person. The new application is demonstrated using mathematical simulation, and is then verified by comparing its performance with the traditional multisensor correlation model.

关键词：传感器；计算机访问控制；计算机程序；数据融合

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Mass transport has generally been recognized as a major limiting factor in the sensitivity and performance of miniaturized sensor platforms. To overcome this limitation, a new approach, termed molecular dam, has been developed to enhance mass transport for protein enrichment in nanofluidic channels by nanoscale electrodeless dielectrophoresis under physiological buffer conditions. The researchers demonstrated protein enrichment factor to be greater than 105-fold in 20 seconds, which is orders of magnitude faster than most reported methods. They also studied the detailed mechanism as how the electrokinetic forces get balanced to achieve the molecular damming effect and the scaling relation of force and nanoconstriction size. Both the capillary- and electrokinetically-driven nanoslit sensor platforms have also been developed in parallel to enhance the reaction kinetics of protein sensing by reducing the diffusion length of reactants.

关键词：传感器；流体；纳米技术；生物标志物；纳米流体力学

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In many remote sensing applications, the area of a scene sensed by a single pixel can often be measured in square meters. This means that many objects of interest in a scene are smaller than a single pixel in the resulting image. Current tracking methods rely on robust object detection using multi- pixel features. A subpixel object does not provide enough information for these methods to work. This dissertation presents a method for tracking subpixel objects in image sequences captured from a stationary sensor that is critically sampled spatially. Using template matching, we estimate the maximum a posteriori probability of the target state over a sequence of images. A distance transform is used to calculate the motion prior in linear time, dramatically decreasing computation requirements. We compare the results of this method to a previously state-of-the-art track-before-detect particle filter designed for tracking small, low contrast objects using both synthetic and real-world imagery. Results show our method produces more accurate state estimates and higher detection rates than the current state of the art methods at signal-to-noise ratios as low as 3dB.

关键词：传感器；光学探测器；远程探测器；测量仪器；亚像素

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