基于UML的C4ISR传感器动态处理模型仿真

现代军事仿真需要建立军事对抗活动中的各类模型，包括武器平台模型、作战模型以及决策模型等，传感器功能仿真模型在系统的开发和研制过程中具有重要意义。如何建立出有效的传感器处理模型来保证信息输入的可靠性和真实性是各类C^4ISR系统都面临的问题，使用统一建模语言（UML）对传感器处理模型进行可视化建模，首先使用用例图和顺序图对C^4ISR系统中2维或者3维传感器工作流程建模，然后使用活动图对整个处理流程和每个处理流程来描述问题的细节，为系统分析员、设计人员和开发人员提供了不同的分析问题、解决问题的视角，使从事C^4ISR系统传感器仿真研究的相关人员可以参考该文提出的模型进行软件开发。     

Layout optimization of an inertial energy harvester for miniature underwater mooring platforms

Comprehensive analyses of the layout influence on power performance of a low-frequency miniature horizontal-pendulum-type inertial energy harvester for underwater mooring platforms are presented in this article. The mathematical models are obtained utilizing the Newton-Euler method. The power performance is evaluated by simulations over different parameters, such as damping, excitation frequency, and layout position. Simulation results indicate that the harvester can extract energy from low-frequency excitations over the range of 0.1 Hz–0.4 Hz, and maximum output power can reach to 0.7 W under excitation frequency f = 0.4 Hz. Different layout positions influence the energy harvesting performance of the harvester dramatically. Changing the layout position to positive value can enhance and broaden the power performance. The amplitude responses with different layout positions do not show resonant characteristics, even near the natural frequency of the harvester, due to large amplitude vibrations and strong nonlinear characteristic. As excitation frequency f = 0.4 Hz, there is a zero output power point appears at layout position d = −1.3 m. Moreover, the harnessed power has a quadratic relationship with the layout position value.     

Insights into vehicle trajectories at the handling limits: analysing open data from race car drivers

Race car drivers can offer insights into vehicle control during extreme manoeuvres; however, little data from race teams is publicly available for analysis. The Revs Program at Stanford has built a collection of vehicle dynamics data acquired from vintage race cars during live racing events with the intent of making this database publicly available for future analysis. This paper discusses the data acquisition, post-processing, and storage methods used to generate the database. An analysis of available data quantifies the repeatability of professional race car driver performance by examining the statistical dispersion of their driven paths. Certain map features, such as sections with high path curvature, consistently corresponded to local minima in path dispersion, quantifying the qualitative concept that drivers anchor their racing lines at specific locations around the track. A case study explores how two professional drivers employ distinct driving styles to achieve similar lap times, supporting the idea that driving at the limits allows a family of solutions in terms of paths and speed that can be adapted based on specific spatial, temporal, or other constraints and objectives.     

惯导系统初始对准自适应参数选取法研究

平台式惯导系统的初始对准,为进入导航状态提供必要的初始条件,主要的性能指标是对准精度和时间。本文提出了一种新的变频带对准法的三阶调平系统,在对准过程中,系统的带宽能适应调平过程中信噪比的变化,从而使性能达到最优,经理论分析和仿真研究表明,这种新方法比经典方法,调平速度快而且提高了水平陀螺测漂及方位角的估值的精度。     

桥梁监测系统中复杂结构的静力应变传感器优化配置方法

在桥梁结构状态监测评估系统中,传感器优化配置问题是监测信息经济可靠的关键,也是业内广泛关注的热点问题之一。本文以复杂桥梁结构为研究对象,提出了一套基于关心截面插值拟合误差最小准则的传感器优化配置方法,并通过实例介绍了该方法的优化步骤及验证了其有效性。     

Autonomous vehicle perception: The technology of today and tomorrow

Perception system design is a vital step in the development of an autonomous vehicle (AV). With the vast selection of available off-the-shelf schemes and seemingly endless options of sensor systems implemented in research and commercial vehicles, it can be difficult to identify the optimal system for one’s AV application. This article presents a comprehensive review of the state-of-the-art AV perception technology available today. It provides up-to-date information about the advantages, disadvantages, limits, and ideal applications of specific AV sensors; the most prevalent sensors in current research and commercial AVs; autonomous features currently on the market; and localization and mapping methods currently implemented in AV research. This information is useful for newcomers to the AV field to gain a greater understanding of the current AV solution landscape and to guide experienced researchers towards research areas requiring further development. Furthermore, this paper highlights future research areas and draws conclusions about the most effective methods for AV perception and its effect on localization and mapping. Topics discussed in the Perception and Automotive Sensors section focus on the sensors themselves, whereas topics discussed in the Localization and Mapping section focus on how the vehicle perceives where it is on the road, providing context for the use of the automotive sensors. By improving on current state-of-the-art perception systems, AVs will become more robust, reliable, safe, and accessible, ultimately providing greater efficiency, mobility, and safety benefits to the public.     

Privacy protection method for fine-grained urban traffic modeling using mobile sensors

With the ubiquitous nature of mobile sensing technologies, privacy issues are becoming increasingly important, and need to be carefully addressed. Data needs for transportation modeling and privacy protection should be deliberately balanced for different applications. This paper focuses on developing privacy mechanisms that would simultaneously satisfy privacy protection and data needs for fine-grained urban traffic modeling applications using mobile sensors. To accomplish this, a virtual trip lines (VTLs) zone-based system and related filtering approaches are developed. Traffic-knowledge-based adversary models are proposed and tested to evaluate the effectiveness of such a privacy protection system by making privacy attacks. The results show that in addition to ensuring an acceptable level of privacy, the released datasets from the privacy-enhancing system can also be applied to urban traffic modeling with satisfactory results. Albeit application-specific, such a “Privacy-by-Design” approach would hopefully shed some light on other transportation applications using mobile sensors.     

Real time queue length estimation for signalized intersections using travel times from mobile sensors

We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation.     

Initial results from long-term measurements of atmospheric humidity and related parameters in the marine boundary layer at two locations in the Gulf of Mexico

Measurements of boundary layer moisture have been acquired from Rotronic MP-100 sensors deployed on two NDBC buoys in the northern Gulf of Mexico from June through November 1993. For one sensor, which was retrieved approximately 8 months after deployment, the post- and precalibrations agreed closely and fell well within WMO specifications for accuracy. The second sensor operated continuously from June 1993 to February 1997 (3.5 years). Buoy observations of relative humidity and supporting data were used to calculate specific humidity and the surface fluxes of latent and sensible heat. Specific humidities from the buoys were compared with observations of moisture obtained from nearby ship reports, and the correlations were generally high (0.7–0.9). Surface gravity wave spectra were also acquired. The time series of specific humidity and the other buoy parameters revealed three primary scales of variability, small (h), synoptic (days), and seasonal (months). The synoptic variability was clearly dominant and occurred primarily during September, October, and November. Most of the synoptic variability was due to frontal systems that dropped down into the Gulf of Mexico from the continental US followed by air masses which were cold and dry. Cross-correlation analyses of the buoy data indicated that: (1) the moisture field was highly coherent over distances of 800 km or more in the northern Gulf of Mexico; and (2) both specific humidity and air temperature served as tracers of the motion associated with propagating atmospheric disturbances. These correlation analyses also revealed that the prevailing weather systems generally entered the buoy domain from the South prior to September, but primarily from the North thereafter. Spectra of the various buoy parameters indicated strong diurnal and semidiurnal variability for barometric pressure and sea surface temperature (SST) and lesser variability for air temperature, wind speed and significant wave height. The surface fluxes of latent and sensible heat were dominated by the synoptic events which took place from September through November with the transfer of latent heat being primarily from the ocean to the atmosphere. Finally, an analysis of the surface wave observations from each buoy, which included calculations of wave age and estimates of surface roughness, indicate that major heat and moisture flux events coincide with periods of active wave growth, although the data were insufficient to identify any causal relationships.     

基于GPRS的振弦式传感器测频系统

针对传统桥粱振动频率测量系统存在数据采集实时性差的缺点，提出基于GPRS无线网络的数据采集方法。以Atmega128单片机为现场数据采集端的MCU，并以MC35为GPRS Modem来实现与互联网接入，将GPRS无线技术引入桥梁安全检测测频系统，非常适用于要求实时性的、大数据量传送的远程数据监控系统应用场合。