945 resultados para Time of Arrival Method


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The time-of-detection method for aural avian point counts is a new method of estimating abundance, allowing for uncertain probability of detection. The method has been specifically designed to allow for variation in singing rates of birds. It involves dividing the time interval of the point count into several subintervals and recording the detection history of the subintervals when each bird sings. The method can be viewed as generating data equivalent to closed capture–recapture information. The method is different from the distance and multiple-observer methods in that it is not required that all the birds sing during the point count. As this method is new and there is some concern as to how well individual birds can be followed, we carried out a field test of the method using simulated known populations of singing birds, using a laptop computer to send signals to audio stations distributed around a point. The system mimics actual aural avian point counts, but also allows us to know the size and spatial distribution of the populations we are sampling. Fifty 8-min point counts (broken into four 2-min intervals) using eight species of birds were simulated. Singing rate of an individual bird of a species was simulated following a Markovian process (singing bouts followed by periods of silence), which we felt was more realistic than a truly random process. The main emphasis of our paper is to compare results from species singing at (high and low) homogenous rates per interval with those singing at (high and low) heterogeneous rates. Population size was estimated accurately for the species simulated, with a high homogeneous probability of singing. Populations of simulated species with lower but homogeneous singing probabilities were somewhat underestimated. Populations of species simulated with heterogeneous singing probabilities were substantially underestimated. Underestimation was caused by both the very low detection probabilities of all distant individuals and by individuals with low singing rates also having very low detection probabilities.

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In this paper we characterize the relative sensor-target geometry in R2 in terms of potential localization performance for time-of-arrival based localization. Our aim is to characterize those relative sensor-target geometries which minimize the relative Cramer-Rao lower bound.

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This paper looks at the theoretical conditions underpinning unique localization of synchronized multiple emitters using Time-of-Arrival measurements subjected to the data-association problem. The necessary fundamental requirements to solve the so-called ghost node problem associated with sensor arrays are examined. We derive a measurement bound for ideal situations and the underlying concepts are illustrated via simulations.

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Previous research studies and operational trials have shown that using the airborne Required Time of Arrival (RTA) function, an aircraft can individually achieve an assigned time to a metering or merge point accurately. This study goes a step further and investigates the application of RTA to a real sequence of arriving aircraft into Melbourne Australia. Assuming that the actual arrival times were Controlled Time of Arrivals (CTAs) assigned to each aircraft, the study examines if the airborne RTA solution would work. Three scenarios were compared: a baseline scenario being the actual flown trajectories in a two hour time-span into Melbourne, a scenario in which the sequential landing slot times of the baseline scenario were assigned as CTAs and a third scenario in which the landing slots could be freely redistributed to the inbound traffic as CTAs. The research found that pressure on the terminal area would sometimes require aircraft to lose more time than possible through the RTA capability. Using linear holding as an additional measure to absorb extensive delays, up to 500NM (5%) of total track reduction and 1300kg (3%) of total fuel consumption could be saved in the scenario with landing slots freely distributed as CTAs, compared to the baseline scenario. Assigning CTAs in an arrival sequence requires the ground system to have an accurate trajectory predictor to propose additional delay measures (path stretching, linear holding) if necessary. Reducing the achievable time window of the aircraft to add control margin to the RTA function, had a negative impact and increased the amount of intervention other than speed control required to solve the sequence. It was concluded that the RTA capability is not a complete solution but merely a tool to assist in managing the increasing complexity of air traffic.

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Managing the sustainability of urban infrastructure requires regular health monitoring of key infrastructure such as bridges. The process of structural health monitoring involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors, and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures, and acoustic emission is one technique that is finding an increasing use in the monitoring of civil infrastructures such as bridges. Acoustic emission technique is based on the recording of stress waves generated by rapid release of energy inside a material, followed by analysis of recorded signals to locate and identify the source of emission and assess its severity. This chapter first provides a brief background of the acoustic emission technique and the process of source localization. Results from laboratory experiments conducted to explore several aspects of the source localization process are also presented. The findings from the study can be expected to enhance knowledge of the acoustic emission process, and to aid the development of effective bridge structure diagnostics systems.

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提出一种基于TOA(tim e of arrival)测距、利用节点之间的几何关系实现传感器网络中未知节点自定位的算法.该方法计算量小、算法简单且定位精度高.仿真实验证明了该方法的有效性.*

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This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

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Scoparone (6,7-dimethoxycoumarin) is known to have a wide range of pharmacological properties. In this study, a rapid and validated ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry (UPLC/ESI-QTof-MS) method was developed to investigate the metabolism of scoparone in rat for the first time. The new method reduced the sample handling and analytical time by three- to six-fold, and the detection limit by five- to 1000-fold, compared to published methods. Far more metabolites were detected and identified compared to published data, which were preliminarily identified as scopoletin, isoscopoletin, isofraxidin, and fraxidin, respectively, when subjected to tandem mass spectrometry analyses. It is found that the metabolic trajectory of scoparone in rat focused on phase I metabolism which is obviously different from published results, and revealed a wide range of pharmacological properties of scoparone partly attributed to the bioactivities of its metabolites.

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Liuwei Dihuang Wan (LWD), a classic Chinese medicinal formulae, has been used to improve or restore declined functions related to aging and geriatric diseases, such as impaired mobility, vision, hearing, cognition and memory. It has attracted increasingly much attention as one of the most popular and valuable herbal medicines. However, the systematic analysis of the chemical constituents of LDW is difficult and thus has not been well established. In this paper, a rapid, sensitive and reliable ultra-performance liquid chromatography with electrospray ionization quadrupole time-of-flight high-definition mass spectrometry (UPLC-ESI-Q-TOF-MS) method with automated MetaboLynx analysis in positive and negative ion mode was established to characterize the chemical constituents of LDW. The analysis was performed on a Waters UPLCTM HSS T3 using a gradient elution system. MS/MS fragmentation behavior was proposed for aiding the structural identification of the components. Under the optimized conditions, a total of 50 peaks were tentatively characterized by comparing the retention time and MS data. It is concluded that a rapid and robust platform based on UPLC-ESI-Q-TOF-MS has been successfully developed for globally identifying multiple-constituents of traditional Chinese medicine prescriptions. This is the first report on systematic analysis of the chemical constituents of LDW. This article is protected by copyright. All rights reserved.

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A modified linear prediction (MLP) method is proposed in which the reference sensor is optimally located on the extended line of the array. The criterion of optimality is the minimization of the prediction error power, where the prediction error is defined as the difference between the reference sensor and the weighted array outputs. It is shown that the L2-norm of the least-squares array weights attains a minimum value for the optimum spacing of the reference sensor, subject to some soft constraint on signal-to-noise ratio (SNR). How this minimum norm property can be used for finding the optimum spacing of the reference sensor is described. The performance of the MLP method is studied and compared with that of the linear prediction (LP) method using resolution, detection bias, and variance as the performance measures. The study reveals that the MLP method performs much better than the LP technique.

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A quasi-steady time domain method is developed for the prediction of dynamic behavior of a mooring system under the environmental disturbances, such as regular or irregular waves, winds and currents. The mooring forces are obtained in a static sense at each instant. The dynamic feature of the mooring cables can be obtained by incorporating the extended 3-D lumped-mass method with the known ship motion history. Some nonlinear effects, such as the influence of the instantaneous change of the wetted hull surface on the hydrostatic restoring forces and Froude-Krylov forces, are included. The computational results show a satisfactory agreement with the experimental ones.

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his paper proposes an optimisation-based method to calculate the critical slip (speed) of dynamic stability and critical clearing time (CCT) of a self-excited induction generator (SEIG). A simple case study using the Matlab/Simulink environment has been included to exemplify the optimisation method. Relationships between terminal voltage, critical slip and reactance of transmission line, CCT and inertial constant have been determined, based on which analysis of impact on relaying setting has been further conducted for another simulation case.