Bio: R.G. Stansfield is an academic researcher. The author has contributed to research in topic(s): Position (vector). The author has an hindex of 1, co-authored 1 publication(s) receiving 212 citation(s).
Topics: Position (vector)
TL;DR: In this paper, it was shown that the reliability of a fix does not depend on the size of the particular "cocked hat" from which it is derived, and the reciprocal of the root-mean-square error expected in the position of the fix should be adopted as the conventional standard quantity for measuring the reliability.
Abstract: The paper deals with the location of an object of u nknown position, on which bearings are taken from two or more stations whose positions are known, and provides solutions to the two problems:-(a) Given a set of bearings, what is the most probable position of the object?(b) How far from the true position is the position indicated by the “fix” likely to be?Diagrams are given to show the results of applying the theory to typical practical cases.It is shown that, subject to certain qualifications, reliability of a fix does not depend on the size of the particular “cocked hat” from which it is derived.It is proposed that the reciprocal of the root-mean-square error expected in the position of the fix should be adopted as the conventional standard quantity for measuring the reliability of a fix.
TL;DR: The U.S. National Lightning Detection Network (NLDN) has provided real-time and historical lightning data to the electric utility industry, the National Weather Service, and other government and commercial users.
Abstract: The U.S. National Lightning Detection Network TM (NLDN) has provided lightning data covering the continental United States since 1989. Using information gathered from more than 100 sensors, the NLDN provides both real-time and historical lightning data to the electric utility industry, the National Weather Service, and other government and commercial users. It is also the primary source of lightning data for use in research and climatological studies in the United States. In this paper we discuss the design, implementation, and data from the time-of-arrival/magnetic direction finder (TOA/MDF) network following a recent system-wide upgrade. The location accuracy (the maximum dimension of a confidence region around the stroke location) has been improved by a factor of 4 to 8 since 1991, resulting in a median accuracy of 500 m. The expected flash detection efficiency ranges from 80% to 90% for those events with peak currents above 5 kA, varying slightly by region. Subsequent strokes and strokes with peak currents less than 5 kA can now be detected and located; however, the detection efficiency for these events is not quantified in this study because their peak current distribution is not well known.
TL;DR: In this article, the authors proposed an approach based on maximizing the determinant of the Fisher information matrix (FIM) subject to state constraints imposed on the observer trajectory (e.g., by the target defense system).
Abstract: The problem of bearings-only target localization is to estimate the location of a fixed target from a sequence of noisy bearing measurements. Although, in theory, this process is observable even without an observer maneuver, estimation performance (i.e., accuracy, stability and convergence rate) can be greatly enhanced by properly exploiting observer motion to increase observability. This work addresses the optimization of observer trajectories for bearings-only fixed-target localization. The approach presented herein is based on maximizing the determinant of the Fisher information matrix (FIM), subject to state constraints imposed on the observer trajectory (e.g., by the target defense system). Direct optimal control numerical schemes, including the recently introduced differential inclusion (DI) method, are used to solve the resulting optimal control problem. Computer simulations, utilizing the familiar Stansfield and maximum likelihood (ML) estimators, demonstrate the enhancement to target position estimability using the optimal observer trajectories.
TL;DR: This work considers the problem of selecting the best nodes for localizing (in the mean squared position error sense) a target in a distributed wireless sensor network and introduces different computationally efficient node selection approaches that use global network knowledge.
Abstract: This paper discusses a new localized resource manager for a wireless sensor network of bearings-only sensors. Specifically, each node uses knowledge of the target under surveillance to determine whether it should actively collect measurements and how far to disseminate the data in order for the sensor network to maintain track of the target. At each node, the resource manager requires only knowledge of the relative location to the target for itself and the active nodes from the previous snapshot. The decentralized strategy represents a modification to the global node selection (GNS) method that exploits knowledge of the location of all nodes in the network. Simulations show that despite the lack of global network knowledge, the new localized management method is almost as effective as GNS in terms of balancing the tradeoff between energy usage and localization accuracy.
TL;DR: The US National Lightning Detection Network/sup TM/ (NLDN) as mentioned in this paper is a system that senses the electromagnetic fields that are radiated by individual return strokes in cloud-to-ground (CG) flashes.
Abstract: Lightning is a significant cause of interruptions or damage in almost every electrical or electronic system that is exposed to thunderstorms. The problem is particularly severe for electric power utilities that have exposed assets covering large areas. We summarize the basic properties of cloud-to-ground (CG) lightning, the primary hazard to structures on the ground, and then we discuss methods of detecting and locating such discharges. We describe the US National Lightning Detection Network/sup TM/ (NLDN), a system that senses the electromagnetic fields that are radiated by individual return strokes in CG flashes. This network provides data on the time of such strokes, their location and polarity and an estimate of the peak current. We discuss the network detection efficiency and location accuracy and some of the limitations that are inherent in any detection system that operates with a finite number of sensors with fixed trigger thresholds. We also discuss how NLDN data have benefited utilities by providing lightning warnings in real time and information on whether CG strokes are the cause of faults, documenting the response of fixed assets that are exposed to lightning, and quantifying the effectiveness of lightning protection systems. We conclude with some general observations on the use of lightning data by power utilities and we provide some guidelines on the uncertainties in lightning parameters that are acceptable in the industry.
TL;DR: A single-step approach based on the maximum likelihood criterion is proposed here for both known and unknown waveforms and it is shown that in some cases of interest the proposed method inherently selects reliable observations while ignoring unreliable data.
Abstract: Several techniques for emitter localization based on the Doppler effect have been described in the literature. One example is the differential Doppler (DD) method in which the signal of a stationary emitter is intercepted by at least two moving receivers. The frequency difference between the receivers is measured at several locations along their trajectories and the emitter's position is then estimated based on these measurements. This two-step approach is suboptimal since each frequency difference measurement is performed independently, although all measurements correspond to a common emitter position. Instead, a single-step approach based on the maximum likelihood criterion is proposed here for both known and unknown waveforms. The position is determined directly from all the observations by a search in the position space. The method can only be used for narrowband signals, that is, under the assumption that the signal bandwidth must be small compared to the inverse of the propagation time between the receivers. Simulations show that the proposed method outperforms the DD method for weak signals while both methods converge to the Cramer-Rao bound for strong known signals. Finally, it is shown that in some cases of interest the proposed method inherently selects reliable observations while ignoring unreliable data.