Showing papers on "Wireless sensor network published in 1987"

Distributed Multiple Model Estimation

Abstract: A distributed estimation algorithm for discrete time systems with multiple models described by Markovian parameters is presented. Several approaches have been proposed for the multiple model problem, however, they assume a centralized processing architecture in which all the measurements are sent to and processed at a central node. In this paper, the problem of constructing the global conditional pdf of states and model parameters by fusing the local pdfs from multiple nodes is considered. The results can be applied to multi-target tracking with maneuvers in distributed sensor networks.

Tracking Multiple Air Tragets with Distributed Acoustic Sensors

Abstract: The tracking of multiple air targets by a network of distributed acoustic sensor/processor nodes is considered. Since each sensor measures only the acoustic azimuths of the targets, cooperation among nodes in the distributed sensor network (DSV) is needed. A multiple-hypothesis approach to distributed tracking is used. Each sensor/processor forms hypotheses consisting of local azimuth and azimuth rate tracks for the targets. When the nodes communicate, hypotheses consisting of global position and velocity tracks are then formed. Simulation results for a network of several nodes are presented to illustrate the algorithms.

An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

Abstract: A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SMC filling coverage holes and countering jamming; and evaluating sensor status. The paper will describe the architecture used for the expert system and the reasons for selecting the chosen methods. The SM&C simulation produces a graphical representation of sensors and their associated tracks such that the benefits of the sensor management and control expert system are evident. Jammer locations are also part of the display. The paper will describe results from several scenarios that best illustrate the sensor management and control concepts.

Progress In Otdr Optical Fiber Sensor Networks

Abstract: There is great interest for distributed or multiplexed fiber optic sensor networks for process control automation Optical Time Domain Reflectometry (OTDR) is a potentially very useful method for monitoring several sensors distributed along a fiber, but its actual capabilities, using present concepts, are too restricted to allow competitive industrial performance We present here a novel scheme of OTDR fiber sensor multiplexing which allows, ,the monitoring of up to 50 ON/OFF switches along a given fiber under practical and realistic conditions Detection of reflected, rather than backscattered, light makes much better use of the in-line loss introduced by each sensor, yielding a larger dynamic range which explains this very significant improvement in the number of multiplexed sensors Theoretical considerations about this novel scheme and its limits, taking into account present OTDR technology, are presented together with experimental results of a twenty ON/OFF sensor network feasibility prototype

On Hypothesis Testing in Distributed Sensor Networks.

Abstract: : In this report, some hypothesis testing problems in distributed sensor networks are considered. Optimum data fusion rules are obtained when the decision rules at the detectors are known. The distributed hypothesis testing problem with a distributed data fusion is solved using the Bayesian as well as the Neyman-Pearson approach. The decentralized Neyman-Pearson hypothesis testing problem and the sequential hypothesis testing problem for a tandem topology network are investigated. The distributed sequential probability ratio test problem is also studied. In all these problems, optimal strategies at each site and at each time stage are obtained. Keywords include: Fusion, Surveillance, Remote Receivers, Detection, and Estimation. (r.h.)