Proceedings ArticleDOI
Managing landmine detection sensors: results from application to AMDS data
Mark P. Kolba,Leslie M. Collins +1 more
- Vol. 6553
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TLDR
The sequential probability ratio test (SPRT) developed by Wald is implemented within the previously developed sensor management framework to allow cell-level decisions of "target" or "no target" to be made based on the observed sensor data.Abstract:
Previous work by the authors using information-based sensor management for static target detection has utilized a
probability of error performance metric that assumes knowledge of the number of targets present in a grid of cells.
Using this probability of error performance metric, target locations are estimated as the N cells with the largest posterior
state probabilities of containing a target. In a realistic application, however, the number of targets is not known a priori.
The sequential probability ratio test (SPRT) developed by Wald is therefore implemented within the previously
developed sensor management framework to allow cell-level decisions of "target" or "no target" to be made based on
the observed sensor data. Using these cell-level decisions, more traditional performance metrics such as probability of
detection and probability of false alarm may then be calculated for the entire region of interest.
The resulting sensor management framework is implemented on a large set of data from the U.S. Army's autonomous
mine detection sensors (AMDS) program that has been collected using both ground penetrating radar (GPR) and
electromagnetic induction (EMI) sensors. The performance of the sensor manager is compared to two different direct
search techniques, and the sensor manager is found to achieve the same P d performance at a lower cost than either of the direct search techniques. Furthermore, uncertainty in the sensor performance characteristics is also modeled, and the
use of uncertainty modeling allows a higher P d to be obtained than is possible when uncertainty is not modeled within the sensor management framework.read more
Citations
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Dissertation
An Intelligent Sensor Management Framework for Pervasive Surveillance
TL;DR: The proposed SMF significantly enhances the process of information gathering by coordinating the sensing resources in order to collect the most reliable data from a dynamic scene while operating under energy constraints.
Proceedings ArticleDOI
Fusion Techniques for Hybrid Ground Penetrating Radar - Electromagnetic Induction Landmine Detection Systems
TL;DR: Algorithm development and fusion will be discussed, with an aim at achieving a threshold probability of detection (PD) of 0.98 with a low false alarm rate (FAR) of less than 1 false alarm per 2 square meters.
Journal ArticleDOI
A Collaborative Energy-Aware Sensor Management System Using Team Theory
Allaa R. Hilal,Otman A. Basir +1 more
TL;DR: A team-theoretic formulation based on the Belief-Desire-Intention (BDI) model and the Joint Intention theory is proposed as a mechanism for effective and energy-aware collaborative decision-making and shows that the proposed approach has 12 × less energy consumption than that of the popular centralized approach.
Journal ArticleDOI
A Scalable Sensor Management Architecture Using BDI Model for Pervasive Surveillance
Allaa R. Hilal,Otman A. Basir +1 more
TL;DR: This paper introduces a scalable and flexible SMA for many sensor management applications, particularly, pervasive surveillance, called the extended hybrid architecture for SM (E-HASM), an architecture that combines the advantages of the holonic, federated, and market-based paradigms.
Proceedings ArticleDOI
Sensor management for landmine detection using correlated sensor observations
Mark P. Kolba,Leslie M. Collins +1 more
TL;DR: This paper alters the modeling framework that has been used previously to incorporate observation correlation, which will more realistically model the interrelationships between sensor observations, and presents results that compare the performance of the sensor manager to theperformance of an unmanaged direct search procedure.
References
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Journal ArticleDOI
Optimum Character of the Sequential Probability Ratio Test
Abraham Wald,Jacob Wolfowitz +1 more
TL;DR: In this article, it was shown that the sequential probability ratio test for deciding between two simple alternatives (H_0 and H_1) requires on the average fewest observations.
Journal ArticleDOI
Multitarget tracking using the joint multitarget probability density
TL;DR: This work addresses the problem of tracking multiple moving targets by recursively estimating the joint multitarget probability density (JMPD) and gives an implementation of the JMPD method based on particle filtering techniques and provides an adaptive sampling scheme which explicitly models the multitarget nature of the problem.
Journal ArticleDOI
Discrimination gain to optimize detection and classification
TL;DR: A method for managing agile sensors to optimize detection and classification based on discrimination gain is presented, used to determine threshold settings and search order for a collection of discrete detection cells in a low signal-to-noise environment.
Journal ArticleDOI
Covariance control for multisensor systems
TL;DR: This work extends the methods developed in single-sensor management schemes to a multisensor application using an approach known as covariance control, which selects sensor combinations based on the difference between the desired covariance matrix and that of the predicted covariance of each target.
Proceedings ArticleDOI
Chasing the elusive sensor manager
S. Musick,R. Malhotra +1 more
TL;DR: In this article, the authors discuss the problem of data fusion in a modern tactical aircraft, focusing first on the problem it poses in modern aircraft and then on attributes that would be desirable in an effective sensor manager.