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Due to advances in sensors and communications there has been an increase in data available to Naval Anti-Submarine Warfare tactical systems. Starting with paper plots, expanding to electronic displays and leading to current interactive assistance tools, these systems have evolved to handle the challenge of realizing the potential increase in Situational Awareness that increased data provides without...
An efficient centralized track initiation method for multistatic radar system is proposed in this paper. The method mainly consists of a same source association technique and a measurement fusion approach. The main advantage of the new method is its good performance of dealing with large measuring deviation and high false alarm rate environment, when compared with other existing track initiation methods...
Lee and Thomas (1984) have introduced a modified version of Wald's sequential probability ratio test. The modified version retains most of the features of Wald's procedure but is easier to analyze and offers efficient truncation procedures. In this study, we use the Lee-Thomas design to analyze the performance of a bank of M parallel sequential sensors whose decisions are fused. We evaluate the performance...
Superpixel methods have become popular in recent years as they provide an efficient preprocessing tool for a manifold of computer vision applications. In this work, we propose a method based on a self-adapting and self-growing network, which is bred starting from two random initialization seeds in the image. Such a network, which is a modification of the Instantaneous Topological Map (ITM), is inspired...
High accuracy navigation usually require expensive sensors and/or its careful integration into a complex and finely tuned system. Smartphones pack a high number of sensors in a portable format, becoming a source of low-quality information with a high heterogeneity and redundancy. This work compares pure GNSS/INS capabilities on both types of platform, and discuss the weaknesses/opportunities offered...
This paper addresses the problem of conflict detection & resolution for air traffic control based on trajectory information processing. Most probabilistic methods for estimating the probability of conflict (PC) in the literature assume a Gaussian distribution of the predicted separation vector between two aircraft. In an advanced multiple model trajectory prediction framework, however, this separation...
The selection of the minimum number of sensors within a network to satisfy a certain estimation performance metric is an interesting problem with a plethora of applications. We have recently explored the sparsity embedded within this problem and have proposed a relaxed sparsity-aware sensor selection (SparSenSe) approach as well as a distributed version of it. In this paper, we generalize our recently...
Maritime Situational Awareness (MSA), the capability of understanding events, circumstances and activities within and impacting the maritime environment, can be greatly improved by the automatic identification and classification of vessel activity. Enhancing coverage of existing technologies such as Automatic Identification System (AIS) provides the possibility to integrate and enrich services and...
Before a sensor network can be used for target localization, the locations of the sensors need to be determined. We approach this calibration step by moving a source to distinct positions around the network. At each position, the range to each sensor is measured, and from these range measurements the sensor locations can be estimated by solving a nonlinear least squares (NLS) problem. Here we formulate...
When Dempster's rule is applied to combine two bodies of evidence, a counterintuitive result may be generated sometimes no matter the conflict is high or not. Two such kinds of emblematic examples are reviewed and analyzed further using the canonical decomposition. By generalizing these examples, a theorem is proposed to classify various counter examples into three cases. It is believed that an unreasonable...
This work proposes a novel way to represent uncertainty on the Lie group of rigid-body motions in the plane. This is achieved by using dual quaternions for representation of a planar rigid-body motion and proposing a probability distribution from the exponential family of distributions that inherently respects the underlying structure of the representation. This is particularly beneficial in scenarios...
Investigating terrorist activity patterns and predicting threats involve collecting and analyzing data from both hard sensors and humans as part of analysts' reasoning process (evidence building, hypothesis creation and testing and decision making). Although automated data fusion methods have been proposed in previous studies, they tend to operate on low-level linguistic features of events and fail...
In recent years there has been an increase in the number of inactive and debris objects in space. The characterization of the uncertainty in the knowledge of these Space Objects (SOs) is very important in developing an understanding of the space debris fields and any present or future threat they may pose. This work examines classification based on Multiple Model Adaptive Estimation (MMAE) to extract...
Object detection and tracking are two important research topics in surveillance systems. Object detection and tracking are typically implemented separately and object tracking is usually performed after the object is detected. This two-stage approach may not work well when the object has a very low signal to noise ratio (SNR), and cannot be reliably detected using a single sample. In this paper, a...
Extended target tracking arises in situations where the resolution of the sensor is high enough to allow multiple returns from the target of interest corresponding to its different parts. Various formulations and solutions may be found in the literature. We concentrate on the data association aspect involved in the tracking problem and propose utilization of a general framework that allows reformulation...
The sparse grid quadrature filter is a point-based Gaussian filter in which expectations of nonlinear functions of Gaussian random vectors are computed using the sparse grid quadrature. The sparse grid quadrature can be considered a generalization of the Unscented Transform in that the Unscented Transform is equivalent to the level-2 sparse grid quadrature. A novel extension of the sparse grid quadrature...
The theory of belief functions is one of the most important tools in information fusion and uncertainty reasoning. Dempster's rule of combination and its related modified versions are used to combine independent pieces of evidence. However, until now there is still no solid evaluation criteria and methods for these combination rules. In this paper, we look on the evidence combination as a procedure...
Tracking of airborne vehicles using distributed acoustic arrays is considered here. Three tetrahedral acoustic arrays are distributed over roughly 1.5 sq. miles area to track a helicopter. The bearing angles are estimated at the significant harmonics of the fundamental frequency of the helicopter rotor using multiple signal classification (MUSIC). Some of the issues using the bearing estimates at...
A new self-adaptive fusion algorithm based on DST and DSmT is proposed. In the new algorithm, part of the conflicting information is normalized according to DST, while the other part is processed by DSmT. A controlling factor is used to control the quantity of information dealt by the two different methods adaptively, which is a new method avoiding setting for the threshold of conflict. The simulation...
Indoor parking localization systems face two major challenges: the absence of GPS coverage and the dynamic character of the parking environment. The absence of GPS coverage can be compensated by data fusion of several sensors in order to localize an object in a map of the environment. However, this map may constantly change due to the dynamic nature of a parking garage. This paper describes an improvement...
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