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Today due to the importance and necessity of implementing security systems in homes and buildings with the capability of higher certainty and lower cost, sensor fusion methods as applicable and high performance methods are attracting the researchers' attention. In this paper, the application of Dempster-Shafer evidential theory and the more general and newer one Dezert-Smarandache theory for implementing...
In this paper, we address the problem of representing domain knowledge for situation awareness in a security application. While ontologies are appropriate for describing taxonomical knowledge, they cannot express more complex knowledge such as entailments. In this paper, we describe how domain knowledge can be encoded through OWL ontologies and SWRL rules in order to reason about the entities and...
A technique is proposed to extract system requirements for a maritime area surveillance system, based on an activity recognition framework originally intended for the characterisation, prediction and recognition of intentional actions for threat recognition. To illustrate its utility, a single use case is used in conjunction with the framework to solicit surveillance system requirements.
Multiplicative noise makes the interpretation of image extremely difficult, and the fixed-size window filters cannot achieve good trade-off between noise suppression and edge keeping. Based on adaptive windowing and local structure detection, a new filtering algorithm of multiplicative noise is developed in this paper. The sliding window size is automatically adjusted by adaptive windowing, and the...
This paper presents a method for identifying dynamic models of autonomous underwater vehicles (AUV) from logged data and a physically motivated model structure. Such models are instrumental for model-based control system design, but also for integrated navigation systems. We motive our work from the perspective of developing second generation integrated navigation systems, which use a sensor fusion...
This paper studies the notion of information evaluation in fusion. It starts from some recommendations defined by NATO relatively to information evaluation in intelligence. It shows that these recommendations, even if imprecise and ambiguous, point out three notions which should be taken into account in order to define information evaluation. It proposes a model of information evaluation, which takes...
The idea of particle filter is to represent probability density function (PDF) of nonlinear/non-Gaussian system by a set of random samples. One of the key issue of particle filter is the proposal distribution. In this paper, the iterated unscented Kalman filter (IUKF) is used to generate the proposal distribution for particle filter. The proposal distributions integrate the current observation, thus...
The paper presents a spatial-color model of object and develops an efficient visual tracking algorithm based on particle filter. This spatial-color model captures richer information than the general color histogram because it incorporates spatial distribution of pixels in addition to color. In order to fast compute the weight of each particle, the Integral Images for computation of histogram, mean...
In this paper a comparison is made between a sensor selection algorithm (SSA) based on the modified Riccati equation (MRE) on the one hand, and a random sensor selection (RSS) or a fixed sensor selection (FSS) scheme on the other hand. The goal is to investigate the benefits the MRE SSA yields compared to the other selection schemes. The MRE SSA is capable of handling sensors with probability of detection...
This work addresses the design of a distributed fault-tolerant decision fusion in the presence of sensor faults when the local sensors sequentially send their decisions to a fusion center. A collaborative sensor fault detection (CSFD) scheme is proposed here to eliminate unreliable local decisions when performing distributed decision fusion. Based on the pre-designed fusion rule, assuming identical...
The estimation of Markov jump systems (MJS) is widely used in target tracking, fault detection, signal processing and digital communications. However, the above researches all assume that state measurement and additional mode observation are synchronous which means both state measurement and mode observation at each sampling time arrive at the fusion centre at the same time. The problem of estimation...
The problem is joint detection and tracking of possibly several objects moving through a region of interest. A wireless sensor network (WSN), deployed in the region, collects the acoustic energy measurements and sends them to the fusion center for processing. The problem is cast in the sequential Bayesian estimation framework and solved using a particle filter. The number of objects is unknown and...
This paper will specifically undertake the task of improving the passive sonar system using self-organizing map. Localizing multiple targets is a challenging problem as passive sonar sensors are only able to detect the targets' bearing angle. An effective way to find the targets location is by triangulation. However, in multi-sensor multi-target environment, ghost targets are introduced during the...
Recently, a number of studies have demonstrated that thermal infrared (IR) imagery offers a promising alternative to visible imagery in face recognition problems due to its invariance to visible illumination changes. However, thermal IR has other limitations including that it is opaque to glass. As a result, thermal IR imagery is very sensitive to facial occlusion caused by eyeglasses. Fusion of the...
Based on the concept of sequential importance sampling (SIS) and the use of Bayesian theory, particle filter is particularly useful in dealing with nonlinear and non-Gaussian problems. In this paper, a new particle filter is proposed that uses a divided difference filter to generate the importance proposal distribution is proposed. The proposal distribution integrates the latest measurements into...
Firstly this article presents a multi-level architecture permitting the localization of a mobile platform and secondly an incremental construction of the environment's map. The environment will be modeled by an occupancy grid built with information provided by the stereovision system situated on the platform. The reliability of these data is introduced to the grid by the propagation of uncertainties...
Two strategies for fusing information from multiple sources when generating predictive models in the domain of pesticide classification are investigated: i) fusing different sets of features (molecular descriptors) before building a model and ii) fusing the classifiers built from the individual descriptor sets. An empirical investigation demonstrates that the choice of strategy can have a significant...
This paper presents a novel sequential variational inference algorithm for distributed multi-sensor tracking and fusion. The algorithm is based on a multi-sensor target representation where a target is represented jointly by its states at different sensors and a global state fusing all sensor data. A tree-structured graphical model is adopted to model the dependencies between these states at a time...
This paper studies the feasibility of information analysis processing technology, which fuses speech and image together in the real-time monitoring system. It emphasizes particularly on speech analysis and fuses these two technologies in terms of scoring strategy. It also makes some improvement on MFCC feature extraction and proposes a quick MFCC algorithm. The proposed algorithm can reach the requirement...
A novel method involved the time-varying tracking model under the nonlinear state-space evolved system is presented, in which the expectation-maximization (EM) algorithm is used to identify the state transition matrix f and the process noise covariance Q online. The typical maneuvering models, as described, essentially, are prior models and use fixed and constant evolved matrix and designed noise...
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