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This paper presents a novel and an improved approach for estimating the position of a vehicle using vehicle-infrastructure cooperative localization. In our previous work we presented a Factor Graph based solution which added the topology (inter-vehicle distance) as a constraint while localizing the vehicle using data from sensors from both inside and outside the vehicle. This paper extends the work...
Single-image blind deblurring could be considered as an important preprocessing step in imaging information fusion. Its purpose is to simultaneously estimate blur kernel and latent sharp image from only one observed blurred image. Blind deblurring has been attracting increasing attention in the fields of image processing, computer vision, computational photography, etc. However, it is a typically...
This paper considers the state estimation of Markovian jump linear systems with random parameters and estimate feedback. The state estimate at the previous epoch is introduced into the dynamical model to depict some phenomena that the system evolvement may depend on the most recent estimate. Then, the linear minimum mean square error estimator is derived for the considered system. A filtering framework...
Hough voting based methods for object detection work by means of allowing local image patches to vote for the center of the object according to the trained visual words. They are effective for object with small local varieties, but incapable of solving multi-view detection problem. The traditional way is training visual words for each subcategory that has similar view. However, limited training data...
Predictive analytics and data fusion techniques are being regularly used for analysis in Quantitative Risk Management (QRM). The primary risk metric of interest, Value-at-Risk (VaR), has always been difficult to robustly estimate for different data types. The classical Monte Carlo simulation (MCS) approach (denoted henceforth as classical approach) assumes the independence of loss severity and loss...
Acoustic propagation delay has not been investigated for a continuous wave multistatic sonar tracking system except for the recent study conducted by Jauffret et al. [4], which estimates the trajectory of a constant velocity target. The results showed that the estimate bias caused by the propagation delay is not negligible, especially for a bistatic system. This paper develops an interacting multiple...
Situation information and sensor information are differentiated and a method for computing the situation information expected value (SIEV) is presented for use in Information Based Sensor Management (IBSM). Nine case pairs are evaluated in which the sensor capabilities vary among poor, average, and good sensors, and the goal lattice values vary among attack, defend, and stealth modes showing that...
Considering the convergence rate is a very important issue as distributed sensors networks usually consist of low-powered wireless devices and speeding up the consensus convergence rate is also important to reduce the number of messages exchanged among neighbors, a new adaptive method for weight assignment of communication links between sensor nodes is proposed based on the dynamic network topology...
A problem of state estimation with destination constraint is considered in this paper. An anti-radiation missile (ARM) often moves towards the target along a trajectory which is almost linear in the X-Y plane. The linear constraint for trajectory and target position are known as priori and can be used to enhance the performance of a tracking filter. In this paper, a destination constrained Kalman...
This paper establishes a risk assessment index system for oil and gas resource countries, with 46 screened indicators across 5 dimensions, namely political risk, economic risk, investment risk, oil and gas resources risk, and the Chinese factor. Furthermore, by using the principal component analysis method, the 46 risk indicators were narrowed down to 16 principal components. Subsequently, a support...
Probabilistic reasoning applied to dynamic spectrum sharing systems enables them to characterize situational uncertainties and determine acceptable spectrum access behaviors. Spectrum sharing systems may use sensing data to reduce situational uncertainty and improve spectrum sharing potential. Probabilistic reasoning approaches enable risk-constrained spectrum access, a concept in which spectrum sharing...
The Sequential Probability Ratio Test (SPRT) is a classical detector for problems with an unfixed sample size. Though it is optimal under some conditions, SPRT can be directly used only for a binary hypothesis with exactly known distributions. In this paper, sequential detection problem with an uncertain hypothesis distribution is considered, in which the uncertain distribution is formulated in a...
Acoustic frequency tracking of a harmonic signal with continuously varying frequency is considered. The Rao-Blackwellized point mass filter (RBPMF), previously proposed by the authors for mechanical vibration tracking, is applied to the problem. The RBPMF is compared with two periodogram-based methods, and the similarities and differences between them are explained. Both experimental and simulation...
In this paper, we consider a scenario where sensors are deployed over a large geographical area for tracking a target with circular nonlinear constraints on its motion dynamics. The sensor state estimates are sent over long-haul networks to a remote fusion center for fusion. We are interested in different ways to incorporate the constraints into the estimation and fusion process in the presence of...
We consider the problem of choosing the best subset of sensors that results in a prescribed error probability Pe in Bayesian setting. Since minimizing the error probability is often difficult to evaluate and manipulate, conventional methods adopt Bhattacharyya distance instead of it. In fact, Chernoff distance is the best achievable exponent in the Bayesian error probability and it is more accurate...
Detection with multiple distributions is considered. Rather than formulating the problem with multiple hypotheses, we formulate the problem in a binary hypothesis testing framework by a multiple model approach. Three classes of the Multi-Model Detection (MMD) problems are considered: simplex, compound, and mixture. Three concepts of optimality are given for these three problems, including Uniformly...
The question addressed in this paper is “what” is to be evaluated by the Uncertainty Representation and Reasoning Evaluation Framework (URREF) ontology. We thus identify the elements composing uncertainty representation and reasoning approaches, which constitute various subjects being assessed. We distinguish between primary evaluation subjects (Uncertainty Representation and Reasoning components...
This paper is the companion-paper of another paper presented in FUSION'17 concerning bearings-only target motion analysis (BOTMA). In this one, bearing data are replaced by range data: we study observability in range-only target motion analysis (ROTMA). When the observer is in constant turn motion, the target's trajectory is observable, as in BOTMA. If the observer is in constant acceleration motion,...
In this paper, under the situation of multiple interference regions, an optimal antenna placement problem for a distributed Multi-Input Multi-Output (MIMO) radar is studied. Considering multiple interference regions, we solve the antenna placement problem by utilizing antenna placement method based on Multi-Objective Particle Swarm Optimization (MOPSO). However, it is not clear when to stop the iteration...
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