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The gains in surveillance information that can be provided by fusion of multiple sensors have been demonstrated in theoretical and practical terms. However, the use of additional sensors quickly reaches a point where the marginal benefits outweigh the marginal costs. In part, this is due to an increasing probability of misassociation. Additionally, the probability of finding an available sensor with...
The reception state of a satellite is an unavailable information for Global Navigation Satellite System receivers. His knowledge or estimation can be used to evaluate the pseudorange error. This article deals with the problem using three reception states: direct reception, alternate reception and blocked situation. This parameter, estimated using a Dirichlet distribution, is included in a particle...
Active and passive sonar sensors provide complementary information about contacts. In addition to the physical characteristics of a passive array, the bearing resolution estimate can be limited by computational constraints given the necessity to survey the full azimuth for contacts. In a distributed field of sensors, however, it may be advantageous to divert the resources of a given sensor from a...
Dempster rule of combination is an effective method in evidence reasoning; however, the original combination rule may produce counterintuitive results when there are severe conflicts among evidences due to the discarding of contradictory mass assignments. In this paper a modified combination rule is proposed based on ambiguity measure (AM), which can describe the evidencepsilas degree of uncertainty...
Feature aided tracking can often yield improved tracking performance over the standard radar tracking with positional measurements alone. However, the complexity of the tracker may dramatically increase due to the inclusion of the target feature state. In this paper, we study the situation where the target feature is a constant or slowly varying parameter with respect to the target state and can be...
The basis for map assisted moving target tracking is a correct and up-to-date representation of the environment. In this contribution a method is proposed to model curved structures, e.g. roads or tracks, with cubic spline curves. The unknown model parameters are estimated based on corrupted measurements using a probabilistic approach. In particular, the method presented results in a linear formulation...
In this paper, we propose a Gaussian mixture (GM)-probability hypothesis density (PHD) filter based algorithm for multiple objects tracking. To reduce the number of used Gaussians, we introduced a clustering procedure and observation Gaussians estimation, to avoid the exponential growth of mixture components when the number of measurement highly increases. The new birth of Gaussian components is performed...
The identity management problem is the problem of probabilistically keeping track of the association between target tracks and target identities, based on observations made by sensors. Updates of the belief state can happen because of new sensor observations reflecting on target identity, or because targets come near each other so that their identities become confused or mixed. Since the space of...
The cardinalized probability hypothesis density (CPHD) filter is a recursive Bayesian algorithm for estimating multiple target states with varying target number in clutter. In the present work, it is shown that a missed detection in one part of the field of view has a significant effect on the probability hypothesis density (PHD) arbitrarily far apart from the missed detection. In the case of zero...
Often knowledge from human experts is expressed in the form of uncertain implication rules, such as ldquoif A then Brdquo with a certain degree of confidence. Therefore, it is important to include such a representation of knowledge into the process of reasoning under uncertainty. Incorporating inference rules based on the material implication of propositional logic into the evidence theory framework...
We propose an asymptotically optimum test for the problem of decentralized sequential hypothesis testing in continuous time, in the case where the sensors have full local memory and no feedback from the fusion center. According to our scheme, the sensors perform locally repeated SPRTs and communicate, asynchronously, their one-bit decisions to the fusion center. The fusion center in turn uses the...
In many tracking scenarios, the amplitude of target returns are stronger than those coming from false alarms. This information can be used to improve the multi-target state estimation by obtaining more accurate target and false alarm likelihoods. Target amplitude feature is well know to improve data association in conventional tracking filters (such as the PDA, MHT), and results in better tracking...
The paper presents two methods of updating the weights of a Gaussian mixture to account for the density propagation within a data assimilation setting. The evolution of the first two moments of the Gaussian components is given by the linearized model of the system. When observations are available, both the moments and the weights are updated to obtain a better approximation to the a posteriori probability...
State estimation and reconstruction quality of distributed phenomena that are monitored by a network of distributed sensors is strongly affected by communication failures, which is a problem in real-world sensor networks. In this paper, we propose a novel sensor scheduling approach named priority list sensor scheduling (PLSS). This approach facilitates efficient distributed estimation in sensor networks,...
Statistical mechanics has proven to be a useful model for drawing inferences about the collective behavior of individual objects that interact according to a known force law (which for a more general usage is referred to as interacting units.). Collective behavior is determined not by computing F = ma for each interacting unit because the problem is mathematically intractable. Instead, one computes...
This work considers the problem of quickest detection with N distributed sensors that receive continuous sequential observations from the environment. These sensors employ cumulative sum (CUSUM) strategies and communicate to a central fusion center by one shot schemes. One shot schemes are schemes in which the sensors communicate with the fusion center only once, after which they must signal a detection...
Although the theory of hypothesis testing is well developed and has a long history of application, practical application of hypothesis testing is plagued with fallacies, confusions, misconceptions, misuses, and abuses. This paper addresses four of the most widespread ones, particularly in statistical processing of signals, data, and information in uncertainty. They concern the decision on a single...
In this paper, we apply a Gaussian Mixture cardinalized PHD tracker to several real and simulated datasets from the MSTWG (Multistatic Tracking Working Group) library from NURC, TNO and ARL:UT. We also report our analysis on the SEABARpsila07 sea experiment.
Recent attention in quickest change detection in a multi-sensor scenario has been on the case where the densities of the observations at all the sensors change instantaneously at the time of disruption. In this work, we consider a scenario where change propagates across the sensors and its propagation can be modeled as a Markov process. A centralized, Bayesian version of this problem, with a common...
This article presents four different approaches for identifying persons during tracking. The ability to keep track of people is essential for mobile robots which provide services to humans. The tracking task is usually carried out using range measuring devices like laser range sensors, which provide spatial information only. They allow to estimate the trajectories of objects quite accurately, but...
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