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This paper is concerned with performance prediction of multiple target tracking system. Effects of misassociation are considered in a simple (linear) framework so as to provide closed-form expressions of the probability of correct association. In this paper, we focus on the development of explicit approximations of this probability for a unique false measurements. Rigorous calculations allow us to...
PMHT algorithm, as proposed, promises high performance multi target tracking in clutter with (relatively) modest computational resources. However, when applied to practical target tracking situations, a number of problems need to be overcome. PMHT assumes fixed number of tracks, and furthermore it assumes that all tracks are true tracks. No track quality measure is provided within PMHT to enable false...
Bayesian networks (BNs) represent joint space probabilities compactly and enable one to carry out efficient inferencing. Although the Dempster-Shafer (DS) belief theoretic framework captures a wider class of imperfections, its utility in such graphical models is limited. This is mainly due to the requirement of having to maintain a basic probability assignment (BPA) for the whole power set of propositions...
Modern passive sonar systems employ a high degree of automation to produce a track-level sonar picture. Further refinement of the track-level information is normally performed by a human operator. Providing automated assistance would reduce the operator's workload and is a key enabler for semi- and fully automated sonar systems. The nature of the signals emitted by targets and of the underwater environment...
This paper deals with the problem of objective evaluation of dynamic, multi-sensor image fusion. For this purpose an established static image fusion evaluation framework, based on gradient information preservation between the inputs and the fused image, is extended to deal with additional scene and object motion information present in multi-sensor sequences. In particular formulations for dynamic,...
Dynamic classifier selection has traditionally focused on selecting the most accurate classifier to predict the class of a particular test pattern. In this paper we propose a new dynamic selection method to select, from a population of ensembles, the most confident ensemble of classifiers to label the test sample. Such a level of confidence is measured by calculating the ambiguity of the ensemble...
Prior to committing personnel to investigate a building or suspicious site such as a cave, it is imperative to determine the importance and current danger of the site. To this end, sensors on a robotic platform can interrogate the site prior to sending in personnel. This paper investigates methods to exploit multiple sensor modalities in order to automatically 1) detect human presence, and 2) detect...
Multiple ground targets tracking with a GMTI (ground moving target indicator) sensor is considered a challenging problem in order to establish battlefield assessment. An IMM algorithm with a variable structure is adapted to the road network and used to track multiple manoeuvring ground targets. However, the case of undetected targets due to terrain elevation or Doppler obscuration was not taken into...
Feature ranking, due to its simplicity and computational efficiency, is a widely used dimensionality reduction technique, especially for large dataset where other methods are computationally too expensive. Conventionally feature ranking is done based on a single ranking criterion. One drawback associated with the conventional, single-criterion ranking is that the ranking order of the features is very...
In this paper we present an application that utilizes a novel two-level fusion architecture to detect and track disease outbreaks across public health system databases. In the first fusion level, collected data is used to detect and track indicative bio-events using latent semantic analysis and unsupervised clustering. In the second fusion level, clusters produced via the first are used to feed dynamic...
Decentralized multisensor-multitarget tracking has numerous advantages over single-sensor or single-platform tracking. In this paper, we present a solution to one of the main problems of decentralized tracking, namely, distributed information transfer and fusion among the participating platforms. This paper presents a hierarchial multi-level decision mechanism for collaborative distributed data fusion...
We consider the problem of state estimation for a dynamic system driven by unobserved, correlated inputs. We model these inputs via an uncertain set of temporally correlated dynamic models, where this uncertainty includes the number of modes, their associated statistics, and the rate of mode transitions. The dynamic system is formulated via two interacting graphs: a hidden Markov model (HMM) and a...
Geolocation with three or more unmanned aerial vehicles (UAVs) based on time-difference-of-arrivals (TDOA) is possible but has implementation problems including UAV trajectory optimization, measurement association, and communication bandwidth limitations. The complexity of each of these problems is manageable with a simpler system of two netted UAVs that processes multiple TDOA measurements collected...
Tracking objects using multiple sensors is more efficient than those using one sensor. In this paper, we proposed a method to fuse data from multiple sensors in Gaussian mixture probability hypothesis density filter. This method can avoid the data association problem in multi-sensor multi-object tracking. Moreover, it is more reliable and less computational than particle probability hypothesis density...
Shape-based image retrieval techniques are among the most successful content-based image retrieval (CBIR) approaches. In recent years, the number of shape-based image retrieval techniques has dramatically increased; however, each technique has both advantages and shortcomings. This paper proposes a consensus-based fusion algorithm to integrate several shape-based image retrieval techniques so as to...
We present a computational geometry method for the problem of triangulation in the plane using measurements of distance-differences. Compared to existing solutions to this well-studied problem, this method is: (a) computationally more efficient and adaptive in that its precision can be controlled as a function of the number of computational operations, making it suitable to low power devices, and...
The question tackled here is the time allocation of radars in a multitarget environment. At a given time radars can only observe a limited part of the space; it is therefore necessary to move their axis with respect to time, in order to be able to explore the overall space facing them. Such sensors are used to detect, to locate and to identify targets which are in their surrounding aerial space. In...
The primary goal of this effort is to establish an approach for determining the trustworthiness of a datum element produced from one or more sources. This discussion develops the notion of Trustworthiness as a measurement of corroboration derived by assessing the level of conformity to existing beliefs. A technique is proposed for combining trustworthiness of sources and specific datum elements.
A cooperative team's performance strongly depends on the view that the team has of the environment in which it operates. In a team with many autonomous vehicles and many sensors, there is a large volume of information available from which to create that view. However, typically communication bandwidth limitations prevent all sensor readings being shared with all other team members. This paper presents...
We present and discuss a mixed conjunctive and disjunctive rule, a generalization of conflict repartition rules, and a combination of these two rules. In the belief functions theory one of the major problem is the conflict repartition enlightened by the famous Zadeh's example. To date, many combination rules have been proposed in order to solve a solution to this problem. Moreover, it can be important...
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