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Distributed image steganography (DIS) (Y.S. Wu et al., 2004) is a new method of concealing secret information in several host images, leaving smaller traces than conventional steganographic techniques, and requiring a collection of affected images for secret information retrieval. Fusion system designs of the future will require enhanced security measures for distributed data communication. DIS, compared...
The exploitation of bistatic Doppler measurements for multistatic tracking is considered. It is found through simulation, that, while the velocity estimation of the standard extended Kalman filter is improved in monostotic situations and multistatic situations where measurement errors are small, a degradation in performance is observed in multistatic situations where the measurement errors are realistically...
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...
This paper considers the recursive estimation of emitter location using time difference of arrival measurements formed by the correlation of signals received by two unmanned aerial vehicles. The time difference of arrival measurement defines an hyperbola of possible emitter locations. This hyperbola is used as a measurement in a nonlinear Alter. The performance of two such filters, an extended Kalman...
The interacting multiple model filter has long been the preferred method to handle multiple models in target tracking. The filter finds a suboptimal solution to a problem, which implicitly assumes that immediate model shifts have the highest probability. We argue that this model-shift property does not capture the typical nature of maneuvering targets, namely that changes in target dynamics persist...
Underwater passive acoustic target tracking is challenging in littoral environments. One way to mitigate the difficulties is to add non-acoustic sensors and use data fusion. The topic of this paper is how to evaluate, in an objective way, the performance of data fusion in this application. Different performance measures are discussed. The performance measures are applied on data from a trial where...
A physical activity monitoring system by data fusion in body sensor networks is presented in this paper, which targets at providing body status information in real time and identifying body activities. By fusion of data collected from several accelerometer sensors placed on different parts of the body, the activities can be identified and tracked Mathematical approaches employed in the system include...
This paper describes a novel technique to obtain radar biases estimates that can effectively reduce mismatches in track association algorithms. This is accomplished by matching ship-borne radar images to geo-referenced satellite images. The matching is performed through the minimization of the averaged partial Hausdorff distance between data points in each image. The minimization rapidly yields robust...
This paper describes two tracking filters based on the use of kinematic information (velocity, acceleration), in addition to usual position measurements. This kinematic information allows for more advanced filtering methods, reducing error especially on maneuvers. In the paper we will show two different Kalman filter exploiting this information, and compare them with regards to accuracy, computational...
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 contribution presents a unified framework for localization and tracking in sensor networks based on fusing a variety of signal energy measurements as provided by for instance acoustic, seismic, magnetic, radio, microwave and infrared sensors. The received energy from such sensors generally decays exponentially, and a log range model is introduced for the sensor observations in logarithmic scale,...
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