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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 probabilistic multi-hypothesis tracking (PMHT) algorithm has been successfully applied to a simulated multi-static active sonar data set that contains a single constant velocity target in varying amounts of clutter [1]. The simulated data set in that study contained negligible registration error was therefore easily registered to a common frame of reference for use in a centralized tracking architecture...
Numerous national and multinational initiatives in maritime surveillance have been initiated, with the goal of having knowledge of all coastal and open-seas activities relevant to national security. As part of this effort, NATO is pursuing research activities to exploit existing multi-sensor systems in support of maritime surveillance. Multi-sensor fusion of data from maritime surveillance assets...
Networked systems that gather sensor data in order to react to phenomena in their surroundings are faced with a growing need for adaptive behavior to operate in dynamically changing environments. In designing a networked system the data processing chain can be decomposed into functional components. These functional components interact by requesting information they need and fulfilling requests received...
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...
A promising method of non-cooperative identification is the classification of a target by high-resolution radar signatures. By simultaneous tracking and classification one obtains a set of successive radar range profiles which contain information on the target from different aspect angles. At this point data fusion of the declaration series can help to stabilize the identification against misclassifications...
The challenge of modern sensor systems is besides the tracking of targets more and more their classification. The knowledge of the target class has significant influence on the identification, threat evaluation and weapon assignment process of large systems. Especially, considering new types of threats in anti asymmetric warfare the knowledge of a target class has an important drawback. Also the target...
Vector roadmaps are invaluable for various applications such as navigation and tracking. A new algorithm is presented aimed at incrementally producing exact, up-to-date vector roadmaps using GMTI tracks. In most existing work the track points are processed independently. Track points are individually associated with segments of existing roads and the road segment locations are corrected accordingly...
The aim of this paper is to present a multiple object tracking data fusion technique, which fuses radar, image, and ego vehicle odometry. The data are fused at a high level, which leads to reliable and stable tracking results providing also additional features as width estimation and the detection of stationary objects. A ldquorealrdquo application of these algorithms is illustrated on a specific...
In recent years the discrepancy between the required knowledge and the available knowledge for obtaining the situation awareness aboard Royal Netherlands Navy ships has increased. This paper presents a methodology to automatically classify objects in the mission environment based on user defined mission information in order to close this gap. The cornerstone of this methodology is the Confidence Interval...
It has been shown that sensor networks and data fusion are effective in providing an accurate operational picture, even in jammed environments. However, a weakness with methods based on data from several sensors is that there is not always data available from all the sensors all the time. In such cases fusion can not be performed with good results, leading to difficulties in detecting true objects...
The multistatic tracking working group (MSTWG) was formed in 2005 by an international group of researchers interested in developing and improving tracking capabilities when applied to multistatic sonar and radar problems. The MSTWG developed several simulated multistatic sonar scenario data sets for use in tracker evaluation by the grouppsilas participants. A common set of performance metrics was...
In this contribution the problem of tracking convoys moving on the ground by means of airborne radar is discussed. A coherent radar with multi-channel array antenna is considered which makes clutter suppression by space-time adaptive processing (STAP) techniques possible. In addition, a technique to estimate the lateral length component of a convoy is used in addition to the conventional range measurement...
For the detection of targets moving on ground, airborne ground moving target indicator (GMTI) radar is well-suited. In the tracking process, complex target dynamics, particularly stop and go maneuvers, and target masking due to Doppler blindness, often lead to track losses. By means of a refined sensor model it is possible to detect and handle such diverse target states. In addition, the generation...
Maritime surveillance of coastal regions requires the processing of data from a large number of heterogeneous surveillance sources. The generation of effective maritime domain awareness requires that the tracks from these sources must be fused. An automated fusion process that supports maritime domain awareness requires that the tracks from heterogeneous sources be modeled in such a way as to support...
Identification of tracked objects is a key capability of automated surveillance and information systems for air, surface and subsurface (maritime), and ground environments, improving situational awareness and offering decision support to operational users. The Bayesian-based identification data combining process (IDCP) provides an effective instrument for fusion of uncertain identity indications from...
This paper presents a high level fusion approach suitable for automotive sensor networks with redundant field of views. The advantage of this method is that it ensures system modularity and allows benchmarking, as it does not permit feedbacks and loops inside the processing. The proposed algorithm deals with the issue of multidimensional assignment as the test vehicle comprises four forward looking...
Several nonlinear filtering techniques are investigated for nonlinear tracking problems. Experimental results show that for a weakly nonlinear tracking problem, the extended Kalman filter and the unscented Kalman filter are good choices, while a particle filter should be used for problems with strong nonlinearity. To quantitatively determine the nonlinearity of a nonlinear tracking problem, we propose...
This paper presents a game theoretic approach for the management of multiple mobile sensors. Our approach can maintain tracks of smart targets under possibly adversarial environments. To ensure computational tractability, sensor management is divided into sensor assignment and sensor scheduling. In sensor assignment, covariance control and information theoretic sensor assignment are combined logically...
Advancements in sensor technology provide new multi-sensor systems with increasing flexibility. The sensor management process aims to perform sensor actions that support the overall goal of the user of a multi-sensor system. Some sensors can support multiple functions. When the different sensor functions utilise shared resources then the sensor actions must be chosen as a compromise between competing...
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