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In the development phase of perception systems (e.g. for advanced driver assistance systems) general interest is pointing towards the performance of the respective detection and tracking algorithms. One common way to evaluate such systems relies on simulated data which is used as a reference. We present a semi-autonomous method, which allows the extraction of reference data from sensor recordings...
In this paper a method is introduced based on the concept of Bayesian networks (BNs), which is applied to model sensor fusion. Sensors can be characterised as real dynamical systems with specific physical functional principles, allowing to determine the value of a physical state of interest within certain ranges of tolerance. The measurements of the sensors are affected by external, e.g. environmental...
A technique is proposed to extract system requirements for a maritime area surveillance system, based on an activity recognition framework originally intended for the characterisation, prediction and recognition of intentional actions for threat recognition. To illustrate its utility, a single use case is used in conjunction with the framework to solicit surveillance system requirements.
The probability hypothesis density (PHD) filter, which was derived from finite set statistics is a promising approach to multi-target tracking. An analytical closed-form solution for the PHD, named Gaussian mixture PHD Filter, is given for linear Gaussian target dynamics with Gaussian births by B. Vo and W. Ma. Based on the Gaussian mixture PHD filter, in this paper, without consideration of data...
In the condition of sensor network (SN), to associate local tracks front multiple sensors is a complex task, due to the combination explosion caused by the increasing number of sensors and targets. A new graphical models-based technique for track association is proposed in this paper to deal with the problem. Firstly, by means of the sparse structure inherent in multisensor multitarget tracking scenario,...
Tracking maneuvering targets is a difficult problem due to unpredictable maneuvers which change the target's state and/or dynamics. To ensure track accuracy a filter needs to model the target correctly and quickly respond to maneuvers. A new sequential filter is proposed which attempts to improve upon existing algorithms in several areas. A more flexible internal model is used to describe effects...
Multiplicative noise makes the interpretation of image extremely difficult, and the fixed-size window filters cannot achieve good trade-off between noise suppression and edge keeping. Based on adaptive windowing and local structure detection, a new filtering algorithm of multiplicative noise is developed in this paper. The sliding window size is automatically adjusted by adaptive windowing, and the...
Data fusion in information retrieval has been investigated by many researchers and quite a few data fusion methods have been proposed, but why data fusion can bring improvement in effectiveness is still not very clear. In this paper, we use a geometric probabilistic framework to formally describe data fusion, in which each component result returned from an information retrieval system for a given...
The knowledge of the principles and goals under which an adversary organization operates is required to predict its future activities. To implement successful counter-actions, additional knowledge of the specifics of the organizational structures, such as command, communication, control, and information access networks, as well as responsibility distribution among members of the organization, is required...
Tracking maneuvering targets presents a great challenge to airborne surveillance radar signal processing and sensor systems management systems. Smears caused by an uncompensated maneuver (either translational or rotational) affect target identification (ID) with distorted target images. An unexpected maneuver introduces large position estimation errors to a tracker and in the worst case loss of track...
This paper is concerned with tracking of ground targets on roads and investigates possible ways to improve target state estimation via fusing a target's track with information about a road along which the target is believed to be traveling. A target track is estimated by a surveillance radar whereas a digital map provides the road network of a region under surveillance. When the information about...
Evidential-reasoning methods, such as the Dempster-Shafer calculus of evidence, are widely applied to information fusion problems. In this paper we examine methodological requirements as well as conceptual issues that are relevant to their understanding and applicability. These matters include interpretation of its basic constructs and that of the notion of evidential independence, the characterization...
Defence Research and Development Canada at Valcartier is pursuing the exploration of situation analysis concepts and the prototyping of computer-based decision support systems to maintain the state of situational awareness for the decision maker. The integration of the human element at the beginning of the analysis process is an important facet of our approach. The mathematical formalism and methodology...
When designing a higher-level fusion system the designer must choose between options, and in doing so confronts a number of tradeoffs. This paper outlines some of those options and the tradeoffs that those options involve.
Contemporary situational awareness problems such as automated normalcy learning for anomaly detection and motion behavior prediction are addressed with biologically-inspired processing, representation, and learning approaches. Issues and challenges are discussed and our responses to them described. Relatively simple neural principles provide considerable power in providing capabilities required to...
By observing various battlefield situations as they unfold and by interacting with peers and with battlefield artifacts, such as sensors and information processing systems, intelligence analysts form internal, mental models of things that they are observing and with which they are interacting. These models provide predictive and explanatory power for understanding a specific situation at hand, for...
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...
The improvement in sensor technologies over the recent years is providing the earth observation community with datacubes of several hundreds of spectral bands which are both an incredible opportunity for phenomenology understanding and material characterization but also pose a serious challenge for their exploitation. We propose in this paper to eliminate spectral redundancy and noise with the minimum...
In the area of process refinement under level 4 data fusion of the JDL model [1,2], high-level sensor management is often performed by human operators manning sensor systems who constantly have to monitor the situational and sensor picture for critical events and dynamically employ myriad sensors' functions to carry out mission-specific tasks. To assist the human operators in dealing better with the...
In this paper we analyze the sensor and fusion schedules of a time-triggered, Kalman filter based, multi-sensor fusion system. The fusion system is used as an environmental perception platform for advanced driver assistance systems and delivers its service to a safety related application. As the application demands cyclic updates with bounded accuracy, the influence of the sensor and fusion schedules...
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