Situation Awareness Problems Research Articles

Spectrum Situation Awareness for Space-Air-Ground Integrated Networks Based on Tensor Computing.

The spectrum situation awareness problem in space-air-ground integrated networks (SAGINs) is studied from a tensor-computing perspective. Tensor and tensor computing, including tensor decomposition, tensor completion and tensor eigenvalues, can satisfy the application requirements of SAGINs. Tensors can effectively handle multidimensional heterogeneous big data generated by SAGINs. Tensor computing is used to process the big data, with tensor decomposition being used for dimensionality reduction to reduce storage space, and tensor completion utilized for numeric supplementation to overcome the missing data problem. Notably, tensor eigenvalues are used to indicate the intrinsic correlations within the big data. A tensor data model is designed for space-air-ground integrated networks from multiple dimensions. Based on the multidimensional tensor data model, a novel tensor-computing-based spectrum situation awareness scheme is proposed. Two tensor eigenvalue calculation algorithms are studied to generate tensor eigenvalues. The distribution characteristics of tensor eigenvalues are used to design spectrum sensing schemes with hypothesis tests. The main advantage of this algorithm based on tensor eigenvalue distributions is that the statistics of spectrum situation awareness can be completely characterized by tensor eigenvalues. The feasibility of spectrum situation awareness based on tensor eigenvalues is evaluated by simulation results. The new application paradigm of tensor eigenvalue provides a novel direction for practical applications of tensor theory.

Cooperative situational awareness of multi-UAV system based on improved D-S evidence theory

Situational awareness (SA) of unmanned aerial vehicles (UAVs) has been a research hotspot over the decades. Existing research mainly focuses on the SA of a single UAV in two-dimensional planes, whereas obstacles are assumed a priori. To eliminate these constraints, this study considers the cooperative situational awareness (CSA) problem of multi-UAV systems in the scenario of crossing a three-dimensional (3D) obstacle belt while no prior information of obstacles is required. First, the distribution models of the multi-UAV system and the obstacles are built based on two reference frames. Second, various types of uncertainties are characterized, which reflect an urgent need for CSA. Thus, a centralized CSA scheme is proposed and conducted on multiple UAVs and at different times, and the Dempster-Shafer (D-S) evidence theory is introduced to address information uncertainties and achieve high-accuracy information fusion. Next, to deal with the high-conflict evidence situations that are common in practice, a modified D-S fusion method is further developed. A modified Pearson coefficient is utilized to measure the correlation between different pieces of evidence. Both information credibility and uncertainty are taken into account to evaluate the evidence from different perspectives, and a novel evidence weight assignment method is presented to treat high-conflict situations. Numerical simulations validate the effectiveness of the proposed CSA method. Compared to existing studies, the proposed method is applicable to different trust paradoxes and achieves the best performance among various fusion methods.

Network Security Situational Awareness Based on Genetic Algorithm in Wireless Sensor Networks

How to design an effective and secure user authentication scheme suitable for complex wireless sensor network (WSN) environments has very important research significance. Based on the genetic algorithm theory, the paper constructs the security situational awareness model of wireless sensor network, and studies the WSN user security authentication scheme. The model uses the genetic algorithm extraction technology combined with the hash function to generate the biometric key, which solves the data accuracy problem of network security situational awareness: the user’s biometric key is obtained through the fuzzy extraction technology; the resistance of the node is to be attacked, but it is powerless when most of the nodes are broken, and it limits the scalability of the network. During the simulation process, the authentication of the identity of the cluster head by the base station is added in the topology establishment stage, and a one-way hash function and a shared key are added to the key management, so that the encryption key and the authentication key change periodically and dynamically, so that enhanced network communication security. The analysis results show that the protocol is feasible. The algorithm proposed in this paper reduces about 70% of the features in the original feature set, the classification detection rate is increased from 95.7212% to 97.7379%, and the false alarm rate is reduced from 7.9427% to 3.1072%, effectively improving the balance between safety and design cost.

A Theoretical Foundation for Context-Aware Cyber-Physical Production Systems

The complex workflows and interactions between heterogeneous entities in Cyber-Physical Production Systems (CPPS) call for the use of context-aware computing technology to operate effectively and meet the order requirements in a timely manner. In addition to the objective to meet the order due date, due to resource contention between production processes, CPPS may enter undesirable states. In undesirable states, all or part of the production activities are in waiting states or blocked situation due to improper allocation of resources. The capability to meet the order due date and prevent the system from entering an undesirable state poses challenges in the development of context-aware computing applications for CPPS. In this study, we formulate two situation awareness problems, including a Deadline Awareness Problem and a Future States Awareness Problem to address the above issues. In our previous study, we found that Discrete Timed Petri Nets provide an effective tool to model and analyze CPPS. In this paper, we present a relevant theory to support the operation of CPPS by extending the Discrete Timed Petri Nets to lay a foundation for developing context-aware applications of CPPS with deadline awareness and future states awareness capabilities. We illustrate the theory developed in this study by an example and conduct experiments to verify the computational feasibility of the proposed method.

Data Work and Decision Making in Emergency Medical Services: A Distributed Cognition Perspective

Emergency medical services (EMS) teams are first responders providing urgent medical care to severely ill or injured patients in the field. Despite their criticality, EMS work is one of the very few medical domains with limited technical support. This paper describes a study conducted to examine technology opportunities for supporting EMS data work and decision-making. We transcribed and analyzed 25 simulation videos. Using the distributed cognition framework, we examined EMS teams' work practices that support information acquisition and sharing. Our results showed that EMS teams leveraged various mechanisms (e.g., verbal communication and external cognitive aids) to distribute cognitive labor in managing, collecting, and using patient data. However, we observed a set of prominent challenges in EMS data work, including lack of detailed documentation in real time, situation recall issues, situation awareness problems, and challenges in decision making and communication. Based on the results, we discuss implications for technology opportunities to support rapid information acquisition, integration, and sharing in time-critical, high-risk medical settings.

HIGH ACCURACY SPACECRAFT ORBIT PROPAGATOR VALIDATION

ABSTRACTThe Space Situational Awareness (SSA) problem is becoming an exponentiallysignificant concern for satellite operators. The threat of on-orbit collisions endangerssatellites, spacecrafts and astronauts themselves especially in low-earth orbits(LEO). Many collisions occurred between satellites and debris that include natural,operational and non-operational objects in space. The collision between Russiancosmos 2251 and American iridium 33, for instance, imposed the need for anaccurate orbital propagation module. In order to perform successful collisionavoidance maneuvers, the mission operators need the orbit prediction to be highlyaccurate. Simple impractical number of collision avoidance maneuvers representsdreadful solution to escape of collision. Fake warning means waste of fuel andresources of satellite. This paper introduces an enhanced model to increase theaccuracy of propagation estimation based on a precise perturbation model.

Information Space Receding Horizon Control for Multisensor Tasking Problems.

In this paper, we present a receding horizon solution to the problem of optimal scheduling for multiple sensors monitoring a group of dynamical targets. The term target is used here in the classic sense of being the object that is being sensed or observed by the sensors. This problem is motivated by the space situational awareness (SSA) problem. The multisensor optimal scheduling problem can be posed as a multiagent Markov decision process on the information space which has a dynamic programming (DP) solution. We present a simulation-based stochastic optimization technique that exploits the structure inherent in the problem to obtain variance reduction along with a distributed solution. This stochastic optimization technique is combined with a receding horizon approach which uses online solution of the control problems to obviate the need to solve the computationally intractable multiagent information space DP problem and hence, makes the technique computationally tractable. The technique is tested on a moderate scale SSA example which is nonetheless computationally intractable for existing solution techniques.

About situation recognition on basis of artificial intelligence technology

This paper considers the situation awareness technique based on artificial intelligence technology. Certain meta–class of situation awareness problems comprising three major classes like environment and two moving objects. In the presented study the situation awareness (SA) is considered as some vector whose parameters contain information about the interrelationship and state of at least three separate classes at a given time instant. Over the SA set the function is being formed that allows to identify SA based on measurements of three classes’ parameters (properties) taken in the space and time. Mechanism of defining the inherence function and SA repository (set) forming is realized through the inference algorithm Rete and immunocomputing method.

Situation awareness in critical infrastructures

Critical infrastructure(CI) protectionand situationawarenessarerelevanttopicsin critical system domain. These issuesgofarbeyond the academicworldinvolvingvery often the national security framework. In this contribution, a review of the most attractive approaches proposed for addressing the situation awareness problems is presented. Most of the proposed approaches are based on multi-sensor data fusion, since the awareness is achieved by building a scenario using data providedby sensors spread into the systems. Humans are supposed to interact with the system, but only a few models are able to include their intervention. The review analysis is performed by considering models, architectures, and techniques adopted in each system and by highlighting their effectiveness and drawbacks. Finally an example in the field of air traffic management is presented.

Design and implementation of a new teleoperation control mode for differential drive UGVs

In this paper, we propose and implement a new control mode for teleoperated unmanned ground vehicles (UGVs), that exploits the similarities between computer games and teleoperation robotics. Today, all teleoperated differential drive UGVs use a control mode called Tank Control, in which the UGV chassis and the pan tilt camera are controlled separately. This control mode was also the dominating choice when the computer game genre First Person Shooter (FPS) first appeared. However, the hugely successful FPS genre, including titles such as Doom, Half Life and Call of Duty, now uses a much more intuitive control mode, Free Look Control (FLC), in which rotation and translation of the character are decoupled, and controlled separately. The main contribution of this paper is that we replace Tank Control with FLC in a real UGV. Using feedback linearization, the orientation of the UGV chassis is abstracted away, and the orientation and translation of the camera are decoupled, enabling the operator to use FLC when controlling the UGV. This decoupling is then experimentally verified. The developments in the gaming community indicates that FLC is more intuitive than Tank Control and reduces the well known situational awareness problem. It furthermore reduces the need for operator training, since literary millions of future operators have already spent hundreds of hours using the interface.

Concern level assessment: Building domain knowledge into a visual system to support network-security situation awareness

Information officers and network administrators require tools to help them achieve situation awareness about potential network threats. We describe a response to mini-challenge 1 of the 2012 IEEE Visual Analytics Science and Technology challenge in which we developed a visual analytic solution to a network-security situation awareness problem. To support conceptual design, we conducted a series of knowledge elicitation sessions with domain experts. These provided an understanding of the information they needed to make situation awareness judgements as well as a characterisation of those judgements in the form of production rules, which define a parameter we called the ‘concern level assessment’. The concern level assessment was used to provide heuristic guidance within a visual analytic system called Middlesex Spatial Interactive Visualisation Environment. An analysis of Visual Analytics Science and Technology challenge assessment sessions using Middlesex Spatial Interactive Visualisation Environment provides some evidence that intelligent heuristics like these can provide useful guidance without unduly dominating interaction and understanding.

Clouds in Space: Scientific Computing using Windows Azure

In this paper we report upon the cloud-based solution that we designed and implemented for space situational awareness. We begin by introducing the background to the work and to the area of space situational awareness. This concerns tracking the hundreds of thousands of known objects in near-Earth orbits, and determining where it is necessary for satellite operators to conduct collision-avoidance manoeuvres to protect their satellites. We also discuss active debris removal, which would be necessary to stabilise the debris population at current levels. We examine the strengths that cloud-based solutions offer in general and how these specifically fit to the challenges of space situational awareness, before describing the architecture we designed for this problem. We demonstrate the feasibility of solving the space situational awareness problem with a cloud-based architecture and note that as time goes on and debris levels rise due to future collisions, the inherent scalability offered by a cloud-based solution will be invaluable.

Pilot Procedure-Following Behavior During Closely Spaced Parallel Approaches

A flight simulator experiment was run to examine pilot procedure-following behavior during closely spaced parallel approaches. Such approaches are being considered under the Next Generation Air Transportation System (NextGen) to increase the capacity of runway systems, possibly without the need to increase the footprint of airports. Pilots flying these approaches utilized a simple heuristic to fly the procedure consistently, despite the heuristic being suboptimal for any of the three conditions. Moreover, procedure compliance was relatively low, but noncompliance itself was not unsafe unless accompanied by situation awareness problems. In some cases, noncompliance could be shown to be a better choice than compliance. These results have implications for assumptions regarding procedure-following by pilots utilizing novel procedures in NextGen.

Improved Situational Awareness in Emergency Management through Automated Data Analysis and Modeling

In this paper, we address the problem of situational awareness in the context of emergency management. Due to the widespread application of information technology, emergency managers face a new challenge in information overload, rather than the lack of information as in the past. These new tools deliver large volumes of data to the decision makers, often in real time. However, during the crisis, the task of identifying the key relevant information poses a real challenge and failure to do so can have disastrous consequences. To address this problem, we propose a model for the fusion of data from diverse sources, both real-time and static, to derive numerical measures that represent the status of a jurisdiction. In our approach, we combine the data available from various sources with human expertise to build customized models based on threats characteristic for particular jurisdictions. We developed a prototype based on data collected for several municipalities and implemented it as a computer model.

Situation Awareness Catches On: What? So What? Now What?

Human factors/ergonomics professionals regularly study the situation awareness (SA) problems of pilots, air traffic controllers, automobile drivers, power plant workers, ambulance dispatchers, urban search and rescue professionals, and unmanned vehicle operators, to mention a few. The challenge has been to define SA operationally and devise measurement strategies that focus on attention and recall on the one hand and relevant actions on the other. Although there have been many successes, challenges remain. This review is organized in three parts. Under “What?” we discuss definitions of SA, their interpretations in terms of human information processing and ecological psychological theories, as well as techniques for measuring SA. Under “So what?” we introduce SA applications'information requirements, technological tools, and training systems'that support the way people work and live. Finally, under “Now what?” we discuss future directions for SA research.

Situation Awareness Problems in General Aviation

Situation awareness (SA) is widely recognized as critical to success in the aviation environment. Most research to date has focused on SA in highly experienced military or commercial airline pilots. Yet, general aviation (GA) pilots, usually far less experienced and trained, fall prey to the vast majority of aviation accidents. Fifty-eight experienced flight instructors completed a survey on SA problems in GA operations. It found a wide range of SA problems across GA pilots at various levels of experience and in all phases of flight, although some factors appear to become less problematic with experience. Areas where problems are the most acute are identified and recommendations are made for improving SA in GA pilots.