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Multi-sensor Maritime Monitoring for the Canadian Arctic: Case Studies

Multi-Sensor Maritime Monitoring for the Canadian Arctic: Ca...

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International Conference on information fusion

作者： Giulia Battistello Javier Gonzalez Martin Ulmke Wolfgang Koch Camilla Mohrdieck Department Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany Data Fusion Concepts Integration and Test Airbus Defence and Space Ulm Germany

ISBN: (纸本)9781509020126

Maritime Domain Awareness (MDA) in the Canadian Arctic is limited by the scarceness or even absence of monitoring sensors. The backbone for vessel surveillance is represented by the satellite-based Automatic Identification System (S-AIS), which provides important though not comprehensive information about ships in the area. The objective of the Canadian-German research project PASSAGES is to specify the requirements and the modular architecture of a persistent maritime surveillance and risk management system adapted to arctic conditions and focused on the Northwest Passage (NWP). In order to provide a continuous vessel traffic picture in remote and local areas, real and simulated sensors from space borne and ground based platforms besides S-AIS are taken into account. The capabilities of such multi-sensor surveillance solutions in enhancing the MDA are demonstrated over two selected operationally relevant scenarios. A key element to achieve this, are robust multisource tracking and fusion algorithms able to cope with different heterogeneous and potentially delayed, imprecise or misaligned sensor data.

关键词： Maritime Domain Awareness Traffic Monitoring Multi-sensor fusion Passive Radar

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Scaling the World of Monocular SLAM with INS-Measurements for UAS Navigation

Scaling the World of Monocular SLAM with INS-Measurements fo...

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International Conference on information fusion

作者： Daniel Bender Fahmi Rouatbi Marek Schikora Daniel Cremers Wolfgang Koch Department Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany Computer Vision Group Technical University of Munich Garching Germany

ISBN: (纸本)9781509020126

The usage of a global positioning system (GPS) corrected inertial navigation system (INS) seems to be advantageous to camera-based pose estimation algorithms for outdoor navigation. The GPS signals lead to a geographical location with an accuracy of a few meters or even up to some centimeters in a setup utilizing correction data. Performing the pose estimation with a camera system has several disadvantages. The high amount of data has to be processed and the robustness may vary because of different environment and weather conditions. Nevertheless, cameras are the most used sensors for various tasks with unmanned aerial systems (UAS) because of their low cost and weight The research results for vision-based simultaneous localization and mapping (SLAM) algorithms show the great capabilities of vision-based navigation. Therefore, the possibilities of cameras should be investigated for outdoor navigation in conjunction with an INS or as standalone backup solution in the case of an INS failure. The vision-based pose estimation using a SLAM algorithm provides considerable additional value by providing a map of the observed area. In contrast to keypoint-based approaches, the usage of a semi-dense formulation leads to 3D information for all image regions with gradients and results in a detailed 3D reconstruction. However, the main problem of the monocular SLAM remains the same. The visual pose estimations, and consequently the generated world, suffer from the unknown scale and the corresponding scale drift. In this work we develop a large scale semi-dense SLAM algorithm for the outdoor navigation of UAS equipped with a camera and an INS. This sensor combination increases the robustness of the visual pose estimation process and enables the generation of a very detailed, metric scaled map.

关键词： Cameras Simultaneous localization and mapping Pose estimation Three-dimensional displays Global Positioning System Robustness Cameras pose estimation three-dimensional displays simultaneous localization and mapping Global Positioning Systems supersonic low altitude missile hybrid navigation systems Instruments Division INS gene navigation Robustness region of an image

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sensor deployment for motion trajectory tracking with a genetic algorithm

Sensor deployment for motion trajectory tracking with a gene...

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2015 IEEE International Conference on Industrial Technology, ICIT 2015

作者： Domingo-Perez, Francisco Lazaro-Galilea, Jose Luis Bravo, Ignacio Martin-Gorostiza, Ernesto Salido-Monzu, David Llana, Alvaro Govaers, Felix Department of Electronics University of Alcalá Alcalá de Henares Spain Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany

ISBN: (纸本)9781479978007

This paper focuses on determining the optimum placement of a given number of sensors for estimating the position of a moving target using range-difference measurements. We define a region of interest and generate several random trajectories with the dynamic white noise acceleration model. After obtaining those trajectories that populate the area we compute the posterior Cramér-Rao lower bound iteratively for each instant of each trajectory. Using that bound we can obtain a global measure of the mean squared error of the estimate of the position and use it as an objective function to be minimized to determine the optimum sensor placement. Finally, we determine that optimum deployment pattern using a genetic algorithm and we include an example of sensor placement using an infrared indoor positioning system. © 2015 IEEE.

关键词： Genetic algorithms

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Improvements in the implementation of log-homotopy based particle flow filters

Improvements in the implementation of log-homotopy based par...

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International Conference on information fusion

作者： Muhammad Altamash Khan Martin Ulmke Sensor Data and Information Fusion Department FKIE Fraunhofer Wachtberg Germany

State estimation of a non-linear system perturbed by non Gaussian noise is a challenging task. Typical solutions like EKF/UKF could fail while Monte Carlo methods, even though more accurate, are computationally expensive. Recently proposed log homotopy based particle flow filter, also known as Daum-Huang filter (DHF) provides an alternative way of non-linear state estimation. There have been a number of DHFs derived, based on solutions of the homotopy flow equation. The performance of these new filters depends a lot on the implementation methodology. In this paper, we highlight the key factors affecting the DHF performance and investigate them individually. We then make recommendations based on our results. It is shown that a properly designed DHF can outperform a basic particle filter, with less execution time.

关键词： Covariance matrices Mathematical model Estimation Atmospheric measurements Particle measurements Eigenvalues and eigenfunctions Approximation methods

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Quality of service resource management for a radar network

Quality of service resource management for a radar network

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IEEE Radar Conference

作者： Roaldje Nadjiasngar Alexander Charlish Sensor Data and Information Fusion Department Information Processing and Ergonomics FKIE Wachtberg Germany

ISBN: (纸本)9781467396561

The resource management problem for a network of radars is formulated in this paper as a quality of service constrained optimisation problem. Conditions for the optimal solution to the problem are derived from the Karush-Kuhn-Tucker (KKT) conditions. An algorithm is presented that extends the single radar Q-RAM algorithm by satisfying the KKT conditions for the radar network case. The algorithm is demonstrated on a target tracking control problem, where it is shown that the proposed multiple sensor Q-RAM (MSQRAM) method enables an increased number of targets to be tracked with a better estimation error in comparison to locally optimised radar nodes.

关键词： Resource management Radar tracking Quality of service Target tracking Optimization Redundancy

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Anticipation in cognitive radar using stochastic control

Anticipation in cognitive radar using stochastic control

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IEEE National Conference on Radar

作者： Alexander Charlish Folker Hoffmann Sensor Data and Information Fusion Department Information Processing and Ergonomics FKIE Wachtberg Germany

ISBN: (纸本)9781479982332

Previous works have identified key characteristics of a cognitive radar, such as knowledge exploitation, perception, action, memory, intelligence and attention. In this work, it is argued that the cognitive characteristic of anticipation can also enhance radar performance. In this paper it is shown that radar management using a partially observable Markov decision process (POMDP) enables the radar to act with anticipation. A method using policy rollout is applied to approximate a POMDP for a target tracking control problem. Through a simulated example it is demonstrated how the anticipative method departs from a purely adaptive approach, and the subsequent improvement in performance is quantified.

关键词： Loss measurement

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A performance model for target tracking with a radar network

A performance model for target tracking with a radar network

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IEEE Radar Conference

作者： Roaldje Nadjiasngar Alexander Charlish Sensor Data and Information Fusion Department Fraunhofer Institute for Communications Wachtberg Germany

ISBN: (纸本)9781467396561

This paper presents a performance model based on covariance analysis for target tracking with a radar network. The model enables the average expected estimation error and temporal resource loading to be calculated for varying operational parameters. This performance model can be used for radar network resource management and is especially suited to quality of service management methods. The performance model is used to demonstrate the benefit of additional nodes in a radar network as well as the influence of the radars to target geometry on the estimation error. The necessity of a resource management mechanism that effectively balances the allocation of the network resources is highlighted.

关键词： Radar tracking Target tracking Estimation error Resource management Radar measurements Signal to noise ratio

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Quality of service management for a multi-mission radar network

Quality of service management for a multi-mission radar netw...

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IEEE International Workshop on Computational Advances in Multi-sensor Adaptive Processing (CAMSAP)

作者： Alexander Charlish Roaldje Nadjiasngar Sensor Data and Information Fusion Department Fraunhofer Institute for Communications Wachtberg Germany

This paper formulates a constrained optimisation problem for quality of service based resource management of a electronically steered phased array radar network. An algorithm is described, which enables the constrained optimisation problem to be solved. It is demonstrated how differing quality of service requirements can be specified for different mission phases. A simulated target tracking control example is given, in which radar control parameters are adjusted with respect to the different mission phases.

关键词： Radar tracking Target tracking Resource management Quality of service Optimization Predictive models

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sensor deployment for motion trajectory tracking with a genetic algorithm

Sensor deployment for motion trajectory tracking with a gene...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Francisco Domingo-Perez Jose Luis Lazaro-Galilea Ignacio Bravo Ernesto Martin-Gorostiza David Salido-Monzu Alvaro Llana Felix Govaers Department of Electronics University of Alcalá Henares Spain Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany

ISBN: (纸本)9781479978014

关键词： Trajectory Receivers Sociology Statistics Genetic algorithms Position measurement Optimization

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Dynamic-occlusion likelihood incorporation in a PHD filter based range-only tracking system

Dynamic-occlusion likelihood incorporation in a PHD filter b...

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International Conference on information fusion

作者： Snezhana Jovanoska Felix Govaers Reiner Thomä Wolfgang Koch Electronic Measurements Research Lab Ilmenau university of Technology Ilmenau Germany Department of Sensor Data and Information Fusion (SDF) Fraunhofer FKIE Wachtberg Germany

ISBN: (纸本)9781479974047

In multiple target tracking target occlusion or shadowing is a common occurrence. A target may be occluded by an existing structure, or in many cases, by another moving target in the environment. In this paper we consider a UWB-based range-only person tracking system. Occlusion regions induced by moving targets in the scenario are defined followed by a derivation of an occlusion likelihood function. The occlusion likelihood is then incorporated within a person localization and tracking framework based on the PHD filter by influencing the probability of target detection. Numerical and experimental results demonstrate that the incorporation of `negative information' leads to a more complete belief of the scenario and can result in use of fewer sensors for covering the area of interest.

关键词： Target tracking Receivers Robot sensing systems Transmitters Time measurement Mathematical model Clutter

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