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Multi-sensor Extension of Radar Resource Management Approach Q-RAM

Multi-Sensor Extension of Radar Resource Management Approach...

引用

2024 sensor data fusion: Trends, Solutions, Applications, SDF 2024

作者： Vollweiter, Christoph Hoffmann, Folker Fraunhofer Fkie Sensor Data and Information Fusion Department Wachtberg Germany

ISBN: (纸本)9798331527440

This paper extends the single radar resource management approach Q-RAM for multiple radar sensors. It optimizes sensor task assignments as well as their radar control parameters jointly based on quality of service. Our method uses single sensor performance models and hence avoids the large parameter space of multi-sensor performance models, which increases exponentially with the number of sensors. This reduces the computational requirements significantly as well as the possible reaction time. The trade-off to this reduction is that our algorithm does not support the execution of the same task on multiple sensors during the same planning period. Though, over multiple planning periods, the tracker can still receive measurements originating from different sensors which allows to exploit the spatial geometry of widely separated sensors. Hence, our method is especially well suited for applications with restricted processing power that need fast reaction times. A simulated tracking scenario shows that the proposed method achieves significantly superior performance to a locally optimized resource management approach as well as to a distance-based assignment. It further accomplished almost identical performance to an approach that employs an exhaustive search to find the best sensor task assignment. © 2024 IEEE.

关键词： Quality of service

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Efficiently Evaluating Radar Performance Models Using Upper Bounds 26

Efficiently Evaluating Radar Performance Models Using Upper ...

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26th International Conference on information fusion, fusion 2023

作者： Vollweiter, Christoph Fraunhofer Fkie Sensor Data and Information Fusion Department Wachtberg53343 Germany

ISBN: (纸本)9798890344854

This paper presents an exact method of efficiently evaluating radar task performance models required by quality of service radar resource management. The method assumes that the utility for each task is monotonic in every radar control parameter dimension compared by the performance model. In comparison to the evaluation of all possible radar control parameter combinations, simulations show that the proposed method significantly decreases the required number of evaluations and runtime while still providing exact results. Although the proposed method is slower than some other approximate methods that were evaluated, it does have the advantage of guaranteeing exact results. Hence, the method is especially well suited for applications that require exact results with fast runtime. The method is evaluated using a single platform tracking performance model, but can easily be applied to other single platform or multi platform performance models. © 2023 International Society of information fusion.

关键词： Target tracking

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Multi-sensor Extension of Radar Resource Management Approach Q-RAM

Multi-Sensor Extension of Radar Resource Management Approach...

引用

Workshop on sensor data fusion: Trends, Solutions, Applications (SDF)

作者： Christoph Vollweiter Folker Hoffmann Sensor Data and Information Fusion Department Fraunhofer FKIE Wachtberg Germany

ISBN: (数字)9798331527440

ISBN: (纸本)9798331527457

关键词： Geometry Target tracking Computational modeling Radar Quality of service Benchmark testing Radar tracking sensors Planning Resource management

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Efficiently Evaluating Radar Performance Models Using Upper Bounds

Efficiently Evaluating Radar Performance Models Using Upper ...

引用

International Conference on information fusion

作者： Christoph Vollweiter Sensor Data and Information Fusion Department Fraunhofer FKIE Wachtberg Germany

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Non-myopic sensor Path Planning for Emitter Localization with a UAV 26

Non-myopic Sensor Path Planning for Emitter Localization wit...

引用

26th International Conference on information fusion, fusion 2023

作者： Hoffmann, Folker Schily, Hans Krestel, Markus Charlish, Alexander Ritchie, Matthew Griffiths, Hugh Fraunhofer Institute for Communication Information Processing and Ergonomics Fkie The Sensor Data & Information Fusion Department Wachtberg Germany Schönhofer Sales and Engineering GmbH Siegburg Germany University College London Department of Electrical Engineering London United Kingdom

ISBN: (纸本)9798890344854

This paper addresses the problem of localizing a stationary RF emitter with a mobile UAV, equipped with a single directional antenna. By rotating around its vertical axis, it determines a bearing towards the emitter. Our interest is in optimally selecting the measurement positions to achieve a fast localization. The majority of such systems described in the literature use greedy planning to select the next measurement position. This work experimentally tests an algorithm that performs a non-myopic planning until the final localization step. The algorithm is based on the policy rollout principle and showed good performance in previous simulative studies. It is adapted to match the needs of a real world setup and evaluated in flight trials. Adaptions include the avoidance of close range measurements to prevent inaccurate measurements at high elevation, and the filtering of poor measurements. © 2023 International Society of information fusion.

关键词： Unmanned aerial vehicles (UAV)

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Distributed Quality of Service Multi-sensor Resource Allocation Model

Distributed Quality of Service Multi-Sensor Resource Allocat...

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IEEE International Conference on Radar

作者： Hans Schily Alexander Charlish Raviraj Adve Anke Schmeink Sensor Data & Information Fusion Fraunhofer FKIE Wachtberg Germany Department of Electrical and Computer Engineering University of Toronto Toronto Canada Chair of Information Theory and Data Analytics RWTH Aachen University Aachen Germany

ISBN: (数字)9798350362381

ISBN: (纸本)9798350362398

Modern phased array multi-function radars come with a large parameter space to optimize their operation, when servicing multiple tasks like search and tracking interleaved. Controlling multiple such radars to pursue a joint goal further increases the parameter space and makes finding the optimal set of radar parameters even more challenging. This paper proposes a new algorithm to allocate a time budget to multiple sensors that jointly optimize for search and tracking. The algorithm is compared to other multi-sensor resource allocation algorithms and an uncoordinated solution. We find that the new algorithm achieves a performance on the same level than the reference methods that jointly optimize the behaviour of the sensors, while requiring fewer model evaluations, which reduces computational requirements.

关键词： Analytical models Computational modeling Spaceborne radar Radar Quality of service Aerospace electronics Radar tracking sensors Resource management Optimization

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Non-myopic sensor Path Planning for Emitter Localization with a UAV

Non-myopic Sensor Path Planning for Emitter Localization wit...

引用

International Conference on information fusion

作者： Folker Hoffmann Hans Schily Markus Krestel Alexander Charlish Matthew Ritchie Hugh Griffiths Sensor Data & Information Fusion department Information Processing and Ergonomics FKIE Fraunhofer Institute for Communication Wachtberg Germany Schönhofer Sales and Engineering GmbH Siegburg Germany Fraunhofer FKIE Department of Electrical Engineering University College London London United Kingdom

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Knowledge based anomaly detection for ground moving targets

Knowledge based anomaly detection for ground moving targets

引用

IEEE Radar Conference

作者： Fotios Katsilieris Alexander Charlish Sensor Data and Information Fusion Department Fraunhofer FKIE Germany

Ground moving target indicator (GMTI) radars are commonly used on airborne platforms in order to detect and track ground targets, such as cars. An operator can use the provided tracks in order to make inference about the behaviour of targets. Prior knowledge, such as road network information, plays a key role in obtaining accurate tracks and thus helping an operator make better inference. This work shows that prior knowledge can also be used for automated anomaly detection when tracking ground targets, thus lowering the workload of an operator. Models for several target behaviours of interest, such as stop-go motion, are presented and tested in simulated examples.

关键词： GMTI Ground moving target tracking Anomaly detection Road network Road information Stop and go

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Nonlinear filter design using Fokker-Planck propagator in Kronecker tensor format

Nonlinear filter design using Fokker-Planck propagator in Kr...

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International Conference on information fusion

作者： Bruno Demissie Muhammad Altamash Khan Felix Govaers Department for Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany

We consider the general continuous-discrete nonlinear filtering problem. In particular, the prediction step involving the numerical solution of the Fokker-Planck equation for the time evolution of the state probability density is known to be a challenging problem as it suffers from the curse of dimensionality. In this contribution a novel approach based on Kronecker tensor decomposition of the matrix exponential of the Fokker-Planck operator is presented. This approach allows solving high dimensional filtering problems while enlarging considerably the time propagation step size compared with finite-difference time stepping methods. We show results from simulations for a passive tracking example involving a four dimensional state vector and compare with other tensor decomposition based approaches.

关键词： Tensile stress Mathematical model Finite difference methods Noise measurement Matrix decomposition Nonlinear filters

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A position free boresight calibration for INS-camera systems

A position free boresight calibration for INS-camera systems

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International Conference on Multisensor fusion and Integration for Intelligent Systems (MFI)

作者： Daniel Bender Daniel Cremers Wolfgang Koch Department Sensor Data and Information Fusion Fraunhofer Institute for Communication Wachtberg Germany Technische Universitat Munchen Munchen Bayern DE Department Sensor Data and Information Fusion Fraunhofer Institute for Communication Information Processing and Ergonomics FKIE Wachtberg Germany

ISBN: (纸本)9781467397087;9781467397094

In this paper, we present an innovative calibration procedure to determine the angle misalignments, also known as boresight, between the coordinate systems of an inertial navigation system (INS) and a camera. All currently known approaches integrate positional information from the INS in the optimization process. Thereby, the position errors in the range of a few meters of most INS devices negatively influence the accuracy of the boresight estimation in state-of-the-art calibration methods. By using line instead of classical point features within the calibration process, we are able to perform the optimization without positional information and avoid being affected by the corresponding noisy data. This can improve the calibration results for systems of all accuracy levels. For the first time, a reliable calibration for systems with poor positional estimations is possible. The presented approach can be applied to images observing a checkerboard, which allows the calibration of the intrinsic camera parameters and boresight misalignment angles from the same dataset. We confirm the high performance of the presented procedure by evaluating simulated and real-world experiments. The achieved results show the capability to reduce the boresight errors to small sub-degree values.

关键词： Cameras Calibration Optimization Position measurement Robot sensing systems Estimation Global Positioning System

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