1,720,957 research outputs found
Sensor management for surveillance and tracking: An operational perspective
No full textRadars have gained increased popularity as sensing devices due to their unique capability to sense objects of interest at very long distances and without being severely limited by weather conditions. Advances in technology have led to the possibility of choosing the sensing parameters of a radar in order to further improve its performance. Especially in the class of active phased array radars, the control of the agile beam is of paramount importance. By controlling the radar beam improved estimation results can be achieved leading to better situation awareness. In the literature, several approaches to sensor (including radar) management can be found. These can be roughly grouped into: a) rule-based or heuristics; b) task-based; c) information-driven; and d) risk/threat-based. These approaches are compared in this thesis and it is found that there is not a single approach that is both Bayes-optimal and takes into account explicitly the user requirements in different operational contexts. In order to overcome the challenges with the existing approaches, this thesis proposes managing the uncertainty in higher-level quantities (as per the JDL model) that are directly of interest to the operator and directly related to the operational goal of the radar system. The proposed approach is motivated by the threat assessment process, which is an integral part of defence missions. Accordingly, a prominent example of a commonly used higher-level quantity is the threat-level of a target. The key advantage of the proposed approach is that it results in Bayes-optimal sensor control that also takes into account the operational context in a model-based manner. In other words: a) a radar operator can select the aspects of threat that are relevant to the operational context at hand; and b) external information about the arrival of targets and other scenario parameters can be included when defining the models used in the signal processing algorithms, leading to context-adaptive sensor management. The proposed approach is initially used in simple tracking examples in order to demonstrate its potential and flexibility. Subsequently, it is used for controlling an agile radar beam such that multiple targets can be tracked while taking into account detection uncertainty and presence of spurious measurements. In these examples, a state-of-the art signal processing algorithm is used, i.e. a CB-MeMBer filter. Finally, the proposed approach is used for area surveillance, i.e. for detection and tracking of multiple targets while taking into account detection uncertainty and presence of spurious measurements. In this context, a density that estimates where any undetected targets might be (denoted as unDTD) plays a key role in balancing the search-to-track time ratio. The presented examples have been drawn both from the civilian and the military domain. From the civilian domain, air-traffic-control examples are shown where threat is modeled based on how fast and how close to each other two aircrafts might come. From the defence domain, asset protection examples are shown where threat is modeled based on how fast and how close to an asset of interest a target might come. Furthermore, the deviation from expected trajectories has been modeled because it can be of interest for anomaly detection purposes. The proposed approach has outperformed all the other approaches in the simulated examples presented in this thesis in achieving lower uncertainty in the threat-level of all targets. In all examples, the proposed approach has outperformed naïve approaches, such as periodic or random selection of sensing actions, in a) estimating the correct number of targets present in the considered scenarios; b) localizing the detected targets; and c) maintaining less tracks, thus lowering the computation time at the update step. When only tracking of targets is considered, the proposed approach was only outperformed in tracking accuracy by a scheme that minimizes the expected variance of the estimated number of targets present in the considered scenario and by a derived rule-based scheme. The main challenge when implementing the proposed approach is the mathematical description of threat. Several interesting aspects of threat have been modeled in this thesis but there are even more to be modeled. Taking into account non-measurable aspects of threat poses an added challenge. Other challenges that might be encountered are a) lower tracking accuracy; and b) higher computational complexity, when compared to other sensor management schemes. The presented research can be extended both within the radar domain and by exploring its application to other domains. Two prominent extensions of interest within the radar domain are: a) taking more aspects of threat into account; and b) addressing the target classification problem. Robotics applications, such as autonomous robot path-planning, offer a promising alternative domain for applying the proposed method.Microelectronics & Computer EngineeringElectrical Engineering, Mathematics and Computer Scienc
Design of a particle filter: for robust target tracking in object-induced clutter
No full textElectrical Engineering, Mathematics and Computer ScienceMicroelectronic
Motion estimation for digital video
No full textElectrical Engineering, Mathematics and Computer Scienc
Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation
No full textThe radar resource management problem in a multitarget tracking scenario for multi-function radar is considered. To solve it, an optimal balancing of the sensor budget by applying Lagrangian relaxation and the subgradient method is proposed. In a time-invariant scenario it is shown that the proposed method will lead to balanced budgets based on track parameters like maneuverability and measurement uncertainty. Moreover, since real world applications quickly lead to time-varying scenarios, it is demonstrated how the approach can be extended to such cases. Furthermore the proposed method is compared with other budget assignment strategies. This paper is the first step into exploring optimal non-myopic solutions using a POMDP framework for surveillance radar applications involving detection, tracking and classification.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System
Target Selection for Tracking in Multifunction Radar Networks: Nash and Correlated Equilibria
No full textWe consider a target selection problem for multitarget tracking in a multifunction radar network from a gametheoretic perspective. The problem is formulated as a noncooperative game. The radars are considered to be players in this game with utilities modeled using a proper tracking accuracy criterion and their strategies are the observed targets whose number is known. Initially, for the problem of coordination, the Nash equilibria are characterized and, in order to find equilibria points, a distributed algorithm based on the bestresponse dynamics is proposed. Afterwards, the analysis is extended to the case of partial target observability and radar connectivity and heterogeneous interests among radars. The solution concept of correlated equilibria is employed and a distributed algorithm based on the regret-matching is proposed. The proposed algorithms are shown to perform well compared to the centralized approach of significantly higher complexityGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System
Using Golay Sequences to Improve the Range Performance of Hybrid Codes for MIMO Radar
No full textIn this paper, waveforms for MIMO phased array radar to enhance cross-range resolution are investigated. The problem of high sidelobes in range created by the use of Hybrid Codes with a single waveform and spatial coding is considered and a method to reduce these sidelobes by the use of Golay sequences as spatial codes is proposed. It is shown that the proposed method achieves the same range performance as a phased array radar with one waveform, despite creating additional sidelobes in Doppler.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System
Radar Resource Management for Multi-Target Tracking Using Model Predictive Control
No full textThe radar resource management problem in a multi-target tracking scenario is considered. Partially observable Markov decision processes (POMDPs) are used to describe each tracking task. Model predictive control is applied to solve the POMDPs in a non-myopic way. As a result, the computational complexity compared to stochastic optimization methods such as policy rollout is dramatically reduced while the resource allocation results maintain similar. This is shown through simulations of dynamic multi-target tracking scenarios in which the cost and computational complexity of different approaches are compared.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System
A Constrained POMDP Formulation and Algorithmic Solution for Radar Resource Management in Multi-Target Tracking
No full textThe radar resource management problem in a multitarget tracking scenario is considered. The problem is solved using a dynamic budget balancing algorithm. It models the different sensor tasks as partially observable Markov decision processes and solves them by applying a combination of Lagrangian relaxation and policy rollout. The algorithm has a generic architecture and can be applied to different radar or sensor systems and cost functions.This is shown through simulations of two-dimensional tracking scenarios. Moreover, it is demonstrated how the algorithm allocates the sensor time budgets dynamically to a changing environment in a nonmyopic fashion. Its performance is compared with different resource allocation techniques and its computational load is investigated with respect to several input parameters.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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