The tracking of resident space objects has been a topic of recent concern due to the numerous objects that must be monitored with respect to relatively few sensors that can observe them. This discrepancy creates situations in which sensors have multiple objects within their view and must decide which to observe and which to ignore at a particular time, a process known as sensor tasking or sensor network management. Previous studies have suggested calculating information- (or covariance-) based metrics to aid in this process, which rely on uncertainty estimates of an object’s location obtained using a nonlinear estimator. In these studies, the coupling between estimation and sensor tasking is investigated using two covariance-based tasking strategies in conjunction with two nonlinear estimators applied within a simple planar satellite-tracking simulation. Results demonstrate that the use of more accurate estimators leads to better overall estimates, not only due to the advantages within the estimation methods, but from the improvement in tasking decisions due to selection of these estimators. In addition, the paper introduces a new utility metric based on approximating stability of the estimation error through estimating a largest Lyapunov exponent, which is shown to outperform an existing Fisher information tasking approach.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Coupling of Estimation and Sensor Tasking Applied to Satellite Tracking


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    01.07.2013




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Generalized Minimum-Time Follow-up Approaches Applied to Tasking Electro-Optical Sensor Tasking

    Murphy, Timothy S. | British Library Conference Proceedings | 2017


    Coupling of Nonlinear Estimation and Dynamic Sensor Tasking Applied to Space Situational Awareness (AAS 11-575)

    Williams, P.S. / Spencer, D.B. / Erwin, R.S. et al. | British Library Conference Proceedings | 2012


    Realistic Sensor Tasking Strategies

    Frueh, Carolin | British Library Conference Proceedings | 2016


    Machine Learning Applied to the Optimization of Sst Sensor Tasking

    Urdampilleta, Igone / Arenillas, Daniel Lubian / Grande, Ignacio et al. | TIBKAT | 2022