Near-optimal evasion strategies, from pursuers that employ modern linear guidance laws, are proposed. Most modern guidance laws rely on the evader’s acceleration to minimize miss distance. However, the evader’s acceleration cannot be directly measured and needs to be estimated. The key idea underlying the proposed approach is to exploit the inherent time delay associated with the pursuer’s estimate of the evader’s acceleration to maximize the miss distance. This problem is posed in a bounded target acceleration optimal-control framework with linear pursuer and evader dynamics of arbitrary order. The evader is assumed to have perfect information on the pursuer’s states, parameters, and guidance law. The pursuer is assumed to have perfect information on the evader’s parameters and states; however, the pursuer’s estimate of the evader’s acceleration is assumed to have a pure delay. The optimal evasion strategies are derived, analytically studied, and extensively evaluated in linear, deterministic and nonlinear, stochastic Monte Carlo simulations. The proposed evasion strategies against this class of pursuers substantially increase the miss distance when compared with strategies that do not exploit estimation delay.


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    Titel :

    Near-Optimal Evasion from Pursuers Employing Modern Linear Guidance Laws


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2021-06-28


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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