A framework integrates particle-based fixed-lag smoothing and semi-Markov maneuver modeling with a generalized guidance law to explicitly account for time-varying estimation delays in stochastic interception.
Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models,
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Comprehensive Approach to Directly Addressing Estimation Delays in Stochastic Guidance
A framework integrates particle-based fixed-lag smoothing and semi-Markov maneuver modeling with a generalized guidance law to explicitly account for time-varying estimation delays in stochastic interception.