Profile-based Maximum Penalised Likelihood Trajectory Estimation from Space-borne LOS Measurements
Keywords: Trajectory estimation, poor-observability, pseudo-measurements, Likelihood estimator
AbstractEstimating the boost-phase trajectory of a ballistic missile using line of sight measurements from space-borne passive sensors is an important issue in missile defense. A well-known difficulty of this issue is the poor-observability of the target motion. A profile-based maximum penalised likelihood estimator is presented, which is expected to work in poor-observability scenarios. Firstly, a more adaptable boost-phase profile is proposed by introducing unknown parameters. Then, the estimator is given based on the Bayesian paradigm. After that, a special penalty for box constraint is constructed based on a mixed distribution. Numerical results for some typical scenarios and sensitivity with respect to a priori information are reported to show that the proposed estimator is promising.
How to Cite
Yi, T., Shen, Z., Wang, Z., Liu, B., & Yi, D. (2016). Profile-based Maximum Penalised Likelihood Trajectory Estimation from Space-borne LOS Measurements. Defence Science Journal, 66(3), 278-286. https://doi.org/10.14429/dsj.66.9226
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