Paper
29 October 1997 Trajectory prediction for ballistic missiles based on boost-phase LOS measurements
Murali Yeddanapudi, Yaakov Bar-Shalom
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Abstract
This paper addresses the problem of the estimation of the trajectory of a tactical ballistic missile using line of sight (LOS) measurements from one or more passive sensors (typically satellites). The major difficulties of this problem include: the estimation of the unknown time of launch, incorporation of (inaccurate) target thrust profiles to model the target dynamics during the boost phase and an overall ill-conditioning of the estimation problem due to poor observability of the target motion via the LOS measurements. We present a robust estimation procedure based on the Levenberg-Marquardt algorithm that provides both the target state estimate and error covariance taking into consideration the complications mentioned above. An important consideration in the defense against tactical ballistic missiles is the determination of the target position and error covariance at the acquisition range of a surveillance radar in the vicinity of the impact point. We present a systematic procedure to propagate the target state and covariance to a nominal time, when it is within the detection range of a surveillance radar to obtain a cueing volume. Mont Carlo simulation studies on typical single and two sensor scenarios indicate that the proposed algorithms are accurate in terms of the estimates and the estimator calculated covariances are consistent with the errors.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Murali Yeddanapudi and Yaakov Bar-Shalom "Trajectory prediction for ballistic missiles based on boost-phase LOS measurements", Proc. SPIE 3163, Signal and Data Processing of Small Targets 1997, (29 October 1997); https://doi.org/10.1117/12.283962
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Missiles

Sensors

Error analysis

Radar

Motion models

Satellites

Monte Carlo methods

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