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<p>In this thesis, a multiple hypotheses tracking (MHT) algorithm is developed to  successfully track multiple ballistic missiles within the boost phase. The success of  previous work on the MHT algorithm and its application in other scientific fields enables  this study to realize an efficient form of the algorithm and examine its feasibility in  tracking multiple crossing ballistic missiles even though various accelerations due to  staging are present. A framework is developed for the MHT, which includes a linear  assignment problem approach used to search the measurement-to-contact association  matrix for the set of exact N-best feasible hypotheses. To test the new MHT, an event in  which multiple ballistic missiles have been launched and threaten the North American  continent is considered. To aid in the interception and destruction of the threat far from  their intended targets, the research focuses on the boost-phase portion of the missile  flight. The near-simultaneous attacks are detected by a network of radar sensors  positioned near the missile launch sites. Each sensor provides position reports or track  files for the MHT routine to process. To quantify the performance of the algorithm, data  from the National Air and Space Intelligence Center's IMPULSE ICBM model is used  and demonstrates the feasibility of this approach. This is especially significant to the U.S.  Missile Defense Agency since the IMPULSE model represents the cognizant analyst's  accurate representation of the ballistic threats in a realistic environment. The results show  that this new algorithm works exceptionally well in a realistic environment where  complex interactions of missile staging, non-linear thrust profiles and sensor noise can  significantly degrade the track algorithm performance especially in multiple target  scenarios.
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<br>Subjects: Ballistics; Electrical engineering; Nonlinear systems; Flight; Guided missiles; Kalman filtering; Algorithms</div>
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Rakdham, Bert</div>
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