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Publication
Calibration Techniques for a New Space Radar Cassegrain Antenna Pointing System
| Name: | Description: | Size: | Format: | |
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| 5.87 MB | Adobe PDF |
Abstract(s)
Esta tese de mestrado investiga a possibilidade de adequar o sistema de radiotelescópio localizado em Pampilhosa da Serra para integração nos Sistemas de Defesa de Mísseis Balísticos (SDMB). No cerne deste estudo está uma simulação avançada desenvolvida em MATLAB, meticulosamente desenvolvida para capturar a complexidade inerente a trajetórias de mísseis ballisticos e os desafios em rastreá-los usando sistemas de radar. Através de uma série de cenários, a tese de mestrado explorou o desempenho do Filtro de Kalman Estendido (FKE) no rastreamento de mísseis. As Métricas implementadas para avaliar o desempenho e para avaliar a precisão do rastreamento incluem a Raiz do Erro Quadrático Médio (REQM), o Erro Médio Absoluto (EMA) e o Erro Normalizado de Estimação ao Quadrado (ENEE). É de salientar que, em configurações otimizadas de radar, os valores de REQM atingiram valores tão baixos quanto 41 metros, EMA reduziu para 37 metros e ENEE melhorou significativamente para cerca de 1.5. Estas métricas sublinham o profundo impacto das especificações do radar na precisão do rastreamento e sugerem a potencial eficácia do sistema de radar de Pampilhosa da Serra em aplicações SDMB quando configurado adequadamente.
This master thesis investigates the suitability of the radar system located in Pampilhosa da Serra for integration into Ballistic Missile Defense Systems (BMDS). At the core of this study is an advanced simulation developed in MATLAB, meticulously designed to capture the intricacies of missile trajectories and the challenges in tracking them using radar systems. Through a series of simulated scenarios, the study explored the performance of the Extended Kalman Filter (EKF) in tracking missiles. Key performance metrics, including the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Normalized Estimation Error Squared (NEES), were used to assess the tracking accuracy. Notably, in optimized radar configurations, RMSE values dropped to as low as 41 meters, MAE reduced to 37 meters, and NEES significantly improved to around 1.5. These metrics underscore the profound impact of radar specifications on tracking precision and suggest the potential efficacy of the Pampilhosa da Serra radar system in BMDS applications when appropriately configured.
This master thesis investigates the suitability of the radar system located in Pampilhosa da Serra for integration into Ballistic Missile Defense Systems (BMDS). At the core of this study is an advanced simulation developed in MATLAB, meticulously designed to capture the intricacies of missile trajectories and the challenges in tracking them using radar systems. Through a series of simulated scenarios, the study explored the performance of the Extended Kalman Filter (EKF) in tracking missiles. Key performance metrics, including the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Normalized Estimation Error Squared (NEES), were used to assess the tracking accuracy. Notably, in optimized radar configurations, RMSE values dropped to as low as 41 meters, MAE reduced to 37 meters, and NEES significantly improved to around 1.5. These metrics underscore the profound impact of radar specifications on tracking precision and suggest the potential efficacy of the Pampilhosa da Serra radar system in BMDS applications when appropriately configured.
Description
Keywords
Sistemas de Defesa de Mísseis Balísticos Sistema de Radar Filtro de Kalman Estendido Simulação MATLAB Precisão de Rastreamento REQM EMA ENEE Ballistic Missile Defense Systems Radar System Extended Kalman Filter MATLAB Simulation Tracking Accuracy