Error estimation in ballistic missile trajectory using Kalman Filter

The Kalman Filter is a very successful and popular tool for the estimation of posterior information of several engineering and non-engineering applications. In engineering applications, the estimation of the state of a ballistic missile is an important requirement for the reliable deployment of an anti ballistic missile (ABM) system. But during the measurement of its flight through radar there are many disturbances that tend to add significant amount of error in its readings thus reducing the effectiveness of ballistic missile defense system. Many researches conducted in the field estimated the state of the missile and tried to minimize the error by using various techniques such as Bayesian theorem, Kalman filter and extended Kalman filter. This research examines the Radar related errors, studies the extent of its impacton ABM system and proposes a solution to minimize the errors and increase the effectiveness of the system. The results obtained are used for error estimation in the filtered radar data and theoretically predicted trajectory of the missile. This approach considerably reduces the error and achieves a high level of accuracy in target interception.