sangeeta_report Essay


AbstractAcknowledgmentAbbreviationTable of Content TOC h z t “Chapter,1,section,2,preChapter,1” Abstract PAGEREF _Toc530826704 h iAcknowledgment PAGEREF _Toc530826705 h iiiAbbreviation PAGEREF _Toc530826706 h vTable of Content PAGEREF _Toc530826707 h viiList of Figures PAGEREF _Toc530826708 h ixList of Tables PAGEREF _Toc530826709 h xi1.Introduction PAGEREF _Toc530826710 h 11.1Background PAGEREF _Toc530826711 h 11.2Motivation PAGEREF _Toc530826712 h 11.3Organization of Report PAGEREF _Toc530826713 h 12.Problem Statement PAGEREF _Toc530826714 h 22.1Literature Survey PAGEREF _Toc530826715 h 22.2Problem formulation PAGEREF _Toc530826716 h 23.System Dynamics and Simulation Model PAGEREF _Toc530826717 h 33.

1Missile Dynamics for the Model PAGEREF _Toc530826718 h 33.2Target Dynamics for the Model PAGEREF _Toc530826719 h 33.3Missile and Target Data used for the Model PAGEREF _Toc530826720 h 33.4Simulation for the validation of dynamics PAGEREF _Toc530826721 h 34.Results and Discussion PAGEREF _Toc530826722 h 44.1Typical SAM system engagement Scenario PAGEREF _Toc530826723 h 45.State Estimation PAGEREF _Toc530826724 h 55.1Estimation essentiality PAGEREF _Toc530826725 h 55.2Estimation Tools PAGEREF _Toc530826726 h 55.3Kalman Filter (KF) PAGEREF _Toc530826727 h 55.4Extended Kalman Filter (EKF) PAGEREF _Toc530826728 h 56.Conclusion and Future Work PAGEREF _Toc530826729 h 66.

1Conclusion PAGEREF _Toc530826730 h 66.2Future Work PAGEREF _Toc530826731 h 67.References PAGEREF _Toc530826732 h 7List of FiguresList of TablesIntroductionBackgroundNumber of Missile guidance schemes is well practiced and available in various literatures. One common requirement for these schemes to become a precise and effective guidance scheme is availability of missile as well as target states. Various sensors are being used to gather the information related to target like Radio detection and ranging (RADAR), Electro-optical tracking system (EOTS), Laser identification detection and ranging (LIDAR), airborne RADARs etc. Similarly for missiles, where we are having freedom to keep our own sensors for accurate measurement of missile states, usually inertial Navigation System (INS) is being used to track the missile states. Now days these sensors are giving the information very accurately apart from measurement of noise.Which is inherent for any physical sensors. Moreover there is a fare probability that few measurements sample may be lost because of loss of tracking, obstacles or even corrupted measurements sample. In this kind of scenario it is inherent to use a good estimator which serve the dual purpose of filtering the measurement noise as well as estimating the states in case of lost of measurement samples.MotivationIn present era of war scenarios, weapon like tactical missiles are of utmost importance to neutralize the threats of aerial attack which are highly maneuverable in nature. Threat targets are continuously improving in terms of technology and maneuvering capability. It is important to improve the accuracy of engagement keeping in mind the catastrophic effect if target goes unattended. Guidance plays a critical role in taking the missile near to moving target from launch point, even though target try to maneuver and escape once came to know that a weapon is launched against it. And for any guidance system to work accurately, states of missile as well as target need to be known as precise as possible. Hence estimation of states are very critical parameters which not only abstract the accurate information from a noisy measurement but also provide the prediction of states for the next time sample or in case of lose of measurement it also assures that missile should not lose its ultimate objective of killing the target just because of losing a few measurement samples.Organization of ReportThis report is organized in different chapters. Chapter-2 explains about the problem statement and the literature survey done for doing this project work. Chapter-3 describes the formulation used for modeling the point-mass model of typical tactical engagement scenario. This chapter explains the detail mathematical modeling of simulation platform created for the generation of true states of missile and target which will be used later for implementing the estimator and comparing the results of estimator design with respect to true states. Chapter-4 shows the results of point-mass model for the typical tactical engagement which also become the reference for comparison of future work. Chapter-5 explains about the various estimator designs especially about usage of kalman filtering for state estimations. Chapter-6 summarizes the current work done for this project work as well as it also explains the work plan for the phase -2 as extension of current work. Last chapter of this report contains a list of reference papers/books/materials, which are also cited throughout the report wherever they are referred.Problem StatementLiterature SurveyProblem formulation System Dynamics and Simulation ModelMissile Dynamics for the ModelTarget Dynamics for the ModelMissile and Target Data used for the ModelSimulation for the validation of modelResults and DiscussionTypical SAM system engagement ScenarioState EstimationEstimation essentialityEstimation ToolsKalman Filter (KF)Extended Kalman Filter (EKF)Conclusion and Future WorkConclusionFuture WorkReferences

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