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@article{186429,
        author = {G. V. S. VAMSI KRISHNA and K. Rajasekhar},
        title = {Real Time 2-D Ship Formation Registration using Extended Kalman Filter and Modified ICP Algorithm for Anti-Ship Missile Targeting},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {1698-1705},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186429},
        abstract = {In Anti-Ship Missile (ASM) systems, precise identification of the designated target from a group of ships during the terminal guidance phase remains a challenging task due to position uncertainty, dynamic formation changes, and presence of false targets or decoys. This paper presents an enhanced real-time algorithm for ASM target selection based on a Modified Iterative Closest Point (MICP) technique integrated with an Extended Kalman Filter (EKF). The proposed approach performs rigid transformation alignment between seeker-acquired data and reference Fire Control Radar (FCR) data, and refines the estimation through EKF-based state prediction and correction. The algorithm is evaluated across three representative combat scenarios: (i) rigid transformation of target formation, (ii) distorted formation with positional deviations, and (iii) realistic environments involving additional false targets (decoys). For each case, the algorithm demonstrates robust convergence and high matching efficiency while maintaining accurate registration despite measurement noise and formation variations. Simulation results validate the effectiveness of the integrated EKF-MICP framework in improving match fidelity, minimizing error rates, and ensuring correct target selection under various real-time constraints in ASM terminal phase applications.},
        keywords = {},
        month = {November},
        }