Abstract
In this paper, performance of sparse-grid Gauss–Hermite filter (SGHF) in bearings-only tracking (BOT) problem has been studied and compared with the performance of unscented Kalman filter (UKF), cubature Kalman filter (CKF), and Gauss–Hermite filter (GHF). The performance has been compared in terms of estimation accuracy and percentage of track loss, subjected to high initial uncertainty. It has been found that track loss of SGHF is less than all other quadrature filters with comparable estimation accuracy.
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Radhakrishnan, R., Bhaumik, S., Tomar, N.K., Singh, A.K. (2015). Bearing-Only Tracking Using Sparse-Grid Gauss–Hermite Filter. In: Mandal, D., Kar, R., Das, S., Panigrahi, B. (eds) Intelligent Computing and Applications. Advances in Intelligent Systems and Computing, vol 343. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2268-2_37
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DOI: https://doi.org/10.1007/978-81-322-2268-2_37
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