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- W4387466181 abstract "In utilizing a variable-structure multiple-model (VSMM) algorithm for kinematic state estimation, the core step is the model set design. This study aims to refine the existing expected-mode augmentation (EMA) algorithm, a method of model set design. First, the OTSU algorithm is employed to determine an adaptive threshold, which in turn allows for a reasonable partition of the basic model set. Next, a subset of possible models is preserved, reactivating models adjacent to the one with the highest prediction probability, eliminating improbable models, and yielding an augmented expected mode. Additionally, the study leverages the translation properties of radial functions and inverse trigonometric function formulas to derive a maneuvering model for star-convex extended targets under uniformly accelerated conditions. In order to assess the effectiveness of the proposed algorithm and the validity of the established maneuvering model, simulation experiments were carried out in both fixed and random scenarios. The proposed algorithm demonstrates improved performance when compared to the interactive multiple-model algorithm and the unmodified EMA algorithm." @default.
- W4387466181 created "2023-10-10" @default.
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- W4387466181 date "2023-01-01" @default.
- W4387466181 modified "2023-10-11" @default.
- W4387466181 title "Maneuvering Star-Convex Extended Target Tracking Based on Modified ExpectedMode Augmentation Algorithm" @default.
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- W4387466181 doi "https://doi.org/10.1590/jatm.v15.1314" @default.
- W4387466181 hasPublicationYear "2023" @default.
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