RAM target tracking based on improved SR-UPF algorithm
Year: 2024
Type: article
Abstract: RAM target has complex motion, which puts forward higher requirements for tracking system. Aiming at particle degradation and other problems existing in the process of particle filter solving RAM target tracking, this paper calculates the posterior probability density function as the prior probability density function of the particle filter through unscented transformation, so as to improve the fitting degree of the posterior probability density function and finally improve the particle effectiveness. At the same time, qr decomposition is used to replace part of Cholesky decomposition in the process of unscented transformation, so that the variance matrix of the output signal remains non-negative. Finally, this paper establishes a dynamic model for a reentry target trajectory, and simulates with Matlab to verify the effectiveness of the proposed algorithm.
Author: ZHANG Han, ZHANG Xun, LIANG Shen
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6891676417
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