Chu SC, Shao ZY, Zhong N, Liu GG, Pan JS. An Enhanced Food Digestion Algorithm for Mobile Sensor Localization.
Sensors (Basel) 2023;
23:7508. [PMID:
37687962 PMCID:
PMC10490790 DOI:
10.3390/s23177508]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/15/2023] [Accepted: 08/16/2023] [Indexed: 09/10/2023]
Abstract
Mobile sensors can extend the range of monitoring and overcome static sensors' limitations and are increasingly used in real-life applications. Since there can be significant errors in mobile sensor localization using the Monte Carlo Localization (MCL), this paper improves the food digestion algorithm (FDA). This paper applies the improved algorithm to the mobile sensor localization problem to reduce localization errors and improve localization accuracy. Firstly, this paper proposes three inter-group communication strategies to speed up the convergence of the algorithm based on the topology that exists between groups. Finally, the improved algorithm is applied to the mobile sensor localization problem, reducing the localization error and achieving good localization results.
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