A Novel Cooperative Localization Algorithm Using Enhanced Particle Filter Technique In Maritime Search And Rescue Wireless Sensor Network

Keywords

Cooperative localization; Enhanced particle filter; Kullback-Leibler divergence; Maritime search and rescue; Wireless sensor networks

Abstract

Maritime search and rescue (MSR) play a significant role in Safety of Life at Sea (SOLAS). However, it suffers from scenarios that the measurement information is inaccurate due to wave shadow effect when utilizing wireless Sensor Network (WSN) technology in MSR. In this paper, we develop a Novel Cooperative Localization Algorithm (NCLA) in MSR by using an enhanced particle filter method to reduce measurement errors on observation model caused by wave shadow effect. First, we take into account the mobility of nodes at sea to develop a motion model—Lagrangian model. Furthermore, we introduce both state model and observation model to constitute a system model for particle filter (PF). To address the impact of the wave shadow effect on the observation model, we develop an optimal parameter derived by Kullback-Leibler divergence (KLD) to mitigate the error. After the optimal parameter is acquired, an improved likelihood function is presented. Finally, the estimated position is acquired

Publication Date

7-1-2018

Publication Title

ISA Transactions

Volume

78

Number of Pages

39-46

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.isatra.2017.09.013

Socpus ID

85030484761 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85030484761

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