A novel cooperative localization algorithm using enhanced particle filter technique in maritime search and rescue...

Area of Science:

• Maritime safety
• Wireless Sensor Networks
• Localization algorithms

Background:

• Maritime search and rescue (MSR) is critical for Safety of Life at Sea (SOLAS).
• Wireless Sensor Network (WSN) technology in MSR faces challenges with inaccurate measurements due to the wave shadow effect.
• Existing localization methods struggle to mitigate these wave-induced errors.

Purpose of the Study:

• To develop a Novel Cooperative Localization Algorithm (NCLA) for MSR.
• To reduce measurement errors in WSNs caused by the wave shadow effect.
• To enhance the accuracy of localization in maritime environments.

Main Methods:

• Developed a Novel Cooperative Localization Algorithm (NCLA) utilizing an enhanced particle filter.
• Incorporated a Lagrangian motion model to account for node mobility at sea.
• Introduced a system model comprising state and observation models for the particle filter.
• Utilized Kullback-Leibler divergence (KLD) to derive an optimal parameter for mitigating wave shadow effect errors.
• Presented an improved likelihood function based on the optimal parameter.

Main Results:

• Successfully reduced measurement errors attributed to the wave shadow effect.
• Enhanced the accuracy of the observation model in the particle filter.
• Achieved more precise position estimation in maritime environments.

Conclusions:

• The Novel Cooperative Localization Algorithm (NCLA) effectively addresses wave shadow effects in MSR WSNs.
• The enhanced particle filter method with KLD-derived parameters improves localization accuracy.
• This algorithm contributes to safer and more efficient maritime search and rescue operations.