Atmospheric refractivity estimation from AIS signal power using the quantum-behaved particle swarm optimization algorithm

• Main Authors: Tang Wenlong, Cha Hao, Wei Min, Tian Bin, Ren Xichuang
• Format: Article
• Language: English
• Published: De Gruyter 2019-12-01
• Series: Open Geosciences
• Subjects: refractivity estimation; automatic identification system; surface-based duct; quantum-behaved particle swarm optimization algorithm
• Online Access: https://doi.org/10.1515/geo-2019-0044

This paper proposes a new refractivity profile estimation method based on the use of AIS signal power and quantum-behaved particle swarm optimization (QPSO) algorithm to solve the inverse problem. Automatic identification system (AIS) is a maritime navigation safety communication system that operates in the very high frequency mobile band and was developed primarily for collision avoidance. Since AIS is a one-way communication system which does not need to consider the target echo signal, it can estimate the atmospheric refractivity profile more accurately. Estimating atmospheric refractivity profiles from AIS signal power is a complex nonlinear optimization problem, the QPSO algorithm is adopted to search for the optimal solution from various refractivity parameters, and the inversion results are compared with those of the particle swarm optimization algorithm to validate the superiority of the QPSO algorithm. In order to test the anti-noise ability of the QPSO algorithm, the synthetic AIS signal power with different Gaussian noise levels is utilized to invert the surface-based duct. Simulation results indicate that the QPSO algorithm can invert the surface-based duct using AIS signal power accurately, which verify the feasibility of the new atmospheric refractivity estimation method based on the automatic identification system.