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Atmospheric Refractivity Estimation from AIS Signal Power Using The Open Geosci. 2019; 11:542–548 Research Article Wenlong Tang, Hao Cha, Min Wei, Bin Tian*, and Xichuang Ren Atmospheric refractivity estimation from AIS signal power using the quantum-behaved particle swarm optimization algorithm https://doi.org/10.1515/geo-2019-0044 Received Aug 23, 2018; accepted Mar 19, 2019 Abbreviations Abstract: This paper proposes a new refractivity profile es- AIS Automatic identification system; timation method based on the use of AIS signal power and IMO: International Maritime Organization; quantum-behaved particle swarm optimization (QPSO) al- PSO: Particle swarm optimization; gorithm to solve the inverse problem. Automatic identifica- QPSO Quantum-behaved particle swarm optimiza- tion system (AIS) is a maritime navigation safety communi- tion; cation system that operates in the very high frequency mo- RFC: Refractivity from clutter; bile band and was developed primarily for collision avoid- SOLAS: Safety Of Life At Sea; ance. Since AIS is a one-way communication system which SPE: Standard parabolic equation does not need to consider the target echo signal, it can es- SSFT: Split-step Fourier transform; timate the atmospheric refractivity profile more accurately. Estimating atmospheric refractivity profiles from AIS sig- nal power is a complex nonlinear optimization problem, the QPSO algorithm is adopted to search for the optimal so- 1 Introduction lution from various refractivity parameters, and the inver- sion results are compared with those of the particle swarm Atmospheric ducting is an abnormal propagation phe- optimization algorithm to validate the superiority of the nomenon resulting from the varying refractivity of air, QPSO algorithm. In order to test the anti-noise ability of the which can cause anomalous propagation of electromag- QPSO algorithm, the synthetic AIS signal power with differ- netic waves. In the marine environment, there is a high ent Gaussian noise levels is utilized to invert the surface- probability of ducts occurring at any time and in any sea based duct. Simulation results indicate that the QPSO al- area, which has a significant impact on the performance gorithm can invert the surface-based duct using AIS signal of radar and communication systems [1]. Therefore, it is power accurately, which verify the feasibility of the new important to estimate the atmospheric refractivity profile atmospheric refractivity estimation method based on the for the performance evaluation and prediction of maritime automatic identification system. radar and communication systems. Keywords: refractivity estimation, automatic identifica- Currently, the method of remote sensing detection is tion system, surface-based duct, quantum-behaved parti- mainly used to estimate atmospheric refractivity profile, cle swarm optimization algorithm and refractivity from clutter (RFC) technique has been an active field of research. RFC estimate refractivity profile of the atmosphere from the sea surface reflected radar clut- ter signal [2–6]. This method holds the characteristics of remote, indirect, real-time, cheap and convenient. Real- *Corresponding Author: Bin Tian: College of Electronic Engineer- time detection can be achieved without increasing any ad- ing, Naval University of Engineering, Wuhan 430033, China; Email: ditional equipment by RFC, because it depends on radar [email protected] measurements only. In recent years, RFC has become a Wenlong Tang, Hao Cha: College of Electronic Engineering, Naval hot research method of estimating atmospheric refractiv- University of Engineering, Wuhan 430033, China ity profile. Although RFC has certain advantages, it actu- Min Wei: The Unit 31003 of PLA University, Beijing 100191, China Xichuang Ren: The Unit 91469 of PLA University, Beijing 100841, ally has the following limitations [7]: In order to estimate China the atmospheric refractivity profile, radar need to transmit Open Access. © 2019 B. Tian et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 License Atmospheric refractivity estimation from AIS signal power using the algorithm Ë 543 high-power signals for active detection, which easily inter- 2 Automatic identification system feres with the normal operation of electronic equipment in the relevant area. In addition, the uncertainty of the cur- In 2000, as a part of the Safety Of Life At Sea (SOLAS) rently utilized normalized radar cross section model of the regulations [14], the International Maritime Organization sea surface will severely limit the accuracy of the inversion. (IMO) require AIS to be fitted aboard all ships of 300 gross When sea surface and weather (volume) clutter is hard to tonnage and upwards engaged on international voyages, separate such as in precipitation, the shortcoming of the cargo ships of 500 gross tonnage and upwards not engaged current RFC approaches is evident. on international voyages and all passenger ships irrespec- However, if we use the automatic identification system tive of size. It came into full force on December 31, 2004, (AIS) for refractivity profile inversion, these problems do and this system is known as Class A AIS, which can auto- not occur. AIS system is a one-way communication system matically provides vessel information, including the ves- that depends on radio wave propagation for the transmis- sel’s identity, type, position, course, speed, navigation sta- sion of AIS signals and the propagation path of AIS signals tus and other safety-related to other ships and to shore sta- will be influenced by the atmospheric conditions [8–10]. tions in its surroundings. It also receives such information Referring to the idea of RFC, this paper proposes a new re- from similarly fitted ships and exchanges data with shore- fractivity profile estimation method based on the AIS sig- based facilities automatically. In 2007, Class B AIS was in- nal power to improve the accuracy of estimating the refrac- troduced for small vessels, including pleasure boats. Class tivity profile. Using existing shipboard and shore-based B messages generally contain less information than Class AIS equipment and AIS networks, no additional equip- A messages. However, they all provide essential safety in- ment is required, the cost is lower, and it is convenient to formation. operate. It can be accurately and efficiently invert the dis- Two international channels are allocated for AIS and tribution of atmospheric ducts over the entire sea surface. both frequencies are in the very high frequency band. They Obviously, atmospheric refractivity profile estimation are 161.975 MHz and 162.025 MHz. As Class A AIS system is an inverse problem, and the powerful and efficient is mandatory for all ships specified by the IMO, we only quantum-behaved particle swarm optimization (QPSO) al- consider this system in this paper. gorithm is presented to estimate the surface-based duct. QPSO algorithm [11–13] is a type of particle swarm opti- mization (PSO) algorithm with quantum behaviour that proposed on the basis of classical particle swarm optimiza- 3 Forward propagation modelling tion algorithm, which is simple, effective and converges rapidly. Because particles in quantum space satisfy unique 3.1 Atmospheric ducts properties of aggregation state, there is no definite tra- jectory when particles move, which enables particles to Since meteorological elements such as temperature, hu- search for global optimal solutions to the entire feasible midity and pressure in the atmospheric environment have solution space. Therefore, the global search performance vertical stratification unevenness characteristics, the at- of the QPSO algorithm is much better than that of classical mospheric refractivity also has vertical stratification un- PSO algorithm. even characteristics. Therefore, electromagnetic waves The remainder of this article is organized as follows. propagating in the atmosphere are affected by atmo- In Section 2, the automatic identification system is intro- spheric refraction. Atmospheric refractivity is defined duced. In Section 3, the forward propagation model used by [15] to calculate the AIS signal power under maritime atmo- N = (n − 1) × 106 (1) spheric duct conditions is provided. In Section 4, a new where n is the refractive index. method to invert the atmospheric refractivity profile using In order to take the influence of the curvature of the the AIS signal power is proposed. Numerical results are an- earth into consideration, the modified refractivity M is in- alyzed and discussed in Section 5, while the paper is con- troduced and defined as cluded in Section 6. (︂ z )︂ M = N + × 106 = N + 0.157z (2) R0 where R0 = 6370 km is the radius of the earth, and z is the height above sea level in m. 544 Ë B. Tian et al. z ward full wave analysis method with the ability to han- dle complex boundary conditions and horizontal inhomo- c2 geneous atmospheric environment, and it also has excel- lent stability and accuracy. The solutions of the parabolic equation method can be achieved by the split-step Fourier transform (SSFT) technique and implemented on a per- zthick M sonal computer in seconds for propagation over a sea sur- face, so it is widely applied to the wave propagation prob- z lems under atmospheric ducting conditions [17]. For the c1 b purpose of analyzing the propagation of AIS signals un- 0 M der atmospheric ducting conditions, the parabolic equa- tion method may be the best choice. Therefore, we utilize Figure 1: Atmospheric modified refractivity profile of surface-based the parabolic
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