Journal of Electrical and Computer Engineering

Volume 2017, Article ID 8097187, 8 pages

https://doi.org/10.1155/2017/8097187

## A Vessel Positioning Algorithm Based on Satellite Automatic Identification System

School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China

Correspondence should be addressed to Shexiang Ma; moc.621@tujt_xsam

Received 25 July 2017; Accepted 2 October 2017; Published 3 December 2017

Academic Editor: Caner Özdemir

Copyright © 2017 Shexiang Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

Vessels can obtain high precision positioning by using the global navigation satellite system (GNSS), but when the ship borne GNSS receiver fails, the existence of an alternative positioning system is important for the navigation safety of vessel. In this paper, a localization method based on the signals transmitted by satellite-based automatic identification system (AIS) is proposed for vessel in GNSS-denied environments. In the proposed method, the positioning model is a modification on the basis of time difference and frequency difference of arrival measurements by introducing an additional measurement, and the measurement is obtained through the interactive multiple model algorithm. The performance of the proposed strategy is evaluated through simulations, and the results validate the feasibility and reliability of vessel localization based on satellite-based AIS.

#### 1. Introduction

Automatic identification system (AIS) is a self-reporting system designed to protect maritime security of vessel and improve maritime efficiency [1]. It plays an important role in ship collision avoidance and maritime supervision through a series of static and dynamic vessel information automatically broadcast, and the information includes latitude, longitude, course, and velocity [2]. The geographical location reported in AIS is derived by the shipboard GNSS receiver and typically with the high accuracy [3]. However, there is a problem that followed with the GNSS being widely used in navigation of maritime. GNSS is vulnerable to accidental interference [4]; the ship will not be able to locate once the GNSS signal is deliberately disturbed or the GNSS receiver fails. So it is necessary to develop a spare navigation system for the ship.

AIS is a self-organized time division multiple access (TDMA) system, which not only can be self-reporting but also can receive AIS information [5]. Although AIS ignored the role of the satellite in its original design; it has been proven feasible to receive AIS signals by satellite [6, 7]. In the satellite-based AIS, the relative speed of satellite and ship is high, and the two are far apart; therefore, there are challenges for the correct detection of the AIS signal such as the problem of time delay, the high Doppler offset, and low signal-to-noise ratio (SNR) [8]. With the current level of AIS signal detection technology, the correct detection of AIS signal can be guaranteed with the improvement of synchronization algorithm, and the influence of high Doppler offset on carrier recovery is gradually decreasing [9]. The satellite-based AIS is already operational but focuses on the stage of “vessel transmitting, satellite receiving.” In view of the fact that a large number of AIS signals are likely to reach the satellite at the same time in this stage but satellite can still detect ship signals [8], the signals can definitely be received by the ship if the satellite can send information in the AIS operating frequency band according to the AIS protocol, because the possibility of AIS signal conflict is relatively low in case of the ship reception thanks to the characteristics of signal transmission. As the technology of satellite-based AIS advances, the potentiality of AIS for navigation becomes a concern and there is the investigation on ship localization using AIS signals received by satellite [10]. In this paper, we assume that, in advanced satellite-based AIS, vessels can receive AIS signals transmitted from satellite in addition to “vessel transmitting, satellite receiving,” and the information of satellite motion state is broadcast by the downlink AIS signal. On the basis of this vision, a ship localization method using AIS signals transmitted from satellite is proposed.

Among the various measurements for positioning tasks, the time of arrival (TOA), the time difference of arrival (TDOA), and the frequency difference of arrival (FDOA) are very representative choices because of the potentials in attaining high localization accuracy [11, 12]. There is a lot of research on the application of TDOA to improve the positioning accuracy of the stationary target and to locate the moving target by using frequency measurements [13–15]. In addition, the positioning methods combining two kinds of measurements such as TDOA/FDOA and TDOA/DOA are also widely discussed [16, 17]. Except for reducing the number of signals required, the combination of time and frequency measurements is attractive for improvement of positioning accuracy [18, 19]. In these methods, however, only the information extracted from the received signals is used for positioning. Taking into account the fact that AIS can obtain the ship velocity and heading by connecting external sensors, in this paper, a modification positioning model based on TDOA/FDOA is proposed by introducing an additional measurement based on the interactive multiple model (IMM) algorithm [20, 21]. The method of TDOA/FDOA and the IMM algorithm are used separately for locating or tracking the target in general; given the characteristic of AIS signal carrying information, they are combined together in the study. Besides, for the purpose of making the estimated result more suitable for the vessel status, a new probability updating method for IMM is designed in this work.

The solution of TDOA/FDOA measurement equation is complicated because of the high nonlinearity [22]. Taylor-series technique can linearize the equations but positioning result is easy to be affected by initial value setting [23]. The method of grid searching achieves the accuracy improvement with the sacrifice of computation [24]. In this paper, the localization results are obtained by Gauss-Newton iteration under the least squares criterion, and the solution of grid rough searching is chosen as the starting value. The feasibility of the positioning method based on the advanced satellite-based AIS signals is investigated through the experiment. The location error distributions of the TDOA/FDOA joint location model and the proposed localization model are analyzed in this study.

#### 2. TDOA/FDOA Localization Based on Least Squares Estimation

In satellite-based AIS, satellites are located at a low orbit from 600 km to 1000 km above the ground. The downlink AIS signals will include the Doppler frequency shift because of the relative satellite-ship velocities, and the frequency shift is up to a maximum of ±4 kHz. In order to achieve localization with the limited number of AIS signals and improve the positioning accuracy as much as possible, the work of ship positioning is carried out on the basis of TDOA/FDOA in this paper.

##### 2.1. Principles of TDOA/FDOA

Assuming that is the time cost by the th AIS signal transmitted from satellite to ship, the TDOA between the adjacent signals received by the ship can be expressed asThe FDOA between the adjacent AIS signals can be expressed aswhere is the carrier frequency of the AIS signal and is the signal propagation velocity. is the vessel position vector in the ECEF reference and and are velocity vector and position vector of the satellite when transmitting the th AIS signal, respectively. is the difference of noise between the two time measurements and is the difference of noise between the two frequency measurements.

It is assumed that the number of signals received by the ship in the visual time of the satellite is ; the localization equation matrix based on (1) and (2) can be written as withwhere is the TDOA measurement vector obtained by synchronization technique and is the FDOA measurement vector. is the measurement noise matrix.

##### 2.2. Calculation Based on Least Squares Estimation

On the basis of least squares criterion, the estimator associated with (3) needs to minimize the differences between the measurements and predictions; the equation to be minimized can be written aswhere is the noise covariance matrix, is the measurement vector of TDOA/FDOA, and .

The estimated position value can be obtained by Gauss-Newton iterationwhere matrix iswith The initial position in (6) needs to be defined in advance; the method for determining the initial position (shown in Figure 1) is as follows: setting up a grid with the units of . The grid is centered on the midpoint of the satellite ground trajectory (the track generated during AIS signals transmission) and the range of grid geodetic coordinates is , where and are the maximum visible longitude and latitude of satellite, respectively. Connecting the start and end points of the satellite ground trajectory and dividing the grid into and (two parts) by extending the connecting line. Searching within each part of grid and selecting two points with (). In the cost function , is the measured frequency of the AIS signal and is the estimated frequency of received signal at the grid point, where is the position vector of grid point in ECEF coordinate. In this paper, we select “nearest point” to eliminate the false image which may occur in grid searching, that is, taking the point with the shortest distance from the origin of the ship as the optimal position . The transformation of vessel location from the geodetic coordinate to ECEF coordinate is defined as follows:where and are the longitude and latitude coordinates of vessel and are the ECEF coordinates of vessel. is radius of curvature in prime vertical, where and are the square of the first eccentricity and equatorial radius of the earth defined by WGS-84, respectively.