Positioning Error Analysis of Ranging-Mode Using AIS Signals in China

Zheng, Kai; Hu, Qing; Zhang, Jingbo

doi:10.1155/2016/6928961

Cited by 13 publications

(15 citation statements)

References 6 publications

(6 reference statements)

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“…Then, the vessel estimates its position according to its signals received from shore stations. In Figure 1, if the vessel, such as Vessel 1, can receive signals from at least three AIS shore stations, either the TOA method or the TDOA method can be utilized to estimate the vessel's position in AIS R-mode positioning [25]. However, the layout of existing AIS shore stations was originally designed to satisfy communication requirements.…”

Section: Ais R-mode Positioningmentioning

confidence: 99%

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The Single-Shore-Station-Based Position Estimation Method of an Automatic Identification System

Jiang

Zheng

2020

Sensors

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In order to overcome the vulnerability of the Global Navigation Satellite System (GNSS), the International Maritime Organization (IMO) initiated the ranging mode (R-Mode) of the automatic identification system (AIS) to provide resilient position data. As the existing AIS is a communication system, the number of shore stations as reference stations cannot satisfy positioning requirements. Especially in the area near a shore station, it is very common that a vessel can only receive signals from one shore station, where the traditional positioning method cannot be used. A novel position estimation method using multiple antennas on shipborne equipment is proposed here, which provides a vessel’s position even though the vessel can only receive signals from a single shore station. It is beneficial for solving positioning issues in proximity to the coast. Further, as the distances between different antennas to the shore station are not sufficiently independent, the positioning matrix can easily be near singularity or ill-conditioned; thus, an effective position solving method is derived. Furthermore, the proposed method is verified and evaluated in different scenarios by numerical simulation. We assessed the influencing factors of positioning performance, such as the vessel’s heading angle, the relative position, and the distances between the shore station and the vessel. The proposed method widely expands the application scope of the AIS R-Mode positioning system.

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Section: Ais R-mode Positioningmentioning

confidence: 99%

“…The existing AIS, though, is set up for communication without considering the requirement of positioning. Hence, a vessel cannot receive signals from three different AIS shore stations at the same time in some sea areas [25]. Therefore, the traditional positioning methods are not feasible.…”

Section: Introductionmentioning

confidence: 99%

The Single-Shore-Station-Based Position Estimation Method of an Automatic Identification System

Jiang

Zheng

2020

Sensors

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“…independent plurality gaussian variables in which the zero-mean [43] is {ξi,j}. In order to unify this article, "i" and "j" are used to symbolize nodes #i and #j.…”

Section: System Modelmentioning

confidence: 99%

“…Between nodes #i and #j, there is some definition, including shadowing decay η i,j (dB), l-th path plurality path gain ξ i,j , path loss exponent α, and the distance d i,j . If the ensemble average operation is E[*], then the result is E ξ i,j 2 = 1/L independent plurality gaussian variables in which the zero-mean [43] is {ξ i,j }. In order to unify this article, "i" and "j" are used to symbolize nodes #i and #j.…”

Section: System Modelmentioning

confidence: 99%

A Power Control Algorithm Based on Chicken Game Theory in Multi-Hop Networks

Wang

Gillbanks

et al. 2019

Symmetry

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With the development of modern society, there are not only many voice calls being made over wireless communication systems, but there is also a great deal of demand for data services. There are increasing demands from the general public for more information data, especially for high-speed services with elevated Gbps levels. As is well known, higher sending power is needed once data rates increase. In order to solve this problem, virtual cellular networks (VCNs) can be employed in order to reduce these peak power shifts. If a VCN works well, mobile ports will receive their own wireless signals via individual cells, and then, the signals will access core networks with the help of a central terminal. Power control can improve the power capacity in multi-hop networks. However, the use of power control will also have a negative impact on network connectivity, delay, and capacity. In order to address the problem, this paper compares specific control methods and capacities in multi-hop networks. Distributed chicken game algorithm power control (DCGAPC) methods are presented in order to reach acceptable minimum levels of network delay and maximum network capacity and connectivity. Finally, a computer simulation is implemented, and the results are shown.

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“…We used the coherent demodulation method based on phase locked loop [30], which can theoretically improve the SNR by 3 dB. The subsequent signal processing flow is the engineering realization of the pseudorange measurement scheme described above.…”

Section: Field Test Verificationmentioning

confidence: 99%

Pseudorange Measurement Method Based on AIS Signals

Zhang

Wang

2017

Sensors

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In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system.

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Positioning Error Analysis of Ranging-Mode Using AIS Signals in China

Cited by 13 publications

References 6 publications

The Single-Shore-Station-Based Position Estimation Method of an Automatic Identification System

The Single-Shore-Station-Based Position Estimation Method of an Automatic Identification System

A Power Control Algorithm Based on Chicken Game Theory in Multi-Hop Networks

Pseudorange Measurement Method Based on AIS Signals

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