Abstract
To guarantee that ships can navigate safely, the International Maritime Organization mandates that all ships navigating internationally must install the automatic identification system (AIS). AIS works in the very high-frequency (VHF) maritime mobile band, and to ensure the signal receiving performance of AIS equipment, it is necessary that the receiver sensitivity can be quickly evaluated and detected. Hence, we propose an evaluation model of AIS receiver sensitivity. The model first measures the packet error rate (PER) of AIS data transmission at a specific power. The distribution of the AIS receiver sensitivity characteristic curve under any transmitted power can be directly obtained, and then whether or not the sensitivity of the AIS receiver satisfies the performance requirements can be quickly evaluated. Regression analysis and the results of actual measurement demonstrate that this model has a goodness of fit (R-squared) value of 0.99 between the power-PER curve of the analog input signal and the measured data, which signifies test efficiency and accuracy beyond conventional test methods.
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Author Keywords
- Automatic identification system (AIS) ,
- AIS receiver ,
- automated test platform ,
- evaluation model ,
- R-squared ,
- sensitivity measurement
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IEEE Keywords
- Artificial intelligence ,
- Receivers ,
- Sensitivity ,
- Marine vehicles ,
- Power measurement ,
- Mathematical model ,
- Testing
Introduction
PRESENTLY , an Automatic Identification System (AIS)is a Navaid System commonly applied in maritime safetyand communications between ships and shores, as well asships and ships [1,2]. In recent years, the number of AISusers has consistently increased, and maritime communicationenvironments have become increasingly complex. In partic-ular, certain busy waters show high data link loads. Forexample, the data-link loads in the Gulf of Mexico, Japan,and the Korean Peninsula measure 64%, 40%, and 40%,respectively [3]. In a 2012 preliminary study conducted inChina, it was discovered that the average occupancy rate ofthe AIS channel in Shanghai Port and Bohai Bay reached30% during rush traffic hours [4]. Meanwhile, the rising ofe-Navigation and the development of the VHF Data ExchangeSystem (VDES) undoubtedly heighten safety requirements formaritime navigation and communication quality [5,6]. As aNavaid System that has been widely used in ship collisionavoidance, the reliability of the AIS system is closely related tothe performance of the AIS receiver. The sensitivity parameteris the key index of performance evaluation, which affects not only communication quality but also the coverage andcapacity of the communication network [7]-[9]. Therefore, itis necessary to study efficient and reliable methods that cantest, analyse and evaluate the sensitivity of the AIS receiver,which is of great significance to research on automatic testtechnology and AIS equipment performance.Conventional receiver sensitivity measurement use an ex-haustive search method to identify the receiver sensitivitywithin a specified range [10]. This method has low accuracyand takes a significant amount of time to measure, whichaffects the performance evaluation of receiver sensitivity.Presently, researches on measurement and evaluation methodsfor receiver sensitivity focus on the mobile communicationfield. Y. Qi et al. [11] propose a technique based on theReceived Signal Strength Indicator for wireless devices, whichgarners the total isotropic sensitivity by measuring the powerlevel at the radio input. S. K. Das et al. [12] present anadaptive switching mechanism for the sensitivity of mobilecommunication receivers, and were able to obtain the bestreceiver sensitivity by measuring the received signal strengthand Bit Error Rate (BER). J. Yao et al. [13] put forth a methodbased on the parametric division algorithm to optimise thereceiver sensitivity measurement, and obtain the sensitivity ofvarious frequency points of the receiver through an iterativealgorithm. Z. Quan et al. [14] propose a fast sensitivitymeasurement method for wireless communication systemsbased on bisection search, reducing time spent on the mea-surement by adjusting the number of test packets. M. Zhu [15]offers a method combining a lazy-learning algorithm modelwith parameter estimation based on an iterative least-squaremethod, which relies strictly on real-time data. M. Shimizu etal. [16] study the BER formula under different modulations inmobile communications, and were able to perform an actualmeasurement analysis. Z. Liu et al. [17] propose the conceptof estimating the sensitivity of other frequency points by firstlyestimating the sensitivity of one point and then obtainingthe Power-BER relationship via mathematical fitting. Anothermethod developed by X. Chen et al. [18] involves a PacketError Rate (PER) calculation based on probability theory andthe packet collision model, used mainly to calculate PER incomputer networks.
In addition, there are certain research on AIS receivermeasurement system. To judge the receiving performanceof an AIS system, M. Gong et al. [19] has developed anautomatic measurement system about the PER of AIS mes-sages. A. Dembovskis [20] builts a hardware test platform,which evaluates briefly the characteristics of satellite-borneAIS receivers. A. Bagazhov [21] created an AIS receivingequipment test system, which uses MATLAB to execute thereceiver performance test for sensitivity.
The above public literatures demonstrate that, in recent years, plenty of experts and scholars have researched sen-sitivity measurement and evaluation, as well as statisticalmethods about PER, and few researches have been done onperformance testing of AIS receivers. Among these works,only that by A. Bagazhov used a system of combining softwareand hardware to measure the AIS receiver sensitivity accordingto conventional methods. However, there is no current targetedresearch literature that focuses on a rapid measurement methodand evaluation model of AIS receiver sensitivity.
The international standard IEC 62320-2 [22] recommendsa conventional test plan for the performance of AIS receivers.In such plan, it is necessary for measuring PERs of theAIS receiver under different signal powers that successiveadjustments to the output power of the signal source. However,the conventional test plan cannot guarantee high measurementaccuracy, which is determined by a set power step and requiresa tedious testing procedure, resulting in low measurementefficiency. Aiming to address this issue, we propose a newevaluation model of AIS receiver sensitivity measurement. Onthe basis of meeting the measurement accuracy requirements,this model can quickly evaluate the sensitivity performance ofAIS receivers, while meeting the high-efficiency measurementrequirements. These improvements can help researchers studyhigh-performance AIS receivers and automatic test technologyfor AIS equipment performance.
The remainder of the paper is organised in the followingmanner. Section II describes the sensitivity requirements ofAIS receivers and proposes an evaluation model for sensitivity.Section III analyses the characteristics of the sensitivity model.Section IV outlines the automated test platform for the AISreceiver. Section V details the test plan and results, followedby general conclusions.
Conclusion
Based on the universal receiver sensitivity measurementmethods, this study innovatively proposes a sensitivity mea-surement evaluation model of AIS receivers, and analyses thecompanding curves and variation ranges of the model viapractical measurements. It is found that the companding curveis related to the bit number of packetsn. As n increases,the curve compresses, and the PER performance deterioratesrapidly asPinreduces. As n decreases, the curve broadens,and the PER performance deteriorates gently asPinreduces.The variation interval of the curve is relevant to the BTproduct of the GMSK signal. As BT increases, the inputpower corresponding to the PER’s variation range of thecurve decreases; in other words, the sensitivity performanceincreases and vice versa.
Additionally, the AIS receiver automatic measurement plat-form and measurement plan are outlined in the paper. Theactual measurement results obtained by the measurement plat-form and the estimated values from the sensitivity measure-ment model curves are evaluated in goodness-of-fit tests, theresult of which reaches 0.99 or more. Hence, the measurementmodel can effectively evaluate the sensitivity performanceindex of an AIS receiver and greatly improve the test efficiencyand accuracy compared to traditional test methods.Regarding current AIS market-oriented equipment and theimprovement of receiver performance, this model has greatimpact. As VDES research continues and e-Navigation strate-gies develop, this study can help improve the reliability andcommunication quality of AIS as well as guarantee the safetyof maritime navigation. The present results can even providepractical reference values about VDES for the developmentof equipments with high anti-interference performance, thedesign of test plans and the establishment of internationalstandards in the future.
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FULL Paper PDF file:
Study of an Evaluation Model for AIS ReceiverSensitivity MeasurementsBibliography
author
Year
2020
Title
Study of an Evaluation Model for AIS Receiver Sensitivity Measurements,
Publish in
in IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 4, pp. 1118-1126, April 2020,
Doi
10.1109/TIM.2019.2910341.
PDF reference and original file: Click here
Somayeh Nosrati was born in 1982 in Tehran. She holds a Master's degree in artificial intelligence from Khatam University of Tehran.
Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.
Nasim Gazerani was born in 1983 in Arak. She holds a Master's degree in Software Engineering from UM University of Malaysia.
