Pseudorange Measurement Method Based on AIS Signals.

Aimed at addressing the problem of carrier synchronization for satellite-based Automatic Identification System (AIS) signals, a novel data-aided carrier frequency offset estimation method in the intermediate frequency is proposed in this paper. AIS signals use Gaussian Minimum Shift Keying (GMSK) for transmission, and a nonlinearity of the GMSK signal is shown to be a sine wave with frequency related to the carrier frequency offset. Based on that, this method constructs an auxiliary function with the available symbols to avoid the influence of the modulated phase information, and it estimates the frequency offset due to Doppler shift with a new interpolated FFT method. Moreover, this method performs better when the signals are filtered by band pass filter even through the bandwidth is as low as the 1/3 nominal bandwidth. Computer simulations are used to assess the synchronizer performance on AWGN channels.

Global Navigation Satellite Systems (GNSS), today the primary mean for Position, Navigation and Timing (PNT) information on-board of a vessel, are highly vulnerable to unintentional and intentional interference like jamming or spoofing. Therefore, maritime community seeks for an alternative system to compensate this thread and follow the vision of the eNavigation strategy of International Maritime Organization (IMO), a safe navigation of vessels from berth to berth. The only alternative terrestrial backup for GNSS is the enhanced LOng-RAnge Navigation (eLORAN). However, that system will probably never reach global coverage because a substantial part of LORAN stations was shutdown in the years 2010 to 2015. There are only certain regions where it is still usable as well as Chayka, the Russian system. Today, in case of a temporal loss of GNSS no system can provide absolute positioning in areas with increased necessity for reliable navigation data provision on a global scale. One candidate for a terrestrial backup system is R(anging)-Mode which utilizes existing maritime radio infrastructure for the broadcast of modified signals, which allow distance estimation to the transmitter. First feasibility studies were done in the North Sea, in China and in South Korea. The Baltic Sea is due to the high number of vessels along the shipping routes and its sensitive marine ecosystem a suitable region for the implementation and testing of R-Mode firstly as a terrestrial backup system to GNSS. It will supplement navigation information in order to reduce the risk of collisions and groundings. New marine applications that require a continuous provision of position information will be made possible at sea, in coastal areas and in harbours. A consortium of 12 research institutions, administrations and industry of Germany, Poland, Sweden and Norway is currently engaged to setup the first R-Mode testbed, which utilizes IALA (International Association of Marine Aids to Navigation and Lighthouse Authorities) beacons and Automatic Identification System (AIS) land stations for the broadcast of R-Mode enabled signals. This will be organized in the southern Part of the Baltic Sea until 2020 funded by EU within the scope of R-Mode Baltic Project. Beside this main goal of the Project (back-up to GNSS) further research and development activities will be conducted. This comprises the selection of most suitable way of R-Mode service implementation on IALA beacon and AIS signals without disruption of the legacy service. Further the selection of best algorithms for positioning either with only one type of R-Mode signals or with both is part of the research activities. In addition a concept development and test installation for the time synchronization of a transnational network of R-Mode stations which is currently maintained by independent national maritime administrations as well as the development of first prototypes of R-Mode receiver capable to cope with modified IALA beacons and/or AIS signals as well as R-Mode base station hardware for R-Mode signal generation is planned. Finally, with R-Mode enabled PNT data processing and Pilot Plug Unit the first two R-Mode applications will be made available. All this activities will be done in close contact with the maritime administrations, IALA, and maritime users. It is anticipated, that R-Mode will be a terrestrial backup system that can fulfil their need for robust and reliable PNT data for safe navigation at sea. Beside a general description of the project first results of a common coverage prediction for the IALA beacon and AIS communication channels for the Baltic Sea region will be estimated and presented. Latter shows that especially the relevant Baltic Sea region with its narrow passages of coastlines in the North (Denmark, Norway and Sweden) and in the South (Germany, Poland) is already well equipped with a dense network of IALA beacons and AIS stations in the vicinity of vessel routes. In case of positive Project results, upgrading all of them to R-Mode service level these would allow positioning in the entire region. Furthermore, the output of the requirement phase study on the R-Mode system and its components is presented. This was done starting from relevant documents of IMO and IALA requirements for a terrestrial backup system were extracted and next further broken down for specific components of the R-Mode system. This shall give guidance throughout the project when selecting appropriate algorithms, methods and technical solutions.

In order to verify the feasibility of atmospheric duct inversion method using automatic identification system signal in the actual sea area, a sea experiment was carried out. The signal acquisition system of portable high sensitivity civil automatic identification system is developed, and the receiving and processing process of automatic identification system signal is analysed. The sea experiment scheme and main experiment equipment are given, and the collected experiment data are processed and analysed. Finally, the method of atmospheric duct inversion using automatic identification system signal is verified by the measured data. Atmospheric duct inversion is an inverse problem, which requires the use of various optimisation algorithms to optimise the duct parameters in order to obtain the characteristic parameter information of the duct. In this paper, the Lévy flight quantum‐behaved particle swarm optimisation algorithm and the deep learning algorithm are respectively used to invert the atmospheric duct parameters. The results show that there is little difference between the inverted duct parameters and the true duct parameters, which verifies the feasibility of using the automatic identification system signal to invert the atmospheric duct.

In this paper, we consider an impulse-based ultra- wideband (UWB) receiver and assess the performance of different multiple access and modulation schemes, including time-hopping pulse position modulation (TH-PPM), time-hopping binary phase shift keying (TH-BPSK), and BPSK-BPSK, under both the additive white Gaussian noise (AWGN) and indoor multipath (CM3) channel assumptions. The assumed receiver combines the received pulses to increase the signal to noise ratio (SNR) and correlates the summed signal with the locally generated template. The performance of the different techniques are estimated using Monte-Carlo simulations and validated by comparing them with the theoretical results obtained for the AWGN channel with the characteristic function (CF) method presented in [1], Amongst other results, we show that the AWGN channel assumption provides rather optimistic results as compared to the more realistic CM3 indoor channel assumption.

With the rapid development of global industry, AIS (automatic identification system) has become an important tool for ship management and safety monitoring. In order to better display the frequency distribution of AIS signals, this paper graphically displays the data in the AIS signals, allowing users to fully understand the data in the AIS signals, including ship type distribution, speed range, and signal frequencies in different areas. It uses Kafka and Flink technology to receive, clean and analyze the sent data, and finally stores it in MySQL and Redis data. It reads the data through Spring Boot + MyBatis, and uses Vue + Echarts chart tool and AutoNavi Map API for display and analysis. To gain an in-depth understanding of its importance and application prospects in the field of epidemics.

Future communication system requires large bandwidths to achieve high data rates, thus rendering analog-to-digital conversion (ADC) a bottleneck due to its high power consumption. In this paper, we consider monobit receivers for QPSK. The optimal monobit receiver under Nyquist sampling is obtained and its performance is analyzed. Then, a suboptimal but low-complexity receiver is proposed. The effect of imbalances between In-phase (I) and Quadrature (Q) branches is carefully examined. To combat the performance loss due to IQ imbalances, monobit receivers based on double training sequences and eight-sector phase quantization are proposed. Numerical simulations show that the low-complexity suboptimal receiver suffers 3dB signal-to-noise-ratio (SNR) loss in additive white Gaussian noise (AWGN) channels and only 1dB SNR loss in multipath channels compared with matched-filter monobit receiver with perfect channel state information (CSI). It is further demonstrated that the amplitude imbalance has essentially no effect on monobit receivers. In AWGN channels, receivers based on double training sequences can efficiently compensate for the SNR loss without complexity increase, while receivers with eight-sector phase quantization can almost completely eliminate the SNR loss caused by IQ imbalances. In dense multipath channels, the effect of imbalances on monobit receivers is slight.

This paper addresses the problem of error correction in a multi-user trellis coded system in the presence of bit stuffing. In particular, one considers the situation in which automatic identification system (AIS) signals are received by a satellite. The proposed receiver uses a cyclic redundancy check (CRC) for error correction. A Viterbi algorithm based on a so-called extended trellis is developed. This trellis is defined by extended states composed of a trellis-code state and a CRC state. Moreover, special conditional transitions are defined in order to take into account the possible presence of bit stuffing. The proposed algorithm was first developed in a single-user context. It is generalized in this paper to a multi-user scenario by designing an interference mitigation method. This method allows one to derive a demodulation algorithm whose complexity is almost identical to that obtained in the single-user context. Some performance results are presented in the context of AIS and compared with results provided by existing techniques.

Automatic identification of digitally modulated signal has to be able to identify the digitally modulated signal correctly and accurately. Importance of automatic identification of digitally modulated signals are rising increasingly. In this paper an advanced technique is presented, that automatically identifies the multi-user chirp modulated signals in Additive White Gaussian Noise (AWGN) channel. The proposed technique is implementing high order moments (fourth, sixth, and eighth) of detail coefficients of discrete wavelet transform (DWT) as a feature extraction set. Adaptive Neural-Fuzzy Inference System (ANFIS) is proposed as a classifier. The proposed identification procedure is capable of identifying multi-user chirp modulated signals with high accuracy at 0dB, 5dB, and 10dB Signal to Noise Ratio (SNR), over AWGN channel.

Evaluation of error rate of a digital communication system is usually done using the Monte Carlo simulation method. The main drawback of the Monte Carlo method is the need of a huge sample size for estimating low error rates. This paper introduces a novel quasi-analytical technique for estimating the error rate of a communication link over an Additive White Gaussian Noise (AWGN) channel, which greatly outperforms the Monte Carlo method. This technique is demonstrated for a simple spherical code.

Communication systems are affected by channel distortions. Impulsive noise is one of the significant factors for channel impairments. The standard additive white Gaussian noise (AWGN) channel model and conventional estimation algorithms like least mean square (LMS) and its variants tend to be ineffective under such conditions. This paper presents a robust adaptive channel estimation algorithm using the Geman-McClure estimator in a diffusion-based distributed network. The analytical study on mean stability and mean square analysis is carried out under two separate noise statistics: Symmetric α-stable ( SαS) and Bernoulli-Gaussian (BG) distribution. The computer simulations confirm the proposed algorithm's competitive robustness compared to the Maximum Correntropy Criterion and Minimum Kernel Risk Sensitive Loss algorithms at a high impulsive noise environment without exponential cost function. Further, the efficiency is also verified by simulating the bit error rate by designing a minimum mean square error (MMSE) equalizer with the estimated coefficients.

We study the whole process of using Low Earth Orbit (LEO) satellite constellation to localize Automatic Identification System (AIS) emitter, especially the methodologies of intelligently improving and modifying LEO satellite constellation positioning algorithm based on AIS data. In this vein, we design a simulation system for cooperative localization of vessels based on the AIS signals they emit, with a LEO satellite constellation. We implement key modules such as vessel motion simulation, AIS signal simulation, satellite-to-ground link simulation, localization algorithm module and system visualization. The simulation results of single satellite and multi-satellites localization systems verify the effectiveness of the proposed system.

This paper presents asymptotic multiuser efficiency (AME) performance analysis of the decorrelator based successive interference cancellation (DBSIC) DS-CDMA multiuser receiver DBSIC is similar to the conventional SIC receiver except that a decorrelator is used at each detection stage prior to cancellation. AMEs of DBSIC are compared with those of single-user matched filter, optimum, decorrelating and conventional SIC receivers over both additive white Gaussian noise (AWGN) and Rayleigh fading channels. It is shown that over AWGN channels, DBSIC AME is lower than the optimum receiver AME when the interfering user is weaker than the user of interest but approaches the unity optimum receiver AME as the interferer becomes stronger than the user of interest. For all spreading codes cross-correlation considered, DBSIC has a similar AME curve shape as the conventional SIC receiver but has a higher AME which remains positive for all user energy ratios, illustrating its near-far resistance over AWGN channels. The AME of DBSIC is better than that of the decorrelating detector when the interferer is much weaker or slightly stronger than the user of interest and has worse performance when the interferer is not much weaker. It is shown that DBSIC is completely near-far resistant over Rayleigh fading channels with the same AME as the decorrelating scheme for user 1 and as the optimum scheme for user 2, both AMEs being independent of the user energy ratio. This shows that DBSIC is preferable compared to the decorrelating detector, while still being less complex than the optimum scheme over Rayleigh fading channels

This correspondence analyzes the performance of concatenated coding systems and modulation schemes operating over the additive white Gaussian noise (AWGN) channel by examining the loss of capacity resulting from each of the processing steps. The techniques described in this correspondence allow the separate evaluation of codes and decoders and thus the identification of where loss of capacity occurs. Knowledge of this capacity loss is very useful for the overall design of a communications system, e.g., for evaluating the benefits of inner decoders that produce information beyond the maximum-likelihood (ML) estimate. The first two sections of this correspondence provide a general technique for calculating the composite capacity of an orthogonal or a bi-orthogonal code and the AWGN channel in isolation. The later sections examine the composite capacities of an orthogonal or a bi-orthogonal code, the AWGN channel, and various inner decoders including the decoder estimating the bit-by-bit probability of a one, as is used in turbo codes. The calculations in these examples show that the ML decoder introduces a large loss in capacity. Much of this capacity loss can be regained by using only slightly more complex inner decoders, e.g., a detector for M-ary frequency-shift keying (MFSK) that puts out the two most likely frequencies and the probability the ML estimate is correct produces significantly less degradation than one that puts out only the most likely frequency.

Modulo lattice additive noise (MLAN) channels appear in the analysis of structured lattice codes with lattice decoding for Costa's dirty-paper channel and the additive white Gaussian noise (AWGN) channel. Building on the recent result on the optimal density of an infinite constellation over an AWGN channel, in this paper, it is shown that with a proper choice of the shaping lattice and the scaling parameter, the dispersion of the MLAN channel is asymptotically the same as that of the (zero-interference) AWGN channel at the same signal-to-noise ratio.

The Orthogonal Frequency Division Multiplexing (OFDM) is also known as multicarrier technology. Wideband digital communications in the recent past have increasingly utilized OFDM. It can withstand difficult channel circumstances, efficiently utilize spectrum resources, decrease ISI, and operate at a high data rate, among many other benefits. It has been used in several wireless and wired communication systems, including fourth generation Long-Term Evolution (4G LTE) mobile communications. The performance assessment and analysis of the OFDM system under Additive White Gaussian Noise (AWGN) channel has been carried out in this work. The factors in which system performance is assessed include the signal quality, Bit Error Rates (BERs), and Signal to Noise Ratios (SNRs) of the received signals. To improve performance while employing multicarrier modulation, the subcarriers must be kept orthogonal to one another, in the process known as OFDM. The sole focus of this study is the performance analysis of PAPR, BER, and SNR utilizing various modulation methods and schemes.