Fingerprint-based indoor localisation suffers from influences such as fingerprint pre-collection, environment changes and expending a lot of manpower and time to update the radio map. To solve the problem, we propose an efficient radio map updating algorithm based on K-Means and Gaussian Process Regression (KMGPR). The algorithm builds a Gaussian Process Regression (GPR) predictive model based on a Gaussian mean function and realises the update of the radio map using K-Means. We have conducted experiments to evaluate the performance of the proposed algorithm and results show that GPR using the Gaussian mean function improves localisation accuracy by about 13·76% compared with other functions and KMGPR can reduce the computational complexity by about 7% to 20% with no obvious effects on accuracy.

A novel synthetic air data estimation method without using air data sensors is presented, and the method only relies on the information from the Navigation System (NS) and Flight Control System (FCS). The aircraft's aerodynamic model is also required to make a connection between the FCS control parameters and the NS measurements. The airspeed, angle of attack and sideslip, angular velocity and wind speed are defined as state vectors, and state equations are established through the aircraft's aerodynamic model and dynamics. Linear velocity and angular velocity provided by the navigation system are considered as the measurement vector. To deal with variable wind fields, a novel Initialised Three-step Extended Kalman Filter (ITEKF), which considers the wind speed as an unknown input, is developed to track the variation of wind speed. Simulation results based on a Generic Hypersonic Vehicle (GHV) model are presented and compared with an existing method. Factors affecting the method's accuracy include the navigation system accuracy and the aerodynamic model error, are also discussed.

With electronic warfare increasingly complicated and military confrontations increasingly intense, the potential security threat to satellite navigation has become a difficult issue to deal with. Traditional satellite navigation anti-interference technology generally refers to jamming, but less consideration has been given to spoofing. It should be noted that the potential risk induced by spoofing interference is worse than that caused by jamming as the loss of positioning integrity may not be immediately obvious. This paper introduces a spoofing detection method based on a two-antenna structure using fraction parts of double-difference carrier phase observables. If all spoofing signals are transmitted by one single antenna, a spoofing detection hypothesis test can be carried out through the normalisation of double-difference carrier phase observables, without need to consider the integer ambiguity problem, measure the baseline vector and estimate the real directions of signals. The detection scheme adopts an M of N algorithm (if M or more of the test values exceed the threshold, the algorithm declares the presence of a spoofing signal), integrating carrier phase measurements of all the available satellites. Finally, the proposed method is verified by real experiments. This spoofing detection method can easily be applied to GNSS anti-spoofing receivers without changing their architecture and has simple and effective characteristics.

Precise control is a key factor in enabling Unmanned Underwater Vehicles (UUVs) to complete various underwater activities. The development of UUV control rules is mostly based on UUV dynamic models. However, such dynamic models contain unknown hydrodynamic parameters that need to be identified. This paper presents a new method, Laser Line Scanning for Hydrodynamic Parameter Identification (LSHPI), which integrates laser line scanning, decoupled dynamics, and evolutionary optimisation to identify the hydrodynamic parameters of an Autonomous Underwater Vehicle (AUV). In this research, laser images, seen from an on board camera's perspective and created using Open Graphics Library (OpenGL), were used to validate LSHPI's feasibility. The accuracy of the AUV positions and Euler angles obtained by the laser image-based methods were investigated for each decoupled One-Dimensional (1D) motion and the influence of other motion disturbances on the accuracy of the obtained AUV positions or Euler angles was also evaluated. In addition, the accuracy of the surge-related hydrodynamic parameters obtained by LSHPI was investigated under different motion disturbances. Based on the hydrodynamic parameter identification results under different motion disturbances, LSHPI's feasibility was successfully validated.

Solving the problem of ship weather routing has been always a goal of nautical navigation research and has been investigated by many scientists. The operation schedule of an oceangoing ship can be influenced by wave or wind disturbances, which complicate route planning. In this paper, we present a real-coded genetic algorithm to determine the minimum voyage route time for point-to-point problems in a dynamic environment. A fitness assignment method based on an individual's position in the sorted population is presented, which greatly simplifies the calculation of fitness value. A hybrid mutation operator is proposed to enhance the search for the optimal solution and maintain population diversity. Multi-population techniques and an elite retention strategy are employed to increase population diversity and accelerate convergence rates. The effectiveness of the algorithm is demonstrated by numerical simulation experiments.

This paper considers the effect of the biases in Global Positioning System (GPS) observations on satellite clock offset estimation. GPS triple-frequency satellite clock and reference observations are discussed. When the reference observation is selected and the corresponding satellite clock offset is computed, satellite clock offsets for all observations are obtained based on the computed satellite clock offset and the biases between the reference observation and other observations. The characteristics of these biases are analysed, and a service strategy for the GPS triple-frequency satellite clock offset is presented. To evaluate the computed GPS satellite clock offset, the performance in single-point positioning is validated. The positioning results show that the average relative improvements are about 20%, 28% and 19% for north, east and vertical components, when the Differential Code Bias (DCB) (P1-P2), DCB (P1-P5) and modelled Inter-Frequency Clock Bias (IFCB) are corrected. The effect of DCB (P1-P2), DCB (P1-P5) and modelled IFCB on the altitude direction is more evident than on the horizontal directions.

Data derived from the Automatic Identification System (AIS) plays a key role in water traffic data mining. However, there are various errors regarding time and space. To improve availability, AIS data quality dimensions are presented for detecting errors of AIS tracks including physical integrity, spatial logical integrity and time accuracy. After systematic summary and analysis, algorithms for error pre-processing are proposed. Track comparison maps and traffic density maps for different types of ships are derived to verify applicability based on the AIS data from the Chinese Zhoushan Islands from January to February 2015. The results indicate that the algorithms can effectively improve the quality of AIS trajectories.

Vessel behaviour analysis plays an important role in maritime situational awareness. However, available technology still provides only limited approaches to vessel behaviour analysis. In this paper, we propose a visual analytics framework to interactively explore the characteristics of vessel behaviour by means of integrating visualisation with data mining and a human-computer interaction controlling model, which combines human insight with the enormous storage and processing capacities of computers to gain insight into vessel behaviour. In addition, we provide multiple views for visually analysing vessel trajectories, densities and speeds. Case studies with 15 days' AIS data collected from the middle Hankou channel to Yangluo channel in the Yangtze River demonstrate the effectiveness of our approach.

Land masking of Synthetic Aperture Radar (SAR) images is generally accomplished by applying either archived shoreline databases or image segmentation. However, those methods cannot be solely applied to geographical areas complicated with many small islands and exposed rocks. Therefore, we have proposed a new procedure where Sobel edge extraction is applied to detect the edges of all objects from KOMPSAT-5 X-band SAR images, followed by a merging process with the edges from the land objects based on Electronic Navigational Chart (ENC) coastlines. Using the land mask data, geometrically corrected SAR images were masked before applying a ship detection algorithm. This land masking procedure was applied to several images covering different areas of the Korean Peninsula. The results show that land targets such as newly constructed and natural objects were also masked, and thus did not create false alarms during ship detection. Therefore, this method can be used to assist precise ship detection using SAR images in coastal waters.

The Beidou System (BDS) started functioning at the end of 2012. The Yaw-Steering (YS) attitude mode for Inclined Geosynchronous Orbit (IGSO) and Medium Earth Orbit (MEO) satellites in BDS ensures that the solar panels face the Sun. The orbit radial accuracies for IGSO/MEO satellites are 0·5 m and the User Equivalent Range Errors (UERE) are 1·5 m in YS mode. BDS-2 satellites adopt Orbit-Normal (ON) mode to meet the power supply and thermal control requirements of the satellite during deep Earth eclipse periods. In ON mode, long-term orbit ephemeris accuracy monitoring in the Operational Control System (OCS) of BDS indicates that the orbit accuracies for IGSO/MEOs are reduced to a few hundreds of metres, seriously affecting the positioning accuracy and navigation service capability of the BDS system. Solar Radiation Pressure (SRP) is difficult to model in ON mode. Continuous Yaw-Steering (CYS) mode is available for new generation Beidou satellites launched since 2015. The orbit accuracies for these new generation Beidou (BDS-3) satellites were estimated based on BDS monitoring station data and SRP models including ECOM 9/5/3. The evaluation method consisted of four steps, namely, orbit internal consistency analysis, UERE calculation, Satellite Laser Ranging (SLR) data fitting Root Mean Square (RMS) determinations and positioning performance analysis; the data gathering period lasted for more than 60 days and included two CYS periods and one ON period. The experiments showed that the orbit accuracy of the radial component in CYS mode for the BDS-3 satellites degrades by 2 to 3 cm and positioning accuracy degrades only by 1 cm over that in YS mode which is just a small reduction in accuracy compared with the decimetre-level BDS orbit accuracy and the metre-level single point positioning accuracy with BDS pseudorange data. This overcomes declining orbit and positioning accuracy issues in ON mode for BDS-2 satellites. Other results also show that the reliability of BDS has been improved.

This paper proposes a model for combined Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) Real-Time Kinematic (RTK) positioning. The approach uses only one common reference ambiguity, for example, that of GPS L1, and estimates the pseudo-range and carrier phase system and frequency biases. The validations show that these biases are stable during a continuous reference ambiguity period and can be easily estimated, and the other estimated double-differenced ambiguities, such as those of GPS L2, BDS L1, and BDS L2, are not affected. Therefore, our approach solves the problems of a frequently changing reference satellite. In addition, because all the carrier phase observations use the same reference ambiguity, a relationship is established between the different systems and frequencies, and the strength of the combined model is thus increased.

In this contribution, an improved Extended Kalman Filter (EKF), named the Total Extended Kalman Filter (TEKF) is proposed for integrated navigation. It can consider the neglected random observed quantities which may appear in a dynamic model. In particular, this paper will consider the case of vision-based navigation. This algorithm is equipped with quadratic constraints and makes use of condition equations. The paper will show that the refined data from different sensors including a Global Positioning System (GPS) receiver, an Inertial Navigation System (INS) and remote sensors can be fused into a Constrained Total Extended Kalman Filter (CTEKF) algorithm. The CTEKF algorithm is applied to a case study in the Guilan province in the north of Iran. The results show the efficiency of the proposed algorithm.

In this paper, a response model of an Unmanned Surface Vehicle (USV) with a pod-like propulsion device is established. To improve the robustness of motion control in heavy sea states, an integrated nonlinear feedback course-keeping controller is proposed. First, to establish a response model of a USV with pod-like propulsion, model parameters are obtained by the method of system identification, then an integrated nonlinear feedback control strategy is proposed. The essence of this method is to make the original error signal pass through a nonlinear function, and then the output of this function is used to replace the original error signal. Simulation results show that under ordinary sea states, nonlinear feedback can save up to 34.5% of energy used compared with standard feedback methods; under heavy sea states, this can rise to 40.8%. A set of field experiments were carried out with a USV with pod-like propulsion. Results show that under heavy sea states, the test USV can maintain the target course well, which proves the correctness of the model and the robustness of the proposed method.

As Satellite Clock Bias (SCB) prediction may be affected by various factors such as periodic items, sampling length, and stochastic items, a fusion-based prediction method is proposed by considering characteristics of SCB and fitted residue. On this basis, an instance algorithm is presented by fusing four typical prediction models. First, we use Empirical Mode Decomposition (EMD) to pre-process and decompose the SCB series into multiple components with various characteristics. Then, we analyse the fitting performance of each model for different components and prediction length, namely short-, mid- and long-term prediction, and select models with the best performance. Next, we analyse fitted residue of the reconstructed SCB, and select the model with the best fitting results. Finally, we fuse the multiple selected models for SCB prediction. The method is tested using Global Positioning System (GPS) precise clock products provided by the International Global Navigation Satellite System Service (IGS). Experimental results show that, compared with single prediction models and existing combination models, the proposed fusion-based prediction method improves accuracy and stability. In particular, the proposed method is more stable and has better performance for mid- and long-term prediction.

In the Venus capture period, it is difficult for celestial autonomous navigation to satisfy the requirement of high precision. To improve autonomous navigation performance, a Direction, Distance and Velocity (DDV) measurements deeply integrated navigation method is proposed. The “deeply” integrated navigation reflects the fact that the direction and velocity measurements suppress the Doppler effects in the pulsar signals. In the pulsar observation period, the direction and velocity measurements are utilised to compensate for Doppler effects in the pulsar signals. By these means, the residual effects can be ignored. When the direction, distance or velocity measurements are obtained, they are fused to improve the navigation performance. Simulation results demonstrate that the DDV measurements deeply integrated navigation filter converges very well, and provides highly accurate position estimation without a high quality requirement on navigation sensors.