From the Surface Velocity Program (SVP) drifter current data, a detailed and complete track of strong ocean currents in the north-western Pacific is provided using the bin average method. The focus of this study is on the Kuroshio, the strong western boundary current of the North Pacific flowing northward along the east coast of Taiwan and then turning eastward off southern Japan. With its average flow speed of about 2 knots, the Kuroshio can significantly increase the ship's speed for a “super-slow-steaming” container ship travelling at speeds of 12 knots between the ports of Southeast Asia and Japan. By properly utilizing knowledge of strong ocean currents to follow the Kuroshio on the northbound runs and avoid it on the return trip, considerable fuel can be saved and the transit time can be reduced. In the future, the detailed Kuroshio saving-energy route could be built into electronic chart systems for all navigators and shipping routers.

Avoidance of collisions at sea is crucial to navigational safety. In this paper, we use a distributed algorithm to communicate the entire collision avoidance trajectory information for each ship. In each communication, we suggest a new improvement function considering safety and efficiency to identify the avoidance ship in each cycle. Considering the nonlinear collision avoidance trajectory of ships, a new method for calculating the degree of danger using a velocity obstacle algorithm is proposed. Therefore, in each communication, each ship considers the avoidance behaviours of other ships in planning its avoidance trajectory. Additionally, we combine bi-criterion evolution (BCE) and the ant lion optimiser to plan the entire collision avoidance path. Three scenarios are designed to demonstrate the performance of this method. The results show that the proposed method can find a suitable collision-free solution for all ships.

This paper reports on the potential application of interval Kalman filtering techniques in the design of a navigation system for an uninhabited surface vehicle named Springer. The interval Kalman filter (IKF) is investigated for this task since it has had limited exposure for such usage. A state-space model of the Springer steering dynamics is used to provide a framework for the application of the Kalman filter (KF) and IKF algorithms for estimating the heading angle of the vessel under erroneous modelling assumptions. Simulations reveal several characteristics of the IKF, which are then discussed, and a review of the work undertaken to date presented and explained in the light of these characteristics, with suggestions on potential future improvements.

Today's mobile technology features several sensors that when integrated can provide ubiquitous navigation assistance to pedestrians including wheelchair users. Common sensors found in most smartphones are Global Positioning System (GPS), accelerometer, and compass. In this paper, a user's movement pattern recognition algorithm to improve map matching efficiency and accuracy in pedestrian/wheelchair navigation systems/services is discussed. The algorithm integrates GPS positions, orientation data from compass, and movement states recognized from accelerometer data in a client/server architecture. The algorithm is tested in an Android mobile phone, and the results show that the proposed map matching algorithm is efficient and provides good accuracy.

A Relative Positions-Constrained pattern Matching (RPCM) method for underwater gravity-aided inertial navigation is presented in this paper. In this method the gravity patterns are constructed based on the relative positions of points in a trajectory, which are calculated by Inertial Navigation System (INS) indications. In these patterns the accumulated errors of INS indicated positions are cancelled and removed. Thus the new constructed gravity patterns are more accurate and reliable while the process of matching can be constrained, and the probability of mismatching also can be reduced. Two gravity anomaly maps in the South China Sea were chosen to construct a simulation test. Simulation results show that with this RPCM method, the shape of the trajectory in gravity-aided navigation is not as restricted as that in traditional Terrain Contour Matching (TERCOM) algorithms. Moreover, the performance included matching success rates and position accuracies are highly improved in the RPCM method, especially for the trajectories that are not in straight lines. Thus the proposed method is effective and suitable for practical navigation.

In the work package “Integrated Positioning” of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environments) we are dealing with the navigation and guidance of visitors to our University. The start points are the public transport stops in the surroundings of the Vienna University of Technology and the system users should be guided to certain office rooms or persons. For the user's position determination different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors, such as a digital compass and gyro for heading determination, accelerometers for the determination of the distance travelled, a barometric pressure sensor for altitude determination and, for indoor areas, location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter. An optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the senors in the stochastic filter model, the sensor characteristics and performance were investigated in several tests. The tests were performed in different environments either with free satellite visibility, in urban canyons or inside buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach are presented in the paper.

Integrated navigation using multiple Global Navigation Satellite Systems (GNSS) is beneficial to increase the number of observable satellites, alleviate the effects of systematic errors and improve the accuracy of positioning, navigation and timing (PNT). When multiple constellations and multiple frequency measurements are employed, the functional and stochastic models as well as the estimation principle for PNT may be different. Therefore, the commonly used definition of “dilution of precision (DOP)” based on the least squares (LS) estimation and unified functional and stochastic models will be not applicable anymore. In this paper, three types of generalised DOPs are defined. The first type of generalised DOP is based on the error influence function (IF) of pseudo-ranges that reflects the geometry strength of the measurements, error magnitude and the estimation risk criteria. When the least squares estimation is used, the first type of generalised DOP is identical to the one commonly used. In order to define the first type of generalised DOP, an IF of signal–in-space (SIS) errors on the parameter estimates of PNT is derived. The second type of generalised DOP is defined based on the functional model with additional systematic parameters induced by the compatibility and interoperability problems among different GNSS systems. The third type of generalised DOP is defined based on Bayesian estimation in which the a priori information of the model parameters is taken into account. This is suitable for evaluating the precision of kinematic positioning or navigation. Different types of generalised DOPs are suitable for different PNT scenarios and an example for the calculation of these DOPs for multi-GNSS systems including GPS, GLONASS, Compass and Galileo is given. New observation equations of Compass and GLONASS that may contain additional parameters for interoperability are specifically investigated. It shows that if the interoperability of multi-GNSS is not fulfilled, the increased number of satellites will not significantly reduce the generalised DOP value. Furthermore, the outlying measurements will not change the original DOP, but will change the first type of generalised DOP which includes a robust error IF. A priori information of the model parameters will also reduce the DOP.

The E5/L5 frequency band for the new Global Navigation Satellite System (GNSS) signals is crowded with aeronautical pulsed emitters. This results in severe degradation of the performance of GNSS receivers. This paper describes a novel technique for estimating and suppressing time-varying pulsed interference signals such as the Distance Measuring Equipment (DME)/Tactical Air Navigation (TACAN) signals generated by these pulsed emitters. The proposed technique involves the integration of the time-based pulse blanker and the wavelet-based interference mitigation technique. Aviation is the key application considered although many other applications such as transport management and navigation, environmental monitoring, and telecommunications would benefit. A performance assessment of the new technique is carried out by determining the degradation of the carrier-to-noise ratio (CNR) at the output of the correlator. The performance of the new technique is compared with the traditional time domain pulse blanking approach. The results show that the proposed technique performs better than both the time domain pulse blanker and the wavelet-based interference mitigation algorithm. Hence, the integrated pulse mitigation approach can be employed to provide an enhanced degree of interference detection and suppression.

There is increasing demand for navigation capability for space vehicles. The idea to extend the application of Global Navigation Satellite Systems (GNSS) from terrestrial to space applications by the use of main beam and side lobe signals has been shown to be feasible. In order to understand the performance and the potential space applications GNSS can support, this paper characterises the Space Service Volume (SSV) in terms of the four parameters of minimum received power, satellite visibility, pseudorange accuracy and Geometric Dilution of Precision (GDOP). This new definition enables the position errors to be estimated. An analytical methodology is proposed to characterise minimum received power for the worst location. Satellite visibility and GDOP are assessed based on grid points at different height layers (to capture the relationship between height and visibility) for single and multiple GNSS constellations, the former represented by BeiDou III (BDS III) and the latter, BDS III in various combinations with GPS, GLONASS and GALILEO. Additional simulation shows that GNSS can potentially support lunar exploration spacecraft at the Earth phasing orbit. This initial assessment of SSV shows the potential of GNSS for space vehicle navigation.

In-motion alignment plays an important role in improving the manoeuvring capability of a vehicle, and allows the initialisation of a Strapdown Inertial Navigation System (SINS) while moving. Odometer (OD) aided in-motion alignment is widely adopted owing to its fully self-contained characteristic. This paper proposes a complete in-motion alignment algorithm for a vehicle-carried SINS based on odometer aiding, in which an in-motion coarse alignment method using the integration form of the velocity update equation in the body frame to give a rough initial angle is introduced and a new measurement equation in the body frame with a Kalman filter (KF) for the in-motion fine alignment is established. The advantages of the proposed method are verified by simulation and measured data.

A redundant Inertial Measurement Unit (IMU) is an inertial sensing device composed of more than three accelerometers and three gyroscopes. This paper analyses the performance of redundant IMUs and their various sensor configurations. The inertial instruments can achieve high reliability for long periods of time only by redundancy. By suitable geometric configurations it is possible to extract the maximum amount of reliability and accuracy from a given number of redundant single-degree-of-freedom gyros or accelerometers. This paper gives a general derivation of the optimum matrix which can be applied to the outputs of any combination of three or more sensors to obtain three orthogonal vector components based on their geometric configuration and error characteristics. Certain combinations of four or more instruments are able to detect an instrument malfunction, and combinations of five have the additional capability of isolating that malfunction to a particular sensor. Finally, this paper offers a major improvement in reliability, although the improvement in accuracy is minor.

Most Differential Global Positioning System (DGPS) correction formats are based on range information, and thus typical DGPS systems can be implemented only on correction message-readable or raw observable-providing devices. There is no other way to improve an already-calculated position than a ‘block shift technique’, which has a very limited applicability. This paper suggests an algorithm to project measurement correction directly to position domain data without requiring raw pseudorange data. By post-processing methodology, we evaluated the performance of our new algorithm compared to conventional DGPS, which requires raw pseudorange data; the observed difference between them was only 0·1 mm . The proposed correction projection algorithm can be used with commercial off-the-shelf receivers that provide National Marine Electronics Association (NMEA) format data. Our testing with a U-blox LEA-5H receiver resulted in a drastic reduction of horizontal Root Mean Square (RMS) error from 4·75 m to 1·09 m.

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.

Real-time and accurate fault detection and isolation is very important to ensure the reliability and precision of integrated inertial navigation and global navigation satellite systems. In this paper, the detection performance of a residual chi-square method is analysed, and on this basis an improved method of fault detection is proposed. The local test based on a standardised residual is introduced to detect and identify faulty measurements directly. Differing from the traditional method, two appropriate thresholds are selected to calculate the weight factor of each measurement, and the gain matrix is adjusted adaptively to reduce the influence of the undetected faulty measurement. The sliding window test, which uses past measurements, is also added to further improve the fault detection performance for small faults when the local test based on current measurements cannot judge whether a fault has occurred or not. Several simulations are conducted to evaluate the proposed method. The results show that the improved method has better fault detection performance than the traditional detection method, especially for small faults, and can improve the reliability and precision of the navigation system effectively.

The determination of the correct integer number of carrier cycles (integer ambiguity) is the key to high accuracy positioning with carrier phase measurements from Global Navigation Satellite Systems (GNSS). There are a number of current methods for resolving ambiguities including the Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) method, which is a combination of least-squares and a transformation to reduce the search space. The current techniques to determine the level of confidence (integrity) of the resolved ambiguities (i.e. ambiguity validation), usually involve the construction of test statistics, characterisation of their distribution and definition of thresholds. Example tests applied include ratio, F-distribution, t-distribution and Chi-square distribution. However, the assumptions that underpin these tests have weaknesses. These include the application of a fixed threshold for all scenarios, and therefore, not always able to provide an acceptable integrity level in the computed ambiguities. A relatively recent technique referred to as Integer Aperture (IA) based on the ratio test with a large number of simulated samples of float ambiguities requires significant computational resources. This precludes the application of IA in real time.

This paper proposes and demonstrates the power of an integrity monitoring technique that is applied at the ambiguity resolution and positioning stages. The technique has the important benefit of facilitating early detection of any potential threat to the position solution, originating in the ambiguity space, while at the same time giving overall protection in the position domain based on the required navigation performance. The proposed method uses the conventional test statistic for ratio testing together with a doubly non-central F distribution to compute the level of confidence (integrity) of the ambiguities. Specifically, this is determined as a function of geometry and the ambiguity residuals from least squares based ambiguity resolution algorithms including LAMBDA. A numerical method is implemented to compute the level of confidence in real time.

The results for Precise Point Positioning (PPP) with simulated and real data demonstrate the power and efficiency of the proposed method in monitoring both the integrity of the ambiguity computation and position solution processes. Furthermore, due to the fact that the method only requires information from least squares based ambiguity resolution algorithms, it is easily transferable to conventional Real Time Kinematic (RTK) positioning.

Aircraft accidents are extremely rare in the aviation sector. However, their consequences can be very dramatic. One of the most important problems is runway excursions, when an aircraft exceeds the end (overrun) or the side (veer-off) of the runway. After performing exploratory analysis and hypothesis tests, a Bayesian-network-based approach was considered to provide information from risk scenarios involving landing procedures. The method was applied to a real database containing key variables related to landing operations on three runways. The objective was to analyse the effects over runway overrun excursions of failing to fulfil expert recommendations upon landing. For this purpose, the most influential variables were analysed statistically, and several scenarios were built, leading to a runway ranking based on the risk assessed.

This paper presents a new algorithm to accelerate Precise Point Positioning (PPP) convergence. The main idea is to consider the station tropospheric zenith total delay, which is obtained by a global zenith troposphere delay estimate model, as virtual observation and combine it with phase and pseudo-range observations to formulate observation equations. Without relying on any other external enhancement information, it only requires four satellites to quickly complete the positioning with centimetre-level accuracy. Compared with the conventional method, the new one brings about 15% improvement in convergence time.

Code Differential Global Positioning System (DGPS) is widely used in satellite navigation and positioning because of its simple algorithm and preferable precision. Multi-Global Navigation Satellite System (GNSS) is expected to enhance the accuracy, reliability and availability of Differential GNSS (DGNSS) positioning. Traditional DGNSS models should set separate clock parameters due to the clock differences between the different systems. Awareness of the Inter-System Bias (ISB) could help to maximise the redundancy of the positioning model, thus improving the performance of multi-GNSS positioning. This paper aims to examine the inter-system bias of GPS/GLONASS/BeiDou (BDS)/Galileo and their benefits in DGNSS positioning. Results show that Differential ISB (DISB) characteristics vary with different receiver types and systems. The size of DISB could reach metre-level and the precision of estimated DISBs can reach approximately several centimetres within tens of epochs. Therefore, a new real-time DGNSS model that accounts for ISB is proposed. After differential ISBs are initialised, positioning with four satellites from arbitrarily the same or different systems can be realised. Moreover, compared with the traditional DGNSS model, the precision of the positioning results with the new model are obviously improved, especially in harsh environments.

Over recent years, a number of marine autopilots designed using linear techniques have underperformed owing to their inability to cope with nonlinear vessel dynamics. To this end, a new design framework for the development of nonlinear autopilots is proposed. Local Control Networks (LCNs) can be used in the design of nonlinear control systems. In this paper, a LCN approach is taken in the design of a nonlinear autopilot for controlling the nonlinear yaw dynamics of an unmanned surface vehicle known as Springer. It is considered the approach is the first of its kind to be used in marine control systems design. Simulation results are presented and the performance of the nonlinear autopilot is compared with that of an existing Springer Linear Quadratic Gaussian (LQG) autopilot using standard system performance criteria. From the results it can be concluded the LCN autopilot out-performed that based on LQG techniques in terms of the selected criteria. Also it provided more energy saving control strategies and would thereby increase operational duration times for the vehicle during real-time missions.

Many researchers have studied vessel systems to enhance navigation safety at sea, or analysed the statistics of marine casualties of different flagged vessels as well as the fatalities and injuries in ferry accidents. However, little research has been devoted to port safety and especially navigation safety within Taiwanese territorial waters where over a 10-year period there have been 3428 marine accidents with 548 deaths and 524 vessels sunk. In this paper, we use the Grey Relational Analysis (GRA) to analyse the marine accident records of each of Taiwan's commercial ports from 1992–2003. Then, after interviewing the port authority managers and marine specialists, we discover the concerns felt by these professionals about Taiwanese commercial ports. We provide suggestions to strengthen port navigation safety.