The aviation community has very stringent navigation integrity requirements that apply to a variety of manned and Unmanned Aerial Vehicle (UAV) operational tasks. This paper presents the results of the research activities carried out by the Italian Air Force Flight Test Centre (CSV-RSV) in collaboration with the Nottingham Geospatial Institute (NGI) and Cranfield University (CU) in the area of Avionics-Based Integrity Augmentation (ABIA) for mission- and safety-critical Global Navigation Satellite System (GNSS) applications. Based on these activities, suitable models were developed to describe the main causes of GNSS signal outage and degradation in flight, namely: antenna obscuration, multipath, fading due to adverse geometry and Doppler shift. Adopting these models in association with suitable integrity thresholds and guidance algorithms, the ABIA system delivers integrity caution (predictive) and warning (reactive) flags, as well as steering information to the pilot and electronic commands to the aircraft/UAV flight control system. These features allow real-time avoidance of safety-critical flight conditions and fast recovery of the required navigation performance in case of GNSS data losses. This paper presents the key ABIA concepts, architecture and mathematical models. A successive paper will address the ABIA integrity thresholds criteria and detailed results of a TORNADO simulation case-study.

Single-frequency Precise Point Positioning (PPP) using a Global Navigation Satellite System (GNSS) has been attracting increasing interest in recent years due to its low cost and large number of users. Currently, the single-frequency PPP technique is mainly implemented using GPS observations. In order to improve the positioning accuracy and reduce the convergence time, we propose the combined GPS/GLONASS Single-Frequency (GGSF) PPP approach. The approach is based on the GRoup And PHase Ionospheric Correction (GRAPHIC) to remove the ionospheric effect. The performance of the GGSF PPP was tested using both static and kinematic datasets as well as different types of precise satellite orbit and clock correction data, and compared with GPS-only and GLONASS-only PPP solutions. The results show that the GGSF PPP accuracy degrades by a few centimetres using rapid/ultra-rapid products compared with final products. For the static GGSF PPP, the position filter typically converges at 71, 33 and 59 minutes in the East, North and Up directions, respectively. The corresponding positioning accuracies are 0·057, 0·028 and 0·121 m in the East, North and Up directions. Both positioning accuracy and convergence time have been improved by approximately 30% in comparison to the results from GPS-only or GLONASS-only single-frequency PPP. A kinematic GGSF PPP test was conducted and the results illustrate even more significant benefits of increased accuracy and reliability of PPP solutions by integrating GPS and GLONASS signals.

This paper will demonstrate that the Master Pilot Exchange (MPX) is a document of debatable value in pilotage waters. The MPX exists in many formats which are designed to reflect local navigational challenges and port requirements. A generic form exists which can aid the design of local MPX forms. Both the generic and port MPX forms may require the recording of information that has a neutral outcome on the planned act of pilotage. Analysis of significant incidents suggests that investigation recommendations are not consistently reflected in MPX forms and there is a gap between what should be recorded and reality.

Evidence for the existence of risk compensation behaviour in the operation of vessels is shown in the paper The Risk Homeostasis Theory (Baniela and Ríos, 2010). In that analysis, it is concluded that the people engaged in the commercial affairs of ships tend to exchange the level of safety standard of vessels for a more profitable and riskier activity, which makes the rate of shipping accidents fluctuate within certain limits. Since the different levels of power and motivation of those involved in the risk-taking process were not considered in that research, it is the aim of this paper to analyse, on the one hand, how the pressure of the shipping market influences the risk behaviour of shipping business decision-makers and to show, on the other hand, how this influence makes them alter their target level of risk and introduce risks related to low operating cost strategies on vessels. This behavioural adaptation to the shipping market demand has led the human element to be regarded as a factor of risk in the activity of commercial vessels. In this context, the increasing incidence of human errors has arisen as a consequence of practices and manning policies established by the managers of shipping companies.

This paper presents a new Electronic Travel Aid (ETA) ‘Acoustic Prototype’ which is especially suited to facilitate the navigation of visually impaired users. The device consists of a set of 3-Dimensional Complementary Metal Oxide Semiconductor (3-D CMOS) image sensors based on the three-dimensional integration and Complementary Metal-Oxide Semiconductor (CMOS) processing techniques implemented into a pair of glasses, stereo headphones as well as a Field-Programmable Gate Array (FPGA) used as processing unit. The device is intended to be used as a complementary device to navigation through both open known and unknown environments. The FPGA and the 3D-CMOS image sensor electronics control object detection. Distance measurement is achieved by using chip-integrated technology based on the Multiple Short Time Integration method. The processed information of the object distance is presented to the user via acoustic sounds through stereophonic headphones. The user interprets the information as an acoustic image of the surrounding environment. The Acoustic Prototype transforms the surface of the objects of the real environment into acoustical sounds. The method used is similar to a bat's acoustic orientation. Having good hearing ability, with few weeks training the users are able to perceive not only the presence of an object but also the object form (that is, if the object is round, if it has corners, if it is a car or a box, if it is a cardboard object or if it is an iron or cement object, a tree, a person, a static or moving object). The information is continuously delivered to the user in a few nanoseconds until the device is shut down, helping the end user to perceive the information in real time.

This study describes the estimation of spherical wave parameters that appears in Synthetic Aperture Radar (SAR) images acquired over the coast of Chukk, Micronesia. The main causes for the interaction of SAR signals with ocean waves can be retrieved through the Bragg scattering mechanism. Dominant wavelengths were retrieved by means of Fast Fourier Transform (FFT) analysis in terms of peak frequency responses. Sea surface slopes were then obtained from the dispersion relation with consideration of different water wave conditions for each subset area, and wave heights were estimated with the use of dominant wavelengths and sea surface slopes. The work presented in this paper may be useful to retrieve the various wave parameters over different regions. The method used is a novel technique to correlate the relationship between SAR image parameters and dispersion relation.

Integer ambiguity validation is pivotal in precise positioning with Global Navigation Satellite Systems (GNSS). Recent research has shown traditionally used ambiguity validation methods can be classified as members of the Integer Aperture (IA) estimators, and by the virtue of the IA estimation, a user controllable IA fail-rate is preferred. However, an appropriately chosen fail-rate is essential for ambiguity validation. In this paper, the upper bound and the lower bound for the IA fail-rate, which are extremely useful even at the designing stage of a GNSS positioning system, have been analysed, and numerical results imply that a meaningful IA fail-rate should be within this range.

In kinematic Global Navigation Satellite Systems (GNSS) navigation, the Kalman Filter (KF) solution relies, to a great extent, on the quality of the dynamic model that describes the moving object's motion behaviour. However, it is rather difficult to establish a precise dynamic model that only connects the previous state and the current state, since these high-order quantities are usually unavailable in GNSS navigation receivers. To overcome such limitations, the Window-Recursive Approach (WRA) that employs the previous multiple states to predict the current one was developed in Zhou et al., (2010). Its essence is to adaptively fit the moving object's motion behaviour using the multiple historical states in a short time span. Up to now, the WRA method has been performed only using GNSS pseudorange measurements. However, in GNSS navigation fields, the strength of pseudorange observation model is usually weak due to various reasons, e.g., multi-path delay, outliers, insufficient visible satellites. As an important complementary measurement, Doppler can be used to aid Position and Velocity (PV) estimation. In this contribution, implementation of WRA will be developed using the pseudorange and Doppler measurements. Its corresponding state transition matrix is constructed based on the Newton's Forward Difference Extrapolation (NFDE) and Definite Integral (DI) methods for the efficient computation. The new implementation of WRA is evaluated using the real kinematic vehicular GNSS data with two sampling rates. The results show that:

1. (i) aided by GNSS Doppler measurement, the new implementation of WRA significantly improves the accuracy compared with the pseudorange-only WRA.

2. (ii) In high sampling rate, the WRA works best in the case of 2 epochs in time window, while in the low sampling rate, it obtains better solutions if more epochs involved in time window.

3. (iii) Compared with KF with constant velocity dynamic model, the WRA demonstrates better in the self-adaptation and validity.

4. (iv) As a benefit of WRA itself, the NFDE/DI-based state transition matrix for WRA can be previously computed offline without increasing the computation burdens.

In some Global Positioning System (GPS) signal propagation environments, especially in the ionosphere and urban areas with heavy multipath, GPS signal encounters not only additive noise but also multiplicative noise. In this paper we compare and contrast the conventional GPS signal acquisition method which focuses on handling GPS signal acquisition with additive noise, with the enhanced GPS signal processing under multiplicative noise by proposing an extension of the GPS detection mechanism, to include the GPS detection model that explains detection of the GPS signal under additive and multiplicative noise. For this purpose, a novel GPS signal detection scheme based on high order cyclostationarity is proposed. The principle is introduced, the GPS signal detection structure is described, the ambiguity of initial PseudoRandom Noise (PRN) code phase and Doppler shift of GPS signal is analysed. From the simulation results, the received GPS signal at low power level, which is degraded by additive and multiplicative noise, can be detected under the condition that the received block of GPS data length is at least 1·6 ms and sampling frequency is at least 5 MHz.

This note commences with the adoption by the newly invented steam ships, of the sailing ship's custom of referring helm orders to the direction in which the tiller was to be shifted. It records something of the early resiling of the non-English speaking nations from this counter intuitive custom and draws attention to the confusion which the lack of an international approach created, especially for a ship under pilotage. The note concludes with the international uniformity achieved for helm orders by Convention in 1929.

The author uses a personal account of a short-handed small boat voyage, from the Orkney Islands into the Arctic Circle, to determine whether nature can help a navigator estimate their distance from land. As part of this exercise the author reinforces his argument (Gooley, 2010) that natural navigation clues add not only to safety and general awareness, but offer the navigator a richer experience than relying solely on electronic navigation. The main aim of this expedition and paper is to establish whether some of the traditional methods of navigation, used by Pacific Island and Viking navigators, can be of any value to the modern navigator. Recorded sightings of birds, cetaceans, fish, jellyfish, water behaviour and colour are used to support the author's findings. The paper also contains the author's reflections on the experience of undertaking a voyage of this kind and leads to one surprising conclusion.

In this paper, a novel analytical framework for Dynamic Quaternion Ship Domain (DQSD) models has been initially proposed via the Quaternion Ship Domain (QSD) model structure. Unlike previous ship domains, the proposed DQSD model is able to capture essential subjectivity and objectivity of ship domains. To be specific, the significant characteristics are as follows:

1. (1) The proposed DQSD model is integrated by three independent submodels of ship, human and circumstance, which are determined by ship manoeuvrability, navigator's states, and navigation circumstance, respectively.

2. (2) The ship manoeuvrability derived from the MMG-type ship motion model is employed to establish the ship submodel which identifies the DQSD scale.

3. (3) A novel navigator reliability model is proposed to realize the human submodel which defines the ship domain shape with navigator ability, physical and mental states being input variables.

4. (4) In addition, visibility, wind force, wave and traffic congestion are incorporated into the circumstance submodel which is employed to zoom in or out of the DQSD-type ship domain.

Finally, the well-known Esso Osaka tanker model is used to conduct simulation studies on various typical stationary and dynamic situations, and comparative investigations with each other have been comprehensively analysed. Simulation results demonstrate that the DQSD model can capture critical dynamics of ship domains and undoubtedly be effective and superior to previous ship domains in terms of performance and accuracy.

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.

For mobile 3-D radar installed on a gyro-stabilized platform, its measurements are usually contaminated by the systematic biases which contain radar offset biases (i.e., range, azimuth and elevation biases) and attitude biases (i.e., yaw, pitch and roll biases) of the platform because of the errors in the Inertial Measurement Units (IMU). Systematic biases can NOT be removed by a single radar itself; however, fortunately, they can be estimated by using two different radar measurements of the same target. The process of estimating systematic biases and then compensating radar measurements is called error registration. In this paper, the registration models are established first, then, the equivalent radar measurement error expressions caused by the attitude biases are derived and the dependencies among attitude biases and offset biases are analysed by using the observable matrix criterion. Based on the analyses above, an Optimized Bias Estimation Model (OBEM) is proposed for registration. OBEM uses the subtraction of azimuth and yaw bias as one variable and omits roll and pitch biases in the state vector, which decreases the dimension of the state vector from fourteen of the All Augmented Model (AAM), (which uses all the systematic biases of both radars as state vector) to eight and has about 80% reduction in calculation costs. Also, OBEM can decrease the coupling influences of roll and pitch biases and improve the estimation performance of radar elevation bias. Monte Carlo experiments were made. Numerical results showed that the bias estimation accuracies and the rectified radar raw measurement accuracies can be improved.

The Position and Orientation System (POS) is a special Strapdown Inertial Navigation System (SINS)/Global Positioning System (GPS) integrated system, widely employed in airborne remote sensing. In-Flight Alignment (IFA) is an effective way to improve the accuracy and speed of initial alignment for an airborne POS. IFA is normally accomplished with references from the position and velocity of GPS for SINS, so that unstable GPS measurements will result in poor alignment accuracy. To improve alignment accuracy under unstable GPS conditions, an adaptive filtering algorithm of the Second-order Divided Difference filter (DD2) based on adaptive innovation estimation is proposed, which introduces calculated innovation covariance directly into computation of the filter gain matrix. Then, the adaptive DD2 algorithm is used for the IFA of the POS with a large initial heading error. To validate the proposed algorithm, simulations are undertaken, followed by IFA experiments for the prototype of the airborne POS (TX-F30) under a turning manoeuvre in a car-mounted experiment, and under an “8” manoeuvre in-flight. The simulations and experimental results show that the proposed algorithm can reach better alignment accuracy under unknown statistical characteristic of GPS measurement noises.

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.