Autonomous vehicles with an ability to trace chemical plumes can be instrumental in tasks such as detection of unexploded ordnance, search for undersea wreckage and environmental monitoring. As a consequence, use of autonomous vehicles to perform chemical plume tracing has received an increasing interest from the research community in recent years. Owing to the diversity of applications and ambient fluid environment of the plumes, there are numerous plume tracing strategies and approaches. This paper reviews two main approaches and a number of strategies that have been successfully implemented to track air or water borne plumes in order to locate odour sources using autonomous vehicles. The first strategy considered is the biomimetic approach that offers excellent models for the development of robotic systems. Strategies inspired by lobsters and bacterium are the main focus in this study. The second scheme considers parallelization of the search procedure by employing a multi-robot approach. This approach has the advantage of utilising a group of smaller and simpler communicating robots which are capable of performing a collaborative search of the plume.

Integrated electronic marine systems have been put forward as one way of reducing information overload for officers of the watch and other personnel who work on ships' bridges or in fishing wheelhouses. It may be that such systems will improve safety records which, in the case of fishing, are amongst the worst in the world. This article builds on previous work about issues for the systems designer by using a small study of fishing skippers to ascertain their perceptions of using integrated electronic systems in the wheelhouse. Semi-structured interviews were used with 11 skippers from one port who were all familiar with integrated electronic marine systems but did not use them on their vessels. The main reasons for this were a perception of unreliability of both the hardware and the software, together with concerns about data integrity and user control.

This paper describes the air navigation techniques and drills used by Lancasters of the Pathfinder Force of Royal Air Force Bomber Command in early 1945. A brief description is given of the equipment and fixing aids available to the navigator and the environment in which he worked. The paper is based on the author's personal experience and with reference to the log and chart of an operation in which he took part. A running commentary on the navigational aspects of the operation is also given.

The dynamic precise orbit determination of a Low Earth Orbit satellite using triple differenced GPS phases is presented in this study. The atmospheric drag parameters are estimated to compensate the incomplete atmosphere model for better precision of the orbit solution. In addition, the empirical force parameters, especially once- and twice-per-revolution components, along with the new IERS Conventions and models to compute the perturbing forces are introduced to absorb the remaining unmodelled forces. The optimal arc length for the parameterization and the data processing strategy are also tested and analyzed for the best orbit solutions. The triple differencing technique enables fast and efficient orbit estimation, because no ambiguity resolution and cycle slip detection are required. With the triple differenced ion-free GPS phase observables, the orbit and the velocity solutions for 24 hours of CHAMP are calculated; they compare with the published Rapid Science Orbit with the accuracy of 8 cm and 0·12 mm/s in 3D RMS for the orbit and the velocity, respectively, and are statistically consistent with the RSO when it is not better than 4 cm in terms of an absolute accuracy. The approach presented here provides an efficient and simple, but robust, alternative approach, while the solution's accuracy is still comparable to the double-difference results.

Recent navigation systems integrating GPS with Micro-Electro-Mechanical Systems (MEMS) Inertial Measuring Units (IMUs) have shown promising results for several applications based on low-cost devices such as vehicular and personal navigation. However, as a trend in the navigation market, some applications require further reductions in size and cost. To meet such requirements, a MEMS full IMU configuration (three gyros and three accelerometers) may be simplified. In this context, different partial IMU configurations such as one gyro plus three accelerometers or one gyro plus two accelerometers could be investigated. The main challenge in this case is to develop a specific navigation algorithm for each configuration since this is a time-consuming and costly task. In this paper, a universal approach for processing any MEMS sensor configuration for land vehicular navigation is introduced. The proposed method is based on the assumption that the omitted sensors provide relatively less navigation information and hence, their output can be replaced by pseudo constant signals plus noise. Using standard IMU/GPS navigation algorithms, signals from existing sensors and pseudo signals for the omitted sensors are processed as a full IMU. The proposed approach is tested using land-vehicle MEMS/GPS data and implemented with different sensor configurations. Compared to the full IMU case, the results indicate the differences are within the expected levels and that the accuracy obtained meets the requirements of several land-vehicle applications.

Traditionally, GNSS receiver autonomous integrity monitoring (RAIM) has been based upon single epoch solutions. RAIM can be improved considerably when available dynamic information is fused together with the GNSS range measurements in a Kalman filter. However, while the Kalman filtering technique is widely accepted to provide optimal estimates for the navigation parameters of a dynamic platform, assuming the state and observation models are correct, it is still susceptible to unmodelled errors. Furthermore, significant deviations from the assumed models for dynamic systems may also occur. It is therefore necessary that the state estimation procedure is complemented with effective and reliable integrity measures capable of identifying both measurement and modelling errors. Within this paper, fundamental equations required for the effective detection and identification of outliers in a kinematic GNSS positioning and navigation system are described together with the reliability and separability measures. These quality measures are implemented using a Kalman filtering procedure formulated with Gauss-Markov models where the state estimates are derived from least squares principles. Detailed simulations and analyses have been performed to assess the impact of the dynamic information on GNSS RAIM with respect to outlier detection and identification, reliability and separability. The ability of the RAIM algorithms to detect and identify dynamic modelling errors is also investigated.

For certain applications such as E911/E999/E112, GPS chipset receiver manufacturers will possibly have to test their products to ensure these fulfill mandated performance specifications for a variety of outdoor and indoor conditions. As opposed to testing in the field, laboratory testing is totally repeatable and controllable, and may be less costly. Hardware GPS signal simulators are now able to simulate signals under a variety of attenuation and multipath conditions. In indoor environments, GPS signals suffer not only from severe attenuation and multipath but from complex variations thereof. A method to simulate indoor GPS signals such that the stochastic characteristics of the simulated signals match those of actual GPS signals received in situ by a high sensitivity GPS receiver in various indoor environments is presented. Probability density functions and correlation coefficients are used to demonstrate the similarity between field and simulated data in terms of signal power fading and estimated pseudorange error. The results clearly demonstrate the feasibility of the approach.

Multipath is still one of the major error sources that degrades the accuracy of GPS positioning. The amount of multipath is highly dependent on the antenna's environment, which makes it difficult to isolate. Usually there is at least one in-view satellite which is more susceptible to multipath, particularly the one with the lowest elevation angle. To increase the positioning the best satellites must be selected (i.e. by least square or multipath mitigation) for computing a position. In this paper we propose an algorithm which picks up the best satellites (when there are more than four satellites in view) based on wavelet analysis for calculating a position. In this experiment, code and carrier measurements were collected in 15-minute segments by exploiting a single frequency (L1), stationary, navigation-grade receiver in a high-multipath environment. The magnitudes of these pseudoranges were often inflated by multipath error. We then post-processed the received data by applying wavelet filtering to the residuals (code minus carrier) to approximate the multipath values, and compute the receiver's position based on the selected satellites. Satellites were selected based on the residual values. To compare the results with the raw measurements, statistical elements were computed. The results showed significant improvement in variance of the estimated positions and, most importantly, a normalization of the data scatter-distribution was observed.

This paper focuses on modelling and predicting differential GPS corrections transmitted by marine radio-beacon systems using artificial neural networks. Various neural network structures with various training algorithms were examined, including Linear, Radial Biases, and Feedforward. Matlab Neural Network toolbox is used for this purpose. Data sets used in building the model are the transmitted pseudorange corrections and broadcast navigation message. Model design is passed through several stages, namely data collection, preprocessing, model building, and finally model validation. It is found that feedforward neural network with automated regularization is the most suitable for our data. In training the neural network, different approaches are used to take advantage of the pseudorange corrections history while taking into account the required time for prediction and storage limitations. Three data structures are considered in training the neural network, namely all round, compound, and average. Of the various data structures examined, it is found that the average data structure is the most suitable. It is shown that the developed model is capable of predicting the differential correction with an accuracy level comparable to that of beacon-transmitted real-time DGPS correction.

This article is partially based on the Doctoral thesis (Reference 1) entitled (in English) Working aboard and job-related accidents: Health and safety conditions on merchant vessel. Divided into four sections, the paper includes: issues relating to legislation, an analysis of accidents, the research that has been done about accidents and risk factors for falling on board. The main causes of accidents are examined. Moreover, conclusions are drawn by analysing work-related accidents in the Spanish maritime transport sector through a study covering the period between 1999 and 2003. The text was updated in 2004, with the latest official data, figures which may be equally applicable to the maritime sector throughout the European Union.

This paper briefly outlines the production of electronic nautical charts (ENC) as a digital nautical chart, produced by the Croatian National Hydrographic Office (HO) to International Hydrographic Organization (IHO) specifications S-57 Edition 3.1. The production of ENCs is based on the theory of multiscale data management (usage bands). Multiple representations of ENC data are controlled by scale minimum (SCAMIN) attributes. A solution to the problem of multiscale data management as a part of ENC data production for archipelagic sea areas, using the East Adriatic Coast as an example is presented. This solution is based on a long-standing experience in the production of paper charts and recent ENC production for the eastern coast of the Adriatic Sea, which is believed to be the second largest archipelagic area in the Mediterranean. Finally, a new usage band scale range, compilation scale for all navigational purposes and method of using SCAMIN attributes for archipelagic seas are proposed.

GPS is the most widely used global navigation satellite system. By design, there is no provision for real time integrity information within the Standard Positioning Service (SPS). However, in safety critical sectors like aviation, stringent integrity performance requirements must be met. This can be achieved externally or at the receiver level through receiver autonomous integrity monitoring (RAIM). The latter is a cost effective method that relies on data consistency, and therefore requires redundant measurements. An external aid to provide this redundancy can be in the form of an Inertial Navigation System (INS). This should enable continued performance even during RAIM holes (when no redundant satellite measurements are available). However, due to the inclusion of an additional system and the coupling mechanism, integrity issues become more challenging. To develop an effective integrity monitoring capability, a good understanding of the potential failure modes of the integrated system is vital. In this paper potential failure modes of integrated GPS/INS systems are identified. This is followed by the specification of corresponding models that would be required to investigate the capability of existing integrity algorithms and to develop enhancements or new algorithms.