In urban areas, Global Positioning System (GPS) accuracy deteriorates due to signal degradation and multipath effects. To provide accurate and robust navigation in such GPS-denied environments, multi-sensor integrated navigation systems are developed. This paper introduces a 3D multi-sensor navigation system that integrates inertial sensors, odometry and GPS for land-vehicle navigation. A new error model is developed and an efficient loosely coupled closed-loop Kalman Filter (Extended KF or EKF) integration scheme is proposed. In this EKF-based integration scheme, the inertial/odometry navigation output is continuously corrected by EKF-estimated errors, which keeps the errors within acceptable linearization ranges which improves the prediction accuracy of the linearized dynamic error model. Consequently, the overall performance of the integrated system is improved. Real road experiments and comparison with earlier works have demonstrated a more reliable performance during GPS signal degradation and accurate estimation of inertial sensor errors (biases) have led to a more sustainable performance reliability during long GPS complete outages.

For mobile radars installed on a gyro-stabilised platform (GSP) that can steadily follow an East-North-Up (ENU) frame, attitude biases (ABs) of the platform and offset biases (OBs) of the radar are linear dependent variables. Therefore ABs and OBs are unobservable in the linearized registration equations; however, when combining them as new variables, the system becomes observable, and this model has been called the unified registration model (URM). Unlike GSP mobile radars, un-stabilised GSP (or UGSP) mobile radars are installed on the platform directly and rotate with the platform simultaneously. For UGSP, it is testified that both types of biases are independent and observable because the time-varying attitude angles (AAs)1 of the platform are included in the registration equations, which destroy the dependencies of both kinds of biases and lead us to propose a completely different linearized registration model– the All Augmented Model (AAM). AAM employs all OBs and ABs in the state vector and a Kalman filter (KF) to produce their estimates. Numerical simulation results show that the estimated performance of AAM is close to the Cramér-Rao lower bound (CRLB) and that the Root Mean Square Errors (RMSEs) of the rectified measurements by using AAM are more than 500 m smaller than by URM in all directions.

The complementary advantages of high-rate Global Positioning System (GPS) and accelerometer observations for measuring seismic ground motion have been recognised in previous research. Here we propose an approach of tight integration of GPS and accelerometer measurements. The baseline shifts of the accelerometer are introduced as unknown parameters and estimated by a random walk process in the Precise Point Positioning (PPP) solution. To demonstrate the performance of the new strategy, we carried out several experiments using collocated GPS and accelerometer. The experimental results show that the baseline shifts of the accelerometer are automatically corrected, and high precision coseismic information of strong ground motion can be obtained in real-time. Additionally, the convergence and precision of the PPP is improved by the combined solution.

A biologically inspired neurodynamics-based tracking controller of underactuated Autonomous Underwater Vehicles (AUV) is proposed in this paper. The proposed control strategy includes a velocity controller with biological neurons and an adaptive sliding mode controller. The biological neurons are embedded into the backstepping velocity controller to eliminate the sharp speed jumps commonly existing in vehicles due to tracking errors changing suddenly. The outputs of the velocity controller are used as the command inputs of the sliding mode controller, and the thruster control constraints problems that are commonly seen in the backstepping control of AUV are solved by the proposed controller. Simulation results show that the control strategy achieved success in smoothly tracking AUV position and velocity.

The observability of error states in Inertial Navigation System/Global Positioning System (INS/GPS) integration is of great importance. Rank tests or null space tests of the observability matrix have been adopted by previous works, however, for a time-varying system with a high-dimension error state vector, it is very difficult to analyse the observability matrix by these traditional methods. In this paper, the decoupled observability analysis method is proposed for an 18-dimensional INS/GPS integration system. By reducing the dimension of coupling error states, several six-dimensional decoupled observability sub-matrices are obtained, which make the observability analyses easier. The observability results of error states are obtained by the proposed method. Covariance simulation with an Extended Kalman filter (EKF) and a flying test were performed which confirmed the theoretical results.

In recent years, navigation by stellar refraction has received considerable attention, having advantages of high accuracy, simple construction, and low cost. Nevertheless, there are many limitations to the precision and application of this method using a traditional measurement model. This article studies the changing pattern of atmospheric density, the disturbed atmospheric density model and measurement model of stellar refraction ranging from 20 km to 50 km. Furthermore, a control algorithm of multiple mode switching and an adaptive measurement model are proposed. With this method, any refracted starlight from the scope of between 20 km and 50 km can be captured and the measurement model at the appropriate height can be automatically established. Due to this, the reliability and practicality of navigation have been raised considerably. Accuracy of navigation using the adaptive measurement method is observed to improve by about 14%, using computer simulation based on an Unscented Kalman Filter (UKF).

An Electronic Navigational Chart (ENC) is a two-dimensional abstraction and generalisation of the real world and it limits users' ability to obtain more real and rich spatial information of the navigation environment. However, a three-dimensional (3D) chart could dramatically reduce the number of human errors and improve the accuracy and efficiency of manoeuvring. Thus it is important to be able to visualize charts in 3D. This article proposes a new model for future Electronic Chart Display and Information Systems (ECDIS) and describes our approach for the construction of web-based multi-resolution future ECDIS implemented in our system Automotive Intelligent Chart (AIC) 3D ECDIS, including multi-resolution riverbed construction technology, multi-layer technology for data fusion, Mercator transformation of the model, rendering and web publishing methods. AIC 3D ECDIS can support global spatial data and 3D visualization, which merges the 2D vector electronic navigational chart with the three-dimensional navigation environment in a unified framework and interface, and is also published on the web to provide application and data service through the network.

Navigation and positioning system users are demanding greater accuracy and reliability in ever more challenging environments. This is driving a wave of rapid innovation, with the result that multisensor integrated navigation systems will become much more complex. This introduces a number of problems, including how to find the necessary expertise to integrate a diverse range of technologies, how to combine technologies from different organisations that wish to protect their intellectual property, and how to incorporate new navigation technologies and methods without having to redesign the whole system. It also makes it desirable to share development effort over a range of different applications. To address this, the feasibility of a modular approach to the design and development of multisensor integrated navigation and positioning systems is analysed. Assessments of the requirements of different user communities and the adaptability of the different navigation and positioning technologies to different contexts and requirements are presented. Based on this, the adoption of an open interface standard for modular integration is recommended and the issues to be resolved in developing that standard are outlined.

The errors of an inertial navigation system (INS) in response to gyros' errors can be effectively reduced by the rotation technique, which is a commonly used method to improve an INS's accuracy. A gyro's error consists of a deterministic contribution and a stochastic contribution. The compensation effects of gyros' deterministic errors are clear now, but the compensation effects of gyros' stochastic errors are as yet unknown. However, the compensation effects are always needed in a rotational inertial navigation system's (RINS) error analysis and optimization study. In this paper, the compensation effects of gyros' stochastic errors, which are modelled as a Gaussian white (GW) noise plus a first-order Markov process, are analysed and the specific formulae are derived. During the research, the responses of an INS's and a RINS's position error equations to gyros' stochastic errors are first analysed. Then the compensation effects of gyros' stochastic errors brought by the rotation technique are discussed by comparing the error propagation characteristics in an INS and a RINS. In order to verify the theory, a large number of simulations are carried out. The simulation results show a good consistency with the derived formulae, which can indicate the correctness of the theory.

The accuracy of attitude determination using a star sensor tends to be degraded if the host vehicle's manoeuvring smears the star image. In this paper, a new restoration algorithm with the aid of a Strap-down Inertial Navigation System (SINS) is proposed to reduce the effect of the smeared image. The smeared trace length is estimated with aid of the SINS angular rate. The restoration algorithm based on a Wiener filter is designed after the smeared zone is derived with the aid of the SINS coarse attitude. A tracking method is proposed to reject the stars of low centroid extraction accuracy. Simulations demonstrate that the success rate and the accuracy of attitude determination are improved significantly by the restoration algorithm even under a very fast rotation. The impact of the SINS error on the restoration is evaluated in the simulations.

This article proposes a novel method to autonomously determine the relative orbits of a small spacecraft formation flying with a slowly rotating near-Earth asteroid for the asteroid mitigation mission. A combined model of spacecraft-to-asteroid measurements with inter-spacecraft communication is built up. The dynamic model accounting for the perturbations is derived to describe the state variables of the Unscented Kalman Filter (UKF). The Lyapunov function approach is used to design a control law to maintain the orbits of the spacecraft formation. Four navigation scenarios are presented based on the different combinations of multiple measurements: two of them are non-collaborative scenarios which only include the spacecraft-to-asteroid measurements in the measurement models, while the other two are collaborative scenarios with the inter-spacecraft communication added into the measurement models. Simulation results are analysed and compared with each other to show the improvements of the filter performance in the aspects of the convergence speed and the accuracy of the estimator.

The Istanbul Strait is a challenging waterway for maritime traffic due to its rough topology, moderate to severe environmental conditions, and heavy local traffic. In particular, a total of 232 maritime accidents took place there between 2000 and 2011. In this study, generic fuzzy analytic hierarchy processes were used to assess the risk perception of stakeholders in the Istanbul Strait, including ship captains, maritime pilots and Vessel Traffic Services operators. These risk perceptions were then compared to the statistical maritime accident data, revealing a fundamental discrepancy between the risk perception and statistical data. Specifically, the area of the Straight with the highest number of accidents is perceived as relatively low-risk, whereas areas perceived as high-risk experience a lower number of accidents. Our results have implications for stakeholders as well as government agencies responsible for the safety of the Straight.

In this paper, we present a high-precision Mars entry integrated navigation algorithm under large uncertainties via a desensitised extended Kalman filter (DEKF). Firstly, a new six degree-of-freedom Mars entry dynamics model is derived based on the angular velocity outputs of a gyro, which is free of modelling errors in the aerodynamic and control torques. Secondly, both the accelerometer outputs and radio measurements between orbiters and entry vehicle are used as the observations embedded in a navigation filter to perform state estimation and suppress the measurement noise. Finally, a desensitised extended Kalman filter, exhibiting the desirable property of efficiently reducing the sensitivity of state variables with respect to model and parameter uncertainties, is adopted in order to overcome the adverse effects of initial state errors and uncertainties during Mars atmospheric entry and further improve entry navigation accuracy. The numerical simulation results show that the DEKF-based integrated navigation algorithm developed in this paper can achieve a better navigation performance with higher accuracy when compared with the standard extended Kalman filter (EKF)-based integrated navigation algorithm in the presence of larger state errors and parameter uncertainties.

Navigational software often lacks official standardisation of the methods used and their accuracy due to commercial confidentiality. The “black box solutions” used by navigational systems are unknown, thus a logical and simple method to solve navigational problems must be presented. This paper presents new meridian arc formulae by the least squares method. As the traditional meridian arc formulae cannot be expressed as a closed form, they are often truncated to the first few terms for practical use and in doing so neglect the values not used. By forming an overdetermined system with known components of the traditional meridian arc formula and actual length of the meridian arc, the least squares method can be used to approximate the best fitting coefficients for the traditional meridian arc formulae and forms the new compact formulae. The new formulae are based on highly accurate values of the meridian arc for the WGS-84 ellipsoid datum, and are perfect for the computational algorithms implemented in navigational software such as Geographic Information Systems (GIS), Electronic Chart Display and Information Systems (ECDIS) and other Electronic Chart Systems (ECS). Their accuracy is compared with other methods and shows that the new proposed formulae are shorter and accurate with negligible errors. The new formulae can be adapted to the accuracy needed and imply different numbers of coefficients. This can also shorten the calculations in navigation such as rhumb-line or great elliptic sailing on the ellipsoid because the meridian arc length is essential for these calculations.

Four methods to calculate the Vertical Protection Level (VPL) can be used in Advanced Receiver Autonomous Integrity Monitoring (A-RAIM), among which the ideal method is the strictest one. To obtain the ideal VPL satisfying the exact required integrity risk, the worst case bias with the maximum integrity risk is searched for. This investigation has found that the correct worst case highly depends on the choice of the input VPL. To gain the correct result, the computation becomes complex and the accuracy of the result is compromised. Therefore, a new procedure is designed with a new search: the maximum VPL is searched to encompass all possible bias sizes. Since VPL is calculated with a given integrity risk for each bias size, the uncertainty of the arbitrary VPL input in the ideal method is avoided. Also, an optimisation algorithm is adopted to improve computational efficiency. It is shown that the new method is more reliable and efficient than the current best method. Simulation results worldwide also show that the new approach has improved A-RAIM availability from 32%–38% to 74% with GPS and from 44%–43% to 85% with Galileo.

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.

This paper focuses on the performance analysis of ionosphere monitoring using the measurements from a BeiDou Continuously Operating Reference Stations (CORS) network. Combined pseudo-range and carrier phase observations are used to estimate total electron content (TEC) and the hardware delay deviation is also computed. Using the observations from five BeiDou CORS in China, the TEC monitoring results were obtained from each station and compared with GPS monitoring results and also those from the Global Ionosphere Maps (GIM) model. Numerical computation shows that the BeiDou system has the ability to precisely detect the TEC diurnal variation trend on each station. The Residual Mean Square (RMS) difference between the BeiDou and the GIM model at a higher latitude station is about four TEC Units (TECU), while the RMS difference between the GPS and the GIM is about three TECU; at a lower latitude station this difference increases to six TECU for BeiDou and four TECU for the Global Positioning System (GPS); at the lowest latitude station in this study, the differences for both systems are about six TECU.

Analysis of helicopter accidents is fundamental to the development of effective mitigation measures. However, there are significant weaknesses in the current methods. This paper proposes a new structured framework for the analysis of accidents in helicopter operations, which includes the determination of the appropriate timeframe for analysis, establishment of terminological definitions, identification of the relevant accident variables and data sources, and the execution of a three-fold statistical analysis strategy. It is implemented in the context of worldwide offshore helicopter operations, enabling the identification of a number of areas for priority intervention including the need for a global harmonisation of accident data capture and dissemination, causal factor-based metrics for the calculation of accident rates, better pilot support for night-time and arrival operations, and a new safety paradigm to mitigate rare accidents. The framework is recommended for the analysis of helicopter accidents and incidents to support safety improvement.

This paper addresses a simple implementation technology for localising a group of mobile nodes using the Peer-To-Peer (P2P) ranging measurements obtained from a Mobile Wireless Sensor Network (MWSN). In recent years, MWSN-based multi-target localisation technologies have been investigated with alacrity. However, it is difficult to implement P2P ranging and data transformation for multi-target localisation iteratively using single channel MWSN. Also, there are critical problems in the conventional localisation algorithms associated with the estimation errors owing to the erroneous linearization of a nonlinear range equation and bad relative locations of the reference nodes and target node. In this paper, very simple P2P ranging and connection data sharing procedures that can be easily implemented in single channel MWSN are established. Moreover, an adaptive localisation algorithm is presented to reduce the estimation errors that may occur in the conventional localisation algorithms. To verify the performance of the presented implementation technology, a localisation system prototype is developed and the presented procedures and algorithm are embedded in the prototype. Through actual experiments, the validity of the localisation system containing the proposed procedures and algorithm is demonstrated.

Geostationary Earth Orbit (GEO) satellites play a significant role in the space segment of the Chinese Area Navigation System. The C-Band transfer ranging method developed by the National Time Service Center (NTSC) has been widely used in the Chinese Area Positioning System (CAPS), with its advantages of separating satellite ranging from time synchronization and being unaffected by weather. The explicit ranging correction models for the C-Band transfer ranging method are introduced in detail in this article for the first time. Precise Orbit Determination (POD) using C-Band pseudo-range observation of GEO satellite 2010-001A in July 2012 has been conducted. The residual Root Mean Square (RMS) of each site and POD are analysed with orbit difference over overlaps of adjacent orbit arcs. Moreover, the orbit of the GEO satellite has been evaluated by Satellite Laser Ranging (SLR) data from both domestic and foreign SLR sites for the first time. The residual RMS of POD using C-Band observation is better than 0·1 m, and the orbit difference over overlaps of adjacent orbit arcs is better than 3 m. In addition, the residual RMS in line-of-sight for a SLR site in China are better than 1 m, while the RMS for the Yarragadee site in Australia is about 3·4 m. It has been shown that the GEO satellite orbit accords very well with the C-Band observation. Also, the distribution of CAPS stations affects the orbit precision. All sites in CAPS are now located in China with low and medium latitudes. The residual RMS of the SLR site in the southern hemisphere is larger than that of the site in China.