Transfer Alignment (TA) is the initialisation process of the Inertial Navigation System (INS) of an air-launched weapon before its release by using the data from the aircraft INS. The aim of this paper is to improve the TA performance by taking into account the aircraft flexures deterministically. The developed procedure neither requires captive carry tests for determination of flexures nor increases the size of the problem, and can be used in real-time missions of any type of military aircraft. The procedure is evaluated for the Velocity Match (VM) method as well as the Velocity and Attitude Match (VAM) method, which are applied through a Kalman Filter (KF). Using a short-time Wing-Rock (WR) manoeuvre, the results of both methods are compared to each other for two cases in which either the flexures are taken into account deterministically, or modelled as noise by assuming that they are unknown. Standard deviations of the errors and the Circular Error Probable (CEP) variations have shown that the TA performance of the VAM method can be much improved if aircraft flexures are incorporated deterministically into the method. The improved performance makes possible target of opportunity missions at shorter weapon ranges, and it decreases target strike errors.

In shipborne Transfer Alignment (TA) applications, partial observability is one of the most important factors limiting convergence velocity. This paper proposes a new method of attributing weak observable states and lever-arm variables to a group of constraints in order to improve the observability of TA model. This yields the so-called Constrained Transfer Alignment (CTA) model which is uniformly observable even under zero-manoeuvre conditions. Within this framework, the Moving Horizon Estimation (MHE) and its stability analysis are also addressed. Finally, comparative simulation results are given to demonstrate the advantages of the proposed approach.

In an environment where Global Positioning System (GPS) jamming is present, the Dutch army faces all sorts of challenges in such a deployment area, e.g., for the determination of gun locations. Nowadays, an Inertial Navigation System (INS) is used as back-up positioning system. However, to use this back-up tool within specified accuracy limits, additional procedures are needed that limit deployment. An alternative positioning method such as a low-frequency navigation system could be a solution to these problems. An example of a low-frequency navigation system that is currently operational in certain regions is eLORAN (enhanced LOng RAnge Navigation). Hypothetically, a system like this could be realised in a similar way for positioning, navigation and timing solutions for large scale military operations. That is if the performance of eLORAN meets the accuracy requirements. In this paper, eLORAN performances are examined using experiments conducted at a military heath land area in the Netherlands. Moreover, eLORAN Additional Secondary Factor (ASF) correction maps have been computed for that particular area, based on differences in position between Real-Time Kinematic (RTK) GPS and eLORAN measurements at a fixed number of points in that area. Different interpolation methods are used to create these ASF maps. The maps, obtained from static measurements, are used to enhance eLORAN's performance in dynamic measurements using a military platform. The content of this paper has been presented during the European Navigation Conference 2011 in London.

In order to solve the problem of a strapdown Inertial Navigation System (INS) under a vibrating base, a ground fine alignment method is proposed in this paper, and it is about reconstructing the error equations of a strapdown INS. In this method, the effects aroused by the linear and angular vibration are considered as system and measurement noise; in addition, they are also regarded as the components of a system matrix. This setting avoids the effects of linear and angular vibration under a vibrating base. The results of simulation and experiment show that our method is suitable for a ground fine alignment of a strapdown INS under a vibrating base.

The paper presents the continuation of the author's research on Evolutionary Sets of Safe Ship Trajectories (ESoSST) methodology. In an earlier paper (Szlapczynski, 2011) the author described the foundations of this methodology, which used Evolutionary Algorithms (EA) to search for an optimal set of safe trajectories for all the ships involved in an encounter. The methodology was originally designed for open waters or restricted waters when only the standard Convention on the International Regulations for Preventing Collisions at Sea (COLREGS, 1972) rules apply. However, within Traffic Separation Schemes (TSS), where additionally Rule 10 of COLREGS applies, the problem is much more complex and a new solution is needed. This paper introduces the extended ESoSST methodology, with a focus on changes that have to be made to obey Rule 10 and fully support TSS. These changes include detecting and penalizing TSS violations, as well as the pre-processing phase (generating the initial population, which includes predefined TSS-compliant tracks). The methodology has been designed for possible application in Vessel Traffic Service (VTS) centres. Its new mechanisms are presented with details. The examples are included of the results of the computer simulation tests carried out for the Gulf of Gdansk TSS to illustrate the methodology's effectiveness and functional scope.

Gravity Aided Navigation (GravAN) and Geomagnetism Aided Navigation (GeomAN) are two methods for correcting Inertial Navigation System (INS) errors of Autonomous Underwater Vehicles (AUVs) without compromising the AUV mission. One requirement for applying these methods is the relatively large field feature variations along the navigation trajectory. But in some regions with small gravity or geomagnetic variation, it is very difficult to achieve a reliable result solely by GravAN or GeomAN. If these two methods were combined, gravity and geomagnetism information could be complementary and the aided navigation ability could potentially be improved, especially in those regions when neither method is valid. Based on that concept, a Gravity and Geomagnetism Combined Aided Navigation (GGCAN) method is consequently proposed in this paper as a possible solution. The Gravity Anomaly Grid (GAG2) and Earth Geomagnetic Anomaly Grid (EMAG2) are utilized as the background databases, and then a Multiple Model Adaptive Estimation (MMAE) is adopted to obtain an optimal estimated navigation position. Furthermore, an Optimal Weight Allocation Principle (OWAP) is introduced to the combined GravAN and GeomAN methods, together with a weighted average. In simulation, two special regions in the Western Pacific Ocean were chosen to test the proposed method. The results show that GGCAN can improve the position success rate and reduce the error, compared to GravAN or GeomAN. Results indicate that the GGCAN method proposed in this study is able to improve the accuracy and reliability of an aided navigation system.

To improve the computational efficiency and dynamic performance of low cost Inertial Measurement Unit (IMU)/magnetometer integrated Attitude and Heading Reference Systems (AHRS), this paper has proposed an effective Adaptive Kalman Filter (AKF) with linear models; the filter gain is adaptively tuned according to the dynamic scale sensed by accelerometers. This proposed approach does not need to model the system angular motions, avoids the non-linear problem which is inherent in the existing methods, and considers the impact of the dynamic acceleration on the filter. The experimental results with real data have demonstrated that the proposed algorithm can maintain an accurate estimation of orientation, even under various dynamic operating conditions.

Unmanned Air Systems (UAS) navigate using Global Navigation Satellite Systems (GNSS), but GNSS vulnerability precludes its use as the only means of navigation and requires a secondary means of navigation. A differentiating characteristic of UAS is their periodic communications with the ground station. This paper analyses the adequacy of employing UAS Command, Control and Communications (C3) as a secondary means of navigation. With no additional infrastructure, an Extended Kalman Filter (EKF) is used to process C3 messages and to obtain the positions of the UAS. Navigation accuracy and integrity are calculated in a scenario with three UAS. The obtained results meet the International Civil Aviation Organization (ICAO) Performance-Based Navigation (PBN) requirements.

The process used to create charted depictions of aviation instrument approach procedures in the United States is examined. The rapid growth of iPad®-like mobile technologies is discussed relative to the historical context of chart implementation. Notional new methods of electronic chart generation are introduced, demonstrating both the functional possibilities and concerns not directly addressed by existing regulation for private aircraft operators. These concerns suggest a ‘yin-yang’ of the stifling of innovation versus the creation of latent safety hazards. The article concludes by recommending regulatory oversight review of approach chart implementation. A glossary of terms is included at the end of this paper. The facts, analysis, and opinions offered in this article represent an independent effort of the author and do not reflect the opinions of any academic institution or government agency. The author also has a limited financial interest in certain iOS® applications.

Space weather disturbances cause considerable effects on Global Navigation Satellite Systems (GNSS) performance and operation, affecting society and the economy due to the growing reliance on GNSS, especially in densely populated mid-latitudes. Recent studies hypothesised potential utilisation of the Disturbance storm-time (Dst) index for indication of an approaching ionospheric storm and possible deterioration of the GNSS positioning performance. We challenged the hypothesis in the case of the Halloween 2003 event in an attempt to confirm the direct correlation between the Dst index dynamics and the Global Positioning System (GPS) positioning performance in the mid-latitude Mediterranean area. Our results provide no evidence of the direct Dst-GNSS performance correlation for the observed event.