Acquisition of unaided weak Global Positioning System (GPS) signals requires long coherent integration time and thus all the possible navigation data bit combination paths have to be searched. In this paper, to improve the computational efficiency, the Improved Fast Modified Double-Block Zero Padding (IFMDBZP) algorithm using the Optimal Path Search Method (OPSM) is proposed instead of the FMDBZP algorithm using the All Paths Search Method (APSM). The proposed method consists of unlikely data bit combination path elimination by applying the Viterbi algorithm during each coherent integration step to improve the FMDBZP algorithm. The analyses show that the proposed OPSM can reduce the computation calculations and save memory space without suffering any loss compared to the APSM. And the longer the coherent integration time is, the more benefit one can gain from the proposed method. The simulation results also show that the IFMDPZP algorithm using the proposed OPSM has the same acquisition performance as the APSM.

Satellite Navigation Systems (SNS) provide Position, Velocity and Time (PVT) services. The SNS is required to maintain its own System Time with high accuracy. To set up the precise System Time, each system component should maintain its own time within a specified limit. In the SNS, the onboard Space Vehicle (SV) time generator is one of the components and it should be set and maintained with few nanoseconds accuracy. To achieve accurate time setting with minimum difference between the ground and onboard SV systems, the onboard time setting should be highly predictable and accurate. This paper proposes an approach to initialize/set the onboard SV Time. The paper also discusses the concept of synchronization of SV Time with System Time with an overall accuracy better than 1 nsec. The proposed technique requires minimum setting time and synchronization steps and there is no need to predict accurate uplink propagation delay and command execution time.

In this paper, equations are established to solve problems of Rhumb Line Sailing (RLS) on an oblate spheroid. Solutions are provided for both the inverse problem and the direct problem, thereby providing a complete solution to RLS. Development of these solutions was achieved in part by means of computer based symbolic algebra. The inverse solution described attains a high degree of accuracy for distance and azimuth. The direct solution has been obtained from a solution for latitude in terms of distance derived with the introduction of an inverse series expansion of meridian arc-length via the rectifying latitude. Also, a series to determine latitude at any longitude has been derived via the conformal latitude. This was achieved through application of Hermite's Interpolation Scheme or the Lagrange Inversion Theorem. Numerical examples show that the algorithms are very accurate and that the differences between original data and recovered data after applying the inverse or direct solution of RLS to recover the data calculated by the direct or inverse solution are very small. It reveals that the algorithms provided here are suitable for programming implementation and can be applied in the areas of maritime routing and cartographical computation in Graphical Information System (GIS) and Electronic Chart Display and Information System (ECDIS) environments.

Aided Inertial Navigation Systems (INS) systems are commonly implemented in land vehicles for a variety of applications. Several methods have been reported in the literature for evaluating aided INS performance. Yet, the INS error-state-model dependency on time and trajectory implies that no closed-form solutions exist for such evaluation. In this paper, we derive analytical solutions to evaluate the fusion performance. We show that the derived analytical solutions manage to predict the error covariance behavior of the full aided INS error model. These solutions bring insight into the effect of the various parameters involved in the fusion of the INS and an aiding sensor.

Unmanned Marine Vehicles (UMVs), like their aerial cousins Unmanned Aerial Vehicles (UAVs), are not easily classified under existing legal regimes. Even though unmanned, should these seagoing drones be treated as ‘vessels’ under the Law of the Sea Convention articles on navigation rights and duties? Are they ‘vessels’ under the International Regulations for Preventing Collisions at Sea (COLREGs, 1972)? If so, should they be accorded a manoeuvring priority vis-à-vis other vessels? Are the differences between autonomous UMVs and the increasingly automated manned vessels all that great, such that classification should turn on whether the vessel is manned rather than on how navigation and collision avoidance decisions are made and executed?

GNSS relative positioning technique is an important field of study, in which the standard ‘GNSS Baseline Model’ is often used. Differencing between observation equations is used to construct the mathematical model, since this method can eliminate some common errors in the GNSS signal measurements. The ‘Orthogonal Transformation’ method can also construct the GNSS Baseline Model. However, as is described by some scholars, this model may avoid some drawbacks of Double Differencing (DD) while maintaining all the advantages. For comparison purposes, this model is evaluated and the theoretical equivalence of both approaches is proved for the short baseline from two aspects: the Integer Ambiguity Resolution and the conditional least-squares baseline vector.

Vessels are found frequently operating under the Automatic Identification System (AIS) ‘Not Under Command’ (NUC) option near ports and close to shores in order to report their manoeuvre status to nearby traffic. When asked if they are under any kind of restriction regarding their engines or steering, they often answer that they are just drifting or waiting for the pilot or shipowner's orders. The question that arises is this: “Are these vessels really under an NUC situation or can the AIS Navigational Status menu adapt to the different circumstances of navigation?”.