This study is a brief report of the only re-sailing of Columbus' 1492–1493 Voyage following the data in his log in a scientifically controlled research voyage by a professional and experienced global and ocean navigator. The study is follow-on to the article: “The Controversial Skill of Columbus as a Navigator: An Enduring Historical Enigma,” published in The Journal of Navigation (2009) Vol. 62, 417–4251.

The expedition of Zheng He's fleet to the Western Ocean1 in the first half of the 15th century is an important event in the history of navigation, which has attracted the broad attention of domestic and foreign scholars from different fields2. This paper reveals the relation between Zheng He's voyages and the Asian Monsoon from a geographical perspective. Historical records show that Zheng He's seven voyages to the Western Ocean were precisely organized and successfully carried out due to careful consideration of the conditions and periodical patterns of the Asian tropical and subtropical monsoon. Details such as fleet routes, sailing schedules, wind-waiting points, divergent and rendezvous points were painstakingly planned and arranged in advance by the organizers of the expedition, who all paid close attention to the changing patterns of the Asian Monsoon.

In environments where GNSS is unavailable or not useful for positioning, the use of low cost MEMS-based inertial sensors has paved a way to a more cost effective solution. Of particular interest is a foot mounted pedestrian navigation system, where zero velocity updates (ZUPT) are used with the standard strapdown navigation algorithm in a Kalman filter to restrict the error growth of the low cost inertial sensors. However heading drift still remains despite using ZUPT measurements since the heading error is unobservable. External sensors such as magnetometers are normally used to mitigate this problem, but the reliability of such an approach is questionable because of the existence of magnetic disturbances that are often very difficult to predict. Hence there is a need to eliminate the heading drift problem for such a low cost system without relying on external sensors to give a possible stand-alone low cost inertial navigation system. In this paper, a novel and effective algorithm for generating heading measurements from basic knowledge of the orientation of the building in which the pedestrian is walking is proposed to overcome this problem. The effectiveness of this approach is demonstrated through three field trials using only a forward Kalman filter that can work in real-time without any external sensors. This resulted in position accuracy better than 5 m during a 40 minutes walk, about 0·1% in position error of the total distance. Due to its simplistic algorithm, this simple yet very effective solution is appealing for a promising future autonomous low cost inertial navigation system.

Personal navigation has grown rapidly with the introduction of ubiquitous computing and the new generation of smart phones. Appropriate localisation is nowadays a central element for many applications and mobile services. However the proper estimation of the user's location remains a challenge. This paper presents an innovative concept for accurate and reliable positioning in challenging applications. It consists of three components: an absolute geographical reference, the hybridisation of complementary technologies and specific motion models. Two different applications illustrate this concept: urban displacement of blind people and guidance of firefighters. The validity of the concept is assessed with indoor experimental results. Finally the conclusion gives a prospective view of robust personal navigation.

Some new Advanced Driver Assistance Systems (ADAS) need on-the-lane vehicle positioning on accurate digital maps, but current applications of vehicle positioning do not justify the surcharge of very accurate equipment such as DGPS or high-cost inertial systems. For this reason, the performance of GPS in autonomous mode is analyzed. Although satisfactory results can be found, in some areas the GPS signal is lost or degraded so it is necessary to know the positioning error when using only inertial system data. A theoretical approach based on the uncertainty propagation law is used to estimate the upper limit of distance that can be travelled fulfilling the specifications of an assistance system. Test results support the conclusions of this approach. Finally, the combination of GPS and inertial systems is studied, with the conclusion that the theoretical approach is valid when inertial measurements are used right from the start of GPS signal degradation, without waiting for a complete loss of signal.

In low-cost self-contained pedestrian navigation systems, traditional Pedestrian Dead Reckoning (PDR) solutions utilize accelerometers to derive the speed as well as the distance travelled, and obtain the walking heading from magnetic compasses or gyros. However, these measurements are sensitive to instrument errors and disturbances from ambient environment. To be totally different from these signals in nature, the electromyography (EMG) signal is a typical kind of biomedical signal that measures electrical potentials generated by muscle contractions from the human body. This kind of signal would reflect muscle activities during human locomotion, so that it can not only be used for speed estimation, but also disclose the azimuth information from the contractions of lumbar muscles when changing the direction of walking. Therefore, investigating how to utilize the EMG signal for PDR is interesting and promising. In this paper, a novel EMG-based speed estimation method is presented, including setup of the EMG equipment, pre-processing procedure, stride detection and stride length estimation. Furthermore, this method suggested is compared with the traditional one based on accelerometers by means of several field tests. The results demonstrate that the EMG-based method is effective and its performance in PDR can be comparable to that of the accelerometer-based method.

The CNS/ATM concept envisages reliance on global satellite navigation systems to underpin future air traffic management that is able to cope with the ever-increasing demand for air travel without jeopardising safety and the environment. In order to benefit from GNSS, it is crucial that the navigation performance required of air navigation systems is derived and agreed, based on sound principles. Significant work has been undertaken to date and agreement reached on the navigation requirements for the phases of flight up to Category I (CAT-I) precision approach, and proposals are under discussion for CAT-III precision approach. This paper completes a typical flight profile by addressing airport surface movement, and proposing the requirements based on operational requirements for each airport category, to support operations in zero visibility conditions. The benefits of the approach taken in the derivation of the requirements are discussed relative to the existing navigation requirements.

In this study, satellite based pseudo-range measurements are integrated with accelerometer measurements made by six accelerometers located on the six faces of a cuboid, to independently measure the translational and rotational accelerations, and the pseudo-range. These measurements are then processed by an adaptive Unscented Kalman filter (UKF) to correct for the estimated errors and to obtain the required position and velocities at two independent locations. The relative position and velocity are then obtained by the application of standard vector identities. From these estimates, the position and velocity kinematics of prosthetic limbs and measurements of the joint angles, the true ambulatory position is estimated using a third independent UKF based estimator. The robotic limb joint offsets are assumed to be biased which are also estimated by the third UKF. The basic assumption is that the errors in the measurements are quite similar at the two locations and for this reason it is hypothesised that these errors would be reduced when the relative position and velocity were estimated. The results indicate that the steady-state ambulatory position error of the end-effector is reduced by more than 98%.

A scrutiny of the existing time differencing carrier phase (TDCP) velocity estimation algorithms has revealed several shortcomings that could be further improved. One of these is that the velocity estimation at epoch t would require the receiver positions at epoch t+Δt or more are available. Another is the usage of satellite velocities in the calculations which would increase the receiver computational load and degrade the accuracy. In this paper, an improved TDCP velocity estimation approach has been proposed and tested. The new approach depends only on receiver position at epoch t and satellite positions at epoch t and t+Δt. Satellite velocities are not required in this calculation. This proposed algorithm has been validated using static and kinematic field test data, showing that equivalent velocity accuracy achievable by using differential GPS techniques can be made possible with the proposed standalone GPS method.

The existence of Unexploded Ordnance (UXO) is a serious environmental hazard, especially in areas being converted from military to civilian use. The detection and discrimination performance of UXO detectors depends on the sensor technology as well as on the processing methodology that inverts the data to infer UXO. The detection systems, typically electro-magnetic induction (EMI) devices, require very accurate positioning (or geolocation) in order to discriminate candidate UXO from non-hazardous items. For this paper, a hand-held geolocation system based on a tactical-grade IMU, such as the HG1900, was tested in the laboratory over a small, metre-square area in sweep and swing modes. A camera position system was used to emulate GPS or alternative ground-based external ranging systems that control positioning errors. The proposed integration algorithm is a combination of linear filtering (Extended Kalman Filter) and nonlinear, also non-Gaussian filtering (Unscented Particle Filter) in the form of the Rao-Blackwellized Particle Filter (RBPF). The test results show that the position accuracy was improved by applying nonlinear filter-based smoothing techniques in both the straight and curved sections of the sweep and swing trajectories.

The demand for navigation assistance and advances in several technologies has been paving the way for Personal Navigation Services (PerNavs). As users increasingly rely on PerNavs for navigation assistance, they gain a better understanding of what PerNavs can offer and how they operate. This trend, consequently, will increase the demand for PerNav that can provide high quality solutions. While there have been studies addressing uncertainties associated with selected individual navigation modules, there is a void in the literature addressing the overall uncertainty in PerNavs. In this paper, we discuss uncertainty in PerNavs by analyzing uncertainties associated with each of its modules and how they propagate and impact other modules. A Bayesian network is presented as one possible model to manage (by developers) and communicate (to users) uncertainty in PerNavs.

To effectively design navigation and travel information systems, car manufacturers need data on how these systems are typically used. In this study, researchers surveyed thirty typical drivers and eleven auto experts to determine previously visited destinations, favourite destinations, and other information. Unexpectedly, subjects predominantly reported they used navigation systems to reach familiar destinations (typical drivers: 61%; auto experts: 89%). History was self-reported to be a very common entry method (typical drivers: 30%; auto experts: 24%), which conflicted with data retrieved from navigation systems (both groups: <1%). Based on the history list, common trip purposes included Shopping and visiting Friends' Houses.