The impact of new signals on precise marine navigation - initial results from an experiment in Harwich Harbour

The General Lighthouse Authorities of the United Kingdom and Ireland (GLAs) are supporting a project at University College London (UCL) to study whether it is possible to meet the International Maritime Organisation’s (IMO) future requirements for port and harbour approach using future GNSS constellations, as detailed in IMO resolution A.915. This paper presents the results of a trial focusing on the accuracy, integrity, availability and continuity of port navigation, port approach, and docking. Abstract The required accuracy for docking is 0.1 m (95\%), which currently necessitates the use of Real Time Kinematic (RTK) processing. We consider the single-epoch geometry-based approach, which is robust against loss of lock and will fully benefit from the additional satellites. The trial was held at the beginning of May 2008 and saw THV Alert navigate into Harwich Harbour while satellite observation data were recorded from the vessel and from shore-based reference stations. Additional data were obtained from nearby Ordnance Survey reference stations, and two total stations were used to track the vessel’s passage to provide a truth model. Several modernised GPS satellites were tracked. The data were processed under different scenarios, using software developed at UCL, and the positioning performance analysed. Abstract Providing integrity for single-epoch RTK is particularly difficult. The identification of phase observation outliers is not possible before the integer ambiguities are resolved, but an undetected outlier could prevent successful ambiguity resolution. However, it will not always be necessary to fix every ambiguity to achieve the required precision, particularly with a multi-GNSS constellation. This paper introduces a new algorithm for partial ambiguity resolution in the presence of measurement bias that has been developed and tested at UCL.  This algorithm results in an improved ambiguity resolution success rate at the expense of computation time

A Dense Reference Network for Mass-Market Centimeter-Accurate Positioning

The quality of atmospheric corrections provided by a dense reference network for centimeter-accurate carrierphase differential GNSS (CDGNSS) positioning is investigated. A dense reference network (less than 20 km inter-station distance) offers significant benefits for mass-market users, enabling lowcost (including single-frequency) CDGNSS positioning with rapid integer ambiguity resolution. Precise positioning on a massmarket platform would significantly influence the world economy, ushering in a host of consumer-focused applications such as globally-registered augmented and virtual reality and improved all-weather safety and efficiency for intelligent transportation systems, applications which have so far been hampered by the several-meter-level errors in standard GNSS positioning. This contribution examines CDGNSS integer ambiguity resolution performance in terms of network correction uncertainty, and network correction uncertainty, in turn, in terms of network density. It considers the total error in network corrections: a sum of ionospheric, tropospheric, and reference station multipath components. The paper’s primary goal is to identify the network density beyond which mass-market users would see no further significant improvement in ambiguity resolution performance. It finishes by describing development and deployment of a low-cost dense reference network in Austin, Texas.Aerospace Engineering and Engineering Mechanic

Vertiport Navigation Requirements and Multisensor Architecture Considerations for Urban Air Mobility

Communication, Navigation and Surveillance (CNS) technologies are key enablers for future safe operation of drones in urban environments. However, the design of navigation technologies for these new applications is more challenging compared to e.g., civil aviation. On the one hand, the use cases and operations in urban environments are expected to have stringent requirements in terms of accuracy, integrity, continuity and availability. On the other hand, airborne sensors may not be based on high-quality equipment as in civil aviation and solutions need to rely on tighter multisensor solutions, whose safety is difficult to assess. In this work, we first provide some initial navigation requirements related to precision approach operations based on recently proposed vertiport designs. Then, we provide an overview of a possible multisensor navigation architecture solution able to support these types of operations and we comment on the challenges of each of the subsystems. Finally, initial proof of concept for some navigation sensor subsystems is presented based on flight trials performed during the German Aerospace Center (DLR) project HorizonUAM

Tightly-Coupled Opportunistic Navigation for Deep Urban and Indoor Positioning

A strategy is presented for exploiting the frequency stability, transmit location, and timing information of ambient radio-frequency “signals of opportunity” for the purpose of navigating in deep urban and indoor environments. The strategy, referred to as tightly-coupled opportunistic navigation (TCON), involves a receiver continually searching for signals from which to extract navigation and timing information. The receiver begins by characterizing these signals, whether downloading characterizations from a collaborative online database or performing characterizations on-the-fly. Signal observables are subsequently combined within a central estimator to produce an optimal estimate of position and time. A simple demonstration of the TCON strategy focused on timing shows that a TCONenabled receiver can characterize and use CDMA cellular signals to correct its local clock variations, allowing it to coherently integrate GNSS signals beyond 100 seconds.Aerospace Engineering and Engineering Mechanic

Preliminary Analysis of Skywave Effects on MF DGNSS R-Mode Signals During Daytime and Nighttime

Accurate positioning, navigation, and timing (PNT) performance are prerequisites for several technologies today. In a marine environment, it is difficult to visually identify one's position accurately, leading to safety concerns. Currently, PNT information is provided mainly from Global Navigation Satellite Systems (GNSS); however, it is vulnerable to radio frequency interference, spoofing, and ionospheric anomaly. Therefore, research on a backup system is needed. Ranging Mode (R-Mode), a terrestrial integrated navigation system, is being investigated for use in a marine environment. R-Mode is a positioning technology that integrates terrestrial signals of opportunity such as medium frequency (MF) differential GNSS (DGNSS), very high frequency (VHF) automatic identification system (AIS), and enhanced long-range navigation (eLoran) signals. Previous studies in Europe show that signals in the MF band differ greatly in accuracy between daytime and nighttime. This difference is primarily caused by skywave. In this study, the MF DGNSS R-Mode signal transmitted from Chungju, Korea was received in Daesan and Daejeon, Korea. The skywave effect during daytime and nighttime was compared and investigated. In addition, the continuous wave intensity of the R-Mode signal was increased during the nighttime to compare its effect on the measurement accuracy

Adaptive real-time dual-mode filter design for seamless pedestrian navigation

Seamless navigation requires that the mobile device is capable of offering a position solution both indoors and outdoors. Novel seamless navigation system design was implemented and tested to achieve this aim. The design consists of general navigation system framework blocks and of the necessary interface agreements between the blocks. This approach enables plug-and-play style design of modules. The implementation used four preselected key technologies. Microstrain 3DM-GX4-45 foot-mounted inertial measurement unit sensor data was fused together with the u-blox GNSS receiver positions outdoors. Context sensitive inference engine enabled the fusion of position updates indoors from the Decawave TREK1000 Ultra WideBand ranging kit and from the 6 Kontakt.io/Raspberry Pi anchor-based Bluetooth low energy fingeprinting system. Novel dual-mode filter design uses a particle filter and the pentagon buffer enhanced Kalman filter in the position solution derivation. Depending on the map and the walls in the environment and on the quality of position updates, the implemented control logic employs the most fit filter for the current context. Computational power is now focussed, when particle filter is needed. The novel pentagon buffer enhanced Kalman filter is 10 times faster, allowing power saving when situation is not too critical. Moreover, the buffer provides position updates by interacting with the map and helps to correct the position solution. The navigation system is seamless according to the tests conducted around and within the Nottingham Geospatial building. No user input is needed for smooth transition from outdoors to indoors and vice versa. The system achieves an accuracy of 2.35m outdoors and 1.4 m indoors (95% of error). Inertial system availability was continuous, while GNSS was available outdoors and BLE and UWB indoors

Combining visual, pedestrian, and collaborative navigation techniques for team based infrastructure free indoor navigation

Peer reviewe

Map Matching Algorithm for the ”Spar på farten” Intelligent Speed Adaptation Project

The availability of Global Navigation Satellite Systems (GNSS) enables sophisticated vehicle guidance and advisory systems such as Intelligent Speed Adaptation (ISA) systems. In ISA systems, it is essential to be able to position vehicles within a road network. Because digital road networks as well as GNSS positioning are often inaccurate, a technique known as map matching is needed that aims to use this inaccurate data for determining a vehicle’s real road-network position. Then, knowing this position, an ISA system can compare speed with the speed limit in effect and take measures against speeding. This paper presents an online map matching algorithm with an extensive number of weighting parameters that allow better determination of a vehicle’s road network position. The algorithm uses certainty value to express its belief in the correctness of its results. The algorithm was designed and implemented to be used in the large scale ISA project ”Spar på farten” . Using test data and data collected from project participants, the algorithm’s performance is evaluated. It is shown that algorithm performs correctly 95 % of the time and is capable of handling GNSS positioning errors in a conservative manner