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Position and time are some of the most vital pieces of information for convenience, security, and safety in our daily lives and have enabled innovative advancements in many science and engineering fields. Since Global Positioning System (GPS) became available to the public, GPS has been applied not only to smartphones and vehicular navigation systems that we use every day, but also to diverse areas such as Internet-of-Things (IOT), synchronization, cellular communications, military, geodesy, agriculture, mining, construction, remote sensing and more. However, the legacy GPS has only been successful in outdoor and open-sky applications, and the demand for positioning and navigation in indoor and urban street environments has been rapidly growing. A number of countries are carrying out their own plans to build advanced satellite-based navigation systems, called global navigation satellite systems (GNSS), with initial operation capability planned around 2020. GNSS will provide a number of new wideband signals with encoded data at multiple frequencies for the enhancement of accuracy, robustness, and signal availability in the GPS-denied environments, such as dense urban streets and indoor environments, as well as in the presence of cyber-attacks. On the other hand, there have been research activities around the world to develop indoor positioning and navigation technologies in diverse directions. One conventional approach is to use radio signals from wireless infrastructure such as WiFi, UWB, and LTE (i.e., cellular signals), and the other is to utilize non-radio signal measurements such as camera-vision, in-building magnetic anomaly, and inertial measurements.

To enable Global Navigation Satellite System (GNSS)-based precise relative positioning, real-time kinematic (RTK) systems have been widely used. However, an RTK system often suffers from a wrong integer ambiguity fix in the GNSS carrier phase measurements and may take a long initialization time over several minutes, particularly when the number of satellites in view is small. To facilitate a reliable GNSS carrier phase-based relative positioning with a small number of satellites in view, this paper introduces a novel GNSS carrier phase-based precise relative positioning method that uses a fixed baseline length as well as heading measurements in the beginning of the operation, which allows the fixing of integer ambiguities with rounding schemes in a short time. The integer rounding scheme developed in this paper is an iterative process that sequentially resolves integer ambiguities, and the sequential order of the integer ambiguity resolution is based on the required averaging epochs that vary for each satellite depending on the geometry between the baseline and the double difference line-of-sight vectors. The required averaging epochs with respect to various baseline lengths and heading measurement uncertainties were analyzed through simulations. Static and dynamic field tests with low cost GNSS receivers confirmed that the positioning accuracy of the proposed method was better than 10 cm and significantly outperformed a conventional RTK solution in a GNSS harsh environment.

Most conventional path generation algorithms search for an optimal path that avoids collisions with obstacles under the constraint of platforms' kino-dynamics. These conventional algorithms usually assume that a user position and obstacle locations are accurately known at any point in navigation environments. However, in a positioning network, the accuracy of a position estimate varies depending on, e.g., the ranging accuracy, network geometry, multipath error, and signal blockages which may lead to unexpected situations, including collision and low efficiency path planning. Therefore, positioning accuracy must be considered in path generation to ensure a reliable navigation capability and collision avoidance. To consider positioning accuracy in path planning, the proposed method in this paper uses a mixture of potential and positioning risk fields that generates a hybrid directional flow to guide an unmanned vehicle (UV) in a safe and efficient path. The results of simulations showed that the proposed method generated successful paths for around 90% percent of the tested routes, while using only the potential field method failed for around 50%. To demonstrate the effectiveness of the proposed local hybrid path planning method, we perform an experiment using a small-size quadcopter, and the results are analyzed and discussed.

This paper investigates the feasibility of the distance measuring equipment (DME)-based alternative position, navigation, and timing architecture using the recent advances on DME/N (normal) signal processing techniques; an improved DME/N pulse waveform and learning-based multipath mitigation algorithm. This paper evaluates the achievable DME range accuracy by using the advanced signal processing techniques, and provides the analysis on the required augmentation of ground DME stations in a selected test region in contiguous United States.

Although Unmanned Aircraft Systems (UAS) have become popular, the auto land of a fixed wing UAS has still remained as a significant challenge. This paper presents a UAS auto landing system based on a Ultra Wide Band (UWB) positioning network. The geometry of the UWB anchors in the network is optimized to provide precise positioning accuracy during the course of UAS landing. The notable performance characteristics of the system is that the positioning of the UAS becomes more accurate as it approaches to the runway more closely. At the point of a landing flare, the landing system is expected to provide vertical positioning accuracy better than 20 cm in 95 percent of time. The paper discusses the methodology of designing the proposed UWB positioning network architecture and the positioning performance analysis through simulations.

The current autonomous navigation of unmanned aircraft systems (UAS) heavily depends on Global Navigation Satellite Systems (GNSS). However, in challenging environments, such as deep urban areas, GNSS signals can be easily interrupted, so that UAS may lose navigation capability at any instant. For urban positioning and navigation, Long Term Evolution (LTE) has been considered a promising signal of opportunity due to its dense network in urban areas, and there has recently been great advancement in LTE positioning technology. However, the current LTE positioning accuracy is found to be insufficient for safe UAS navigation in deep urban areas. This paper evaluates the positioning performance of the current network of LTE base stations in a selected deep urban area and investigates the effectiveness of LTE augmentations using dedicated short range communication (DSRC) transceivers through the optimization of the ground LTE/DSRC network and cooperative positioning among UAS. The analysis results based on simulation using an urban canyon model and signal line of sight propagations show that the addition of four or five DSRC transceivers to the existing LTE base station network could provide better than 4&ndash, 6 m horizontal positioning accuracy (95%) in the selected urban canyon at a position of 150 ft above the ground, while a dense LTE network alone may result in a 15&ndash, 20 m horizontal positioning error. Additionally, the simulation results of cooperative positioning with inter-UAS ranging measurements in the DSRC augmented LTE network were shown to provide horizontal positioning accuracy better than 1 m in most flight space, assuming negligible time-synchronization errors in inter-UAS ranging measurements.

The SFOL pulse is a high accuracy DME/N pulse developed from using Genetic Algorithms. This pulse complies with the current DME/N specifications and is significantly less susceptible to multipaths than previous DME pulses. Recent analysis of the SFOL showed that the multipath-induced ranging error of the SFOL pulse was five times and two and half times less than the conventional Gaussian and Smoothed Concave Polygon pulses. To implement DMEs transmitting the SFOL, first, it would be desirable if modern DMEs currently deployed in the field can be modified to transmit the SFOL pulse without significant changes. It is expected that the biggest modification is required in the pulse shaping process. Currently, we are investigating a pre-distortion of the SFOL pulse for the typical power amplifier of a DME designed to transmit Gaussian pulses. A successful development of the pre-distortion may enable Gaussian pulse-based DMEs to transmit the SFOL pulse with relatively little changes. Second, the terrain in South Korea consists of numerous high mountains that would make it difficult to plan effective DME/DME networks due to the limited line of sights between DMEs and aircraft. Considering the airspace and major airport locations in South Korea, we are developing search algorithms that will result in cost effective DME/DME network layouts in the difficult terrain conditions. The paper will introduce a promising pre-distortion of the SFOL pulse and a strategy in planning of optimal DME/DME networks in South Korea with a recommended network layout.

The FAA's recently announced 2016 Performance Based Navigation (PBN) National Airspace System (NAS) Navigation Strategy states that it will retain and expand Distance Measuring Equipment (DME/N) infrastructure to help ensure continued Area Navigation (RNAV) service during Global Navigation Satellite Systems (GNSS) outages. The targeted navigation performance using DME/DME in this strategy is RNAV 2.0 in the En Route Domain without requiring Inertial Reference Unit (IRU) and RNAV 1.0 in some large Terminal Areas. It is expected that DME will still play an important role as an alternative RNAV navigation source beyond 2030. It is, therefore, desirable to determine if the performance of DME can be improved to enable PBN of higher navigation accuracy to better meet future air traffic needs. This paper investigates the benefit of a newly developed DME/N pulse using Genetic Algorithms (GA) that can provide much higher ranging accuracy than the conventional Gaussian or Smoothed Concave Polygon (SCP) pulse while meeting the pulse shape requirements in current DME specifications. The primary benefit analysis will compare the achievable DME/DME positioning accuracy with a current DME ground network and compare the DME ground network requirements needed to meet RNAV 0.3 and 92.6 m surveillance positioning accuracy using the conventional Gaussian and the GA-based pulses in selected areas in Conterminous US (CONUS) NAS.

The Hatch filter is a code-smoothing technique that uses the variation of the carrier phase. It can effectively reduce the noise of a pseudo-range with a very simple filter construction, but it occasionally causes an ionosphere-induced error for low-lying satellites. Herein, we propose an optimal single-frequency (SF) divergence-free Hatch filter that uses a satellite-based augmentation system (SBAS) message to reduce the ionospheric divergence and applies the optimal smoothing constant for its smoothing window width. According to the data-processing results, the overall performance of the proposed filter is comparable to that of the dual frequency (DF) divergence-free Hatch filter. Moreover, it can reduce the horizontal error of 57 cm to 37 cm and improve the vertical accuracy of the conventional Hatch filter by 25%. Considering that SF receivers dominate the global navigation satellite system (GNSS) market and that most of these receivers include the SBAS function, the filter suggested in this paper is of great value in that it can make the differential GPS (DGPS) performance of the low-cost SF receivers comparable to that of DF receivers.

Global navigation satellite systems (GNSS) have become a primary navigation means for aircraft. However, the signal power of GNSS is very weak, and its service can be disrupted at any time when there is interference or jamming. For this reason, the Federal Aviation Administration (FAA) in the United States has recently chosen a distance measuring equipment (DME)-based aircraft navigation technique, called DME/DME, as an alternative aircraft navigation means for use by around 2030. The reason that the FAA plans to use DME/DME in such a short duration, by around 2030, is presumed to be because the ranging accuracy of DMEs is between 70 to 300 m, which is about 7 to 30 times worse than that of GNSS. Thus, a significant loss of positioning performance is unavoidable with current DMEs. To make DME/DME a more competent alternative positioning source, this paper proposes an advanced DME that could provide a ranging accuracy of around 30 m by employing a recently developed Stretched-Front-Leg (SFOL) pulse. The paper introduces optimal ground station augmentation algorithms that help to efficiently transform the current DME ground network to enable a DME/DME positioning accuracy of up to 0.3 nm or 92.6 m with a minimal number of new ground DME sites. The positioning performance and augmented ground network using the proposed SFOL pulse-based DME are evaluated in two regions which have distinct terrain conditions.