Pedestrian navigation in outdoor environments where global navigation satellite systems (GNSS) are unavailable is a challenging problem. Existing technologies that have attempted to address this problemoften require external reference signals or specialized hardware, the extra size,weight, power, and cost of which are unsuitable for many applications. This article presents a real-time, self-contained outdoor navigation application that uses only the existing sensors on a smartphone in conjunction with a preloaded digital elevation map. The core algorithm implements a particle filter, which fuses sensor data with a stochastic pedestrian motion model to predict the user’s position. The smartphone’s barometric elevation is then compared with the elevation map to constrain the position estimate. The system developed for this research was deployed on Android smartphones and tested in several terrains using a variety of elevation data sources. The results fromthese experiments showthe systemachieves positioning accuracies in the tens of meters that do not grow as a function of time

The global positioning system (GPS) generally provides worldwide high-accuracy positioning. However, GPS requires lines of sight to multiple satellites and may be blocked or jammed, hence backup navigation techniques are of interest. Navigation via signals of opportunity uses existing radio infrastructure as ad hoc navigational beacons. A mobile receiver determines its position by computing a time difference of arrival (TDOA) between signal reception time at the mobile and at a reference receiver. The drawback is that this requires communication between the reference and mobile receivers. In this paper, we show that multicarrier modulation is an ideal candidate for a navigation signal of opportunity. We show that communication between the reference and mobile can be very minimal for multicarrier modulation compared to other modulation types, since the block structure inherently aids synchronization of the two received signals. Simulations are used to quantify the performance of the TDOA estimate as a function of the SNR and the bandwidth between the reference and the mobile.

This paper describes the design and testing of a high-speed, real-time kinematic, precise differential GPS positioning system for use in airborne applications such as automated aerial-refueling and close formation flying. Many of the current ambiguity resolution techniques use the residuals from the least squares position estimation to determine the true ambiguity set, this paper presents a novel approach to the ambiguity resolution problem, called the minimum indicator. Instead of assuming the ambiguity set with the lowest residuals is the true set, other special characteristics of the residuals are examined. The result was the first-ever successful six-degree of freedom, in-flight demonstration of close formation flight, culminating in over 11 hours of close formation flying with a mean radial spherical error of 3.3 centimeters. Other areas addressed include: the difference between "pre-fit" and "post-fit" residuals in the conditional probability calculation, and the impact of a simplified dynamics model on system performance.