Electronic Version

Modern smartphones contain a number of sensors that can be used for navigation when GPS signals are unavailable. Low cost MEMS gyros and accelerometers are increasingly becoming available in modern devices, however when used for positioning, they typically result in large errors after very short periods of time. This paper investigates using measurements from a computer vision algorithm that uses successive frames from a camera approximately looking at the ground to compute the translation between frames. The measurements can be used to control the drift of inertial sensor measurements when measurements from GPS are not available. The concept is convenient since it uses sensors already available on smartphones and pedestrians will naturally hold the smartphone in the required position when using it for navigation. This paper demonstrates that computer vision measurements can significantly reduce the drift of inertial-only positioning for pedestrian navigation in areas where GPS is unavailable. Issues such as computational requirements and operation in low light areas are also discussed.

In an effort to supplement the available satelite-basedpositioning technology and extend such high levelpositioning capability to GPS-denied environments, amethod of vision-based positioning with the use of singlecamera and newly defined 3D maps is proposed. Besides,only natural landmarks are required in the proposedmethod. Absolute position and orientation informationcan be provided in six degree of freedom. Our work hereis to address the accuracy and reliability concerns of sucha vision-based navigation system. The main contributionwill be the newly defined 3D map and the adoption ofphotogrammetric 6DOF pose estimation method toimprove positioning accuracy. Dilution of Precisions(DOPs) are introduced to evaluate positioning precisionwithin the vision-based positioning domain. Qualitycontrol strategies are also applied to detect outliers in theobservation and strengthen system reliability.

In an effort to supplement the available satelite-basedpositioning technology and extend such high levelpositioning capability to GPS-denied environments, amethod of vision-based positioning with the use of singlecamera and newly defined 3D maps is proposed. Besides,only natural landmarks are required in the proposedmethod. Absolute position and orientation informationcan be provided in six degree of freedom. Our work hereis to address the accuracy and reliability concerns of sucha vision-based navigation system. The main contributionwill be the newly defined 3D map and the adoption ofphotogrammetric 6DOF pose estimation method toimprove positioning accuracy. Dilution of Precisions(DOPs) are introduced to evaluate positioning precisionwithin the vision-based positioning domain. Qualitycontrol strategies are also applied to detect outliers in theobservation and strengthen system reliability.

This paper proposes an integration of ‘building heading’ information with ZUPT in a Kalman filter, using a shoe mounted IMU approach. This is done to reduce heading drift error, which remains a major problem in a standalone shoe mounted pedestrian navigation system. The standalone system used in this paper consists of only single low cost MEMS IMU that contains 3-axis accelerometers and gyros. Several trials represented by regular and irregular walking trials were undertaken inside typical public buildings. The results were then compared with HSGPS solution and IMU+ZUPT only solution. Based on these trials, an average return position error of below 5 m was consistently achieved for an average time of 24 minutes – at times as long as 40 minutes - using only a low cost MEMS IMU.

Navigation applications and location-based services are currently becoming standard features in smart phones with built-in GPS receivers. However, a ubiquitous navigation solution which locates a mobile user anytime anywhere is still not available, especially in Global Navigation Satellite System (GNSS) degraded and denied environments. Different motion sensors and angular sensors have been adopted for augmenting the positioning solutions for such environments. An electromyography (EMG) sensor, which measures electrical potentials generated by muscle contractions from human body, is employed in this paper to detect the muscle activities during human locomotion and captures the human walking dynamics for motion recognition and step detection in a Pedestrian Dead Reckoning (PDR) solution. The work presented in this paper is a consecutive step of our pilot studies in developing a novel and robust PDR solution using wearable EMG sensors. The PDR solution includes standing and walking identification, step detection, stride length estimation, and a position calculation with a heading angular sensor. A situation of standing still is identified from the EMG signals collected from a walking process, which has standing and walking dynamics, via a hidden Markov model classifier fed by sample entropy features. Such pre-classified processing reduces the misdetection rate of step detection. After step detection, two stride length estimation methods are investigated for the PDR solution. Firstly, a linear stride length estimation method based on statistic models is investigated to improve the accuracy of the PDR solution. Secondly, five different walking motions are recognized by a motion recognition algorithm based on some particular EMG features, and a fixed stride length is then set for each walking motion to propagate the position. To validate the effectiveness and practicability of the methods mentioned above, some field tests were conducted by a few testers. The test results indicate that the performance of the proposed PDR solution is comparable to that of a commercial GPS receiver in outdoor test under an open-sky environment.

Wireless Sensor Networks (WSNs) consist of densely deployed, independent, and collaborating low cost sensor nodes. The nodes are highly resource-constrained in terms of energy, processing, and data storage capacity. Thus, the protocols used in WSNs must be highly energy-efficient. WSN communication protocols achieving the lowest power consumption minimize radio usage by accurately synchronizing transmissions and receptions with their neighbors. In this paper, we show how network signaling frames of state-of-the-art synchronized communication protocols for low-power WSNs supporting mobile nodes can be used for positioning. We derive mathematical models for node power consumption analysis. Both centralized and distributed positioning architectures are modeled. The models provide a tool for estimating what kind of network lifetimes can be expected when average positioned node speed, the amount of anchor nodes required by the location estimation algorithm, and the location refresh rate required by the application are known. The presented analysis results are based on two kinds of node hardware: with and without Received Signal Strength Indicator (RSSI). The results show that the positioning parameters and used hardware have significant impact on node power consumption and network lifetime. In the presented results, the network lifetime ranges from over 10 years to 2 months with different positioning requirements and hardware.

Ad hoc solutions for positioning and tracking of emergency response teams is an important and safety-critical challenge. The solutions based on inertial sensing systems are promising, but are subject to drift. Based on a brief characterization of the errors encountered in inertial-based dead reckoning estimates, we propose a solution based on a combination of foot-mounted inertial sensors and ultrasound beacons deployed as landmarks in an ad hoc fashion. This paper targets two important aspects within the context of providing positioning service for emergency responders namely on how to locate the deployed static beacons (using multidimensional scaling), and on how to track the responders by using a combination of ultrasound and inertial measurements (using a Kalman filter). We perform evaluation of both the ultrasonic beacon localization and tracking algorithm for data collected from real deployments for different trail topologies and our presented algorithms are benchmarked against an ultra-wideband (UWB) precision location system. Our approach of preventing the drift in inertial estimates by combining with ultrasound measurements are promising and offers a viable solution to providing positioning and tracking support to emergency responders.

There are many applications which require continuous positioning in combined outdoor urban and indoor environments. For a long time GNSS has been used in outdoor environments while indoor positioning is still a challenging task. One of the major degradations that GNSS receivers experience indoors is the presence of multipath. The current paper analyzes several available multipath mitigation techniques which would be suitable for indoor applications. Some of these techniques are described in more details. A few deconvolution based techniques such as the Projection Onto Convex Sets and the Deconvolution Approach are focused on and some tests are performed to show how they work. It is shown which advantages these techniques have over the conventional techniques. The wide range of tests show how these techniques work under ideal conditions, with simulated signals in different environments and in real world using data from high-end GNSS front-end.

The Minimal Detectable Bias method of Fault Detection is frequently employed to determine if a position has integrity. However, to provide integrity the Type I error probability of the statistical tests is required to be preset. Normally, this probability is set to avoid the unnecessary rejection of measurements or to satisfy the continuity requirements. In this paper, the Type I error probability is set based on the integrity requirements by initially setting the Protection Levels equal to the Alert Limit. This new procedure of setting the Type I error probability is compared with the more conventional approach when there are different continuity requirements and when multiple biases are considered. From the results of this comparison, it is concluded that the new procedure increases the availability rates regardless of the continuity requirements and the number of biases considered.