Signal authentication and integrity schemes for next generation global navigation satellite systems

This paper describes a number of techniques for GNSS navigation message authentication. A detailed analysis of the security facilitated by navigation message authentication is given. The analysis takes into consideration the risk of critical applications that rely on GPS including transportation, finance and telecommunication networks. We propose a number of cryptographic authentication schemes for navigation data authentication. These authentication schemes provide authenticity and integrity of the navigation data to the receiver. Through software simulation, the performance of the schemes is quantified. The use of software simulation enables the collection of authentication performance data of different data channels, and the impact of various schemes on the infrastructure and receiver. Navigation message authentication schemes have been simulated at the proposed data rates of Galileo and GPS services, for which the resulting performance data is presented. This paper concludes by making recommendations for optimal implementation of navigation message authentication for Galileo and next generation GPS systems.

Attitude observability of a loosely-coupled GPS/Visual Odometry Integrated Navigation Filter

We present a novel method for integrating GPS position estimates with position and attitude estimates derived from visual odometry using a scheme similar to a classic loosely-coupled GPS/INS integration. Under such an arrangement, we derive the error dynamics of the system and develop a Kalman Filter for estimating the errors in position and attitude. Using a control-based approach to observability, we show that the errors in both position and attitude (including yaw) are fully observable when there is a component of acceleration perpendicular to the velocity vector in the navigation frame. Numerical simulations are performed to confirm the observability analysis.

Autonomous aerial navigation and tracking of marine animals

In this paper, we describe the development of an independent and on-board visual servoing system which allows a computationally impoverished aerial vehicle to autonomously identify and track a moving surface target. Our image segmentation and target identification algorithms were developed with the specific task of monitoring whales at sea but could be adapted for other targets. Observing whales is important for many marine biology tasks and is currently performed manually from the shore or from boats. We also present hardware experiments which demonstrate the capabilities of our algorithms for object identification and tracking that enable a flying vehicle to track a moving target.

A two week persistent navigation and mapping experiment using RatSLAM : insights and current developments

One of the major challenges in achieving long term robot autonomy is the need for a SLAM algorithm that can perform SLAM over the operational lifetime of the robot, preferably without human intervention or supervision. In this paper we present insights gained from a two week long persistent SLAM experiment, in which a Pioneer robot performed mock deliveries in a busy office environment. We used the biologically inspired visual SLAM system, RatSLAM, combined with a hybrid control architecture that selected between exploring the environment, performing deliveries, and recharging. The robot performed more than a thousand successful deliveries with only one failure (from which it recovered), travelled more than 40 km over 37 hours of active operation, and recharged autonomously 23 times. We discuss several issues arising from the success (and limitations) of this experiment and two subsequent avenues of work.

Modeling perceived collision risk in port water navigation

An increase in the likelihood of navigational collisions in port waters has put focus on the collision avoidance process in port traffic safety. The most widely used on-board collision avoidance system is the automatic radar plotting aid which is a passive warning system that triggers an alert based on the pilot’s pre-defined indicators of distance and time proximities at the closest point of approaches in encounters with nearby vessels. To better help pilot in decision making in close quarter situations, collision risk should be considered as a continuous monotonic function of the proximities and risk perception should be considered probabilistically. This paper derives an ordered probit regression model to study perceived collision risks. To illustrate the procedure, the risks perceived by Singapore port pilots were obtained to calibrate the regression model. The results demonstrate that a framework based on the probabilistic risk assessment model can be used to give a better understanding of collision risk and to define a more appropriate level of evasive actions.

Towards persistent indoor appearance-based localization, mapping and navigation using CAT-Graph

The challenge of persistent appearance-based navigation and mapping is to develop an autonomous robotic vision system that can simultaneously localize, map and navigate over the lifetime of the robot. However, the computation time and memory requirements of current appearance-based methods typically scale not only with the size of the environment but also with the operation time of the platform; also, repeated revisits to locations will develop multiple competing representations which reduce recall performance. In this paper we present a solution to the persistent localization, mapping and global path planning problem in the context of a delivery robot in an office environment over a one-week period. Using a graphical appearance-based SLAM algorithm, CAT-Graph, we demonstrate constant time and memory loop closure detection with minimal degradation during repeated revisits to locations, along with topological path planning that improves over time without using a global metric representation. We compare the localization performance of CAT-Graph to openFABMAP, an appearance-only SLAM algorithm, and the path planning performance to occupancy-grid based metric SLAM. We discuss the limitations of the algorithm with regard to environment change over time and illustrate how the topological graph representation can be coupled with local movement behaviors for persistent autonomous robot navigation.

Image Region Salience for Improving Appearance-Based Place Recognition using a Supervised Classifier System

Many state of the art vision-based Simultaneous Localisation And Mapping (SLAM) and place recognition systems compute the salience of visual features in their environment. As computing salience can be problematic in radically changing environments new low resolution feature-less systems have been introduced, such as SeqSLAM, all of which consider the whole image. In this paper, we implement a supervised classifier system (UCS) to learn the salience of image regions for place recognition by feature-less systems. SeqSLAM only slightly benefits from the results of training, on the challenging real world Eynsham dataset, as it already appears to filter less useful regions of a panoramic image. However, when recognition is limited to specific image regions performance improves by more than an order of magnitude by utilising the learnt image region saliency. We then investigate whether the region salience generated from the Eynsham dataset generalizes to another car-based dataset using a perspective camera. The results suggest the general applicability of an image region salience mask for optimizing route-based navigation applications.

The individual and interactive relationship between long chain omega-3 polyunsaturated fatty acids and physical activity as predictors of cognition in cognitively impaired and non-impaired older adults

Alterations in cognitive function are characteristic of the aging process in humans and other animals. However, the nature of these age related changes in cognition is complex and is likely to be influenced by interactions between genetic predispositions and environmental factors resulting in dynamic fluctuations within and between individuals. These inter and intra-individual fluctuations are evident in both so-called normal cognitive aging and at the onset of cognitive pathology. Mild Cognitive Impairment (MCI), thought to be a prodromal phase of dementia, represents perhaps the final opportunity to mitigate cognitive declines that may lead to terminal conditions such as dementia. The prognosis for people with MCI is mixed with the evidence suggesting that many will remain stable within 10-years of diagnosis, many will improve, and many will transition to dementia. If the characteristics of people who do not progress to dementia from MCI can be identified and replicated in others it may be possible to reduce or delay dementia onset, thus reducing a growing personal and public health burden. Furthermore, if MCI onset can be prevented or delayed, the burden of cognitive decline in aging populations worldwide may be reduced. A cognitive domain that is sensitive to the effects of advancing age, and declines in which have been shown to presage the onset of dementia in MCI patients, is executive function. Moreover, environmental factors such as diet and physical activity have been shown to affect performance on tests of executive function. For example, improvements in executive function have been demonstrated as a result of increased aerobic and anaerobic physical activity and, although the evidence is not as strong, findings from dietary interventions suggest certain nutrients may preserve or improve executive functions in old age. These encouraging findings have been demonstrated in older adults with MCI and their non-impaired peers. However, there are some gaps in the literature that need to be addressed. For example, little is known about the effect on cognition of an interaction between diet and physical activity. Both are important contributors to health and wellbeing, and a growing body of evidence attests to their importance in mental and cognitive health in aging individuals. Yet physical activity and diet are rarely considered together in the context of cognitive function. There is also little known about potential underlying biological mechanisms that might explain the physical activity/diet/cognition relationship. The first aim of this program of research was to examine the individual and interactive role of physical activity and diet, specifically long chain polyunsaturated fatty acid consumption(LCn3) as predictors of MCI status. The second aim is to examine executive function in MCI in the context of the individual and interactive effects of physical activity and LCn3.. A third aim was to explore the role of immune and endocrine system biomarkers as possible mediators in the relationship between LCn3, physical activity and cognition. Study 1a was a cross-sectional analysis of MCI status as a function of erythrocyte proportions of an interaction between physical activity and LCn3. The marine based LCn3s eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have both received support in the literature as having cognitive benefits, although comparisons of the relative benefits of EPA or DHA, particularly in relation to the aetiology of MCI, are rare. Furthermore, a limited amount of research has examined the cognitive benefits of physical activity in terms of MCI onset. No studies have examined the potential interactive benefits of physical activity and either EPA or DHA. Eighty-four male and female adults aged 65 to 87 years, 50 with MCI and 34 without, participated in Study 1a. A logistic binary regression was conducted with MCI status as a dependent variable, and the individual and interactive relationships between physical activity and either EPA or DHA as predictors. Physical activity was measured using a questionnaire and specific physical activity categories were weighted according to the metabolic equivalents (METs) of each activity to create a physical activity intensity index (PAI). A significant relationship was identified between MCI outcome and the interaction between the PAI and EPA; participants with a higher PAI and higher erythrocyte proportions of EPA were more likely to be classified as non-MCI than their less active peers with less EPA. Study 1b was a randomised control trial using the participants from Study 1a who were identified with MCI. Given the importance of executive function as a determinant of progression to more severe forms of cognitive impairment and dementia, Study 1b aimed to examine the individual and interactive effect of physical activity and supplementation with either EPA or DHA on executive function in a sample of older adults with MCI. Fifty male and female participants were randomly allocated to supplementation groups to receive 6-months of supplementation with EPA, or DHA, or linoleic acid (LA), a long chain polyunsaturated omega-6 fatty acid not known for its cognitive enhancing properties. Physical activity was measured using the PAI from Study 1a at baseline and follow-up. Executive function was measured using five tests thought to measure different executive function domains. Erythrocyte proportions of EPA and DHA were higher at follow-up; however, PAI was not significantly different. There was also a significant improvement in three of the five executive function tests at follow-up. However, regression analyses revealed that none of the variance in executive function at follow-up was predicted by EPA, DHA, PAI, the EPA by PAI interaction, or the DHA by PAI interaction. The absence of an effect may be due to a small sample resulting in limited power to find an effect, the lack of change in physical activity over time in terms of volume and/or intensity, or a combination of both reduced power and no change in physical activity. Study 2a was a cross-sectional study using cognitively unimpaired older adults to examine the individual and interactive effects of LCn3 and PAI on executive function. Several possible explanations for the absence of an effect were identified. From this consideration of alternative explanations it was hypothesised that post-onset interventions with LCn3 either alone or in interation with self-reported physical activity may not be beneficial in MCI. Thus executive function responses to the individual and interactive effects of physical activity and LCn3 were examined in a sample of older male and female adults without cognitive impairment (n = 50). A further aim of study 2a was to operationalise executive function using principal components analysis (PCA) of several executive function tests. This approach was used firstly as a data reduction technique to overcome the task impurity problem, and secondly to examine the executive function structure of the sample for evidence of de-differentiation. Two executive function components were identified as a result of the PCA (EF 1 and EF 2). However, EPA, DHA, the PAI, or the EPA by PAI or DHA by PAI interactions did not account for any variance in the executive function components in subsequent hierarchical multiple regressions. Study 2b was an exploratory correlational study designed to explore the possibility that immune and endocrine system biomarkers may act as mediators of the relationship between LCn3, PAI, the interaction between LCn3 and PAI, and executive functions. Insulin-like growth factor-1 (IGF-1), an endocrine system growth hormone, and interleukin-6 (IL-6) an immune system cytokine involved in the acute inflammatory response, have both been shown to affect cognition including executive functions. Moreover, IGF-1 and IL-6 have been shown to be antithetical in so far as chronically increased IL-6 has been associated with reduced IGF-1 levels, a relationship that has been linked to age related morbidity. Further, physical activity and LCn3 have been shown to modulate levels of both IGF-1 and IL-6. Thus, it is possible that the cognitive enhancing effects of LCn3, physical activity or their interaction are mediated by changes in the balance between IL-6 and IGF-1. Partial and non-parametric correlations were conducted in a subsample of participants from Study 2a (n = 13) to explore these relationships. Correlations of interest did not reach significance; however, the coefficients were quite large for several relationships suggesting studies with larger samples may be warranted. In summary, the current program of research found some evidence supporting an interaction between EPA, not DHA, and higher energy expenditure via physical activity in differentiating between older adults with and without MCI. However, a RCT examining executive function in older adults with MCI found no support for increasing EPA or DHA while maintaining current levels of energy expenditure. Furthermore, a cross-sectional study examining executive function in older adults without MCI found no support for better executive function performance as a function of increased EPA or DHA consumption, greater energy expenditure via physical activity or an interaction between physical activity and either EPA or DHA. Finally, an examination of endocrine and immune system biomarkers revealed promising relationships in terms of executive function in non-MCI older adults particularly with respect to LCn3 and physical activity. Taken together, these findings demonstrate a potential benefit of increasing physical activity and LCn3 consumption, particularly EPA, in mitigating the risk of developing MCI. In contrast, no support was found for a benefit to executive function as a result of increased physical activity, LCn3 consumption or an interaction between physical activity and LCn3, in participants with and without MCI. These results are discussed with reference to previous findings in the literature including possible limitations and opportunities for future research.

Towards persistent visual navigation using SMART

In this paper, we present SMART (Sequence Matching Across Route Traversals): a vision- based place recognition system that uses whole image matching techniques and odometry information to improve the precision-recall performance, latency and general applicability of the SeqSLAM algorithm. We evaluate the system���s performance on challenging day and night journeys over several kilometres at widely varying vehicle velocities from 0 to 60 km/h, compare performance to the current state-of- the-art SeqSLAM algorithm, and provide parameter studies that evaluate the effectiveness of each system component. Using 30-metre sequences, SMART achieves place recognition performance of 81% recall at 100% precision, outperforming SeqSLAM, and is robust to significant degradations in odometry.

Designing mobile systems for social navigation in urban public places

This thesis presents social requirements and design considerations from a study evaluating interactive approaches to social navigation and user-generated information sharing in urban environments using mobile devices. It investigates innovative ways to leverage mobile information and communication technology in order to provide a social navigation platform for residents and visitors in and for public urban places. Through a design case study this work presents CityFlocks, a mobile information system that offers an easy way for information-seeking new residents or visitors to access tacit knowledge from local people about their new community. It is intended to enable visitors and new residents in a city to tap into the knowledge and experiences of local residents in order to gather information about their new environment. Its design specifically aims to lower existing barriers of access and facilitate social navigation in urban places. In various user tests it evaluates two general user interaction alternatives – direct and indirect social navigation – and analyses which interaction method works better for people using a mobile device to socially navigate urban environments. The outcomes are relevant for the user interaction design of future mobile information systems that leverage the social navigation approach.

Rodent Scope: A User-Configurable Digital Wireless Telemetry System for Freely Behaving Animals

This paper describes the design and implementation of a wireless neural telemetry system that enables new experimental paradigms, such as neural recordings during rodent navigation in large outdoor environments. RoSco, short for Rodent Scope, is a small lightweight user-configurable module suitable for digital wireless recording from freely behaving small animals. Due to the digital transmission technology, RoSco has advantages over most other wireless modules of noise immunity and online user-configurable settings. RoSco digitally transmits entire neural waveforms for 14 of 16 channels at 20 kHz with 8-bit encoding which are streamed to the PC as standard USB audio packets. Up to 31 RoSco wireless modules can coexist in the same environment on non-overlapping independent channels. The design has spatial diversity reception via two antennas, which makes wireless communication resilient to fading and obstacles. In comparison with most existing wireless systems, this system has online user-selectable independent gain control of each channel in 8 factors from 500 to 32,000 times, two selectable ground references from a subset of channels, selectable channel grounding to disable noisy electrodes, and selectable bandwidth suitable for action potentials (300 Hz–3 kHz) and low frequency field potentials (4 Hz–3 kHz). Indoor and outdoor recordings taken from freely behaving rodents are shown to be comparable to a commercial wired system in sorting for neural populations. The module has low input referred noise, battery life of 1.5 hours and transmission losses of 0.1% up to a range of 10 m.

Air navigation services in Australia and the United States : a comparative case study

The central document governing the global organization of Air Navigation Services (ANS) is the Convention on International Civil Aviation, commonly referred to as the “Chicago Convention,” whose original version was signed in that city in 1944. In the Convention, Contracting States agreed to ensure the minimum standards of ANS established by ICAO, a specialized United Nations agency created by the Convention. Emanating from obligations under the Chicago Convention, ANS has traditionally provided by departments of national governments. However, there is a widespread trend toward transferring delivery of ANS services outside of line departments of national governments to independent agencies or corporations. The Civil Air Navigation Services Organisation (CANSO), which is the trade association for independent ANS providers, currently counts approximately 60 members, and is steadily growing. However, whatever delivery mechanisms are chosen, national governments remain ultimately responsible for ensuring that adequate ANS services are available. The provision by governments of ANS reflects the responsibility of the state for safety, international relations, and indirectly, the macroeconomic benefits of ensuring a sound infrastructure for aviation. ANS is a “public good” and an “essential good” provided to all aircraft using a country’s airfields and airspace. However, ANS also represents a service that directly benefits only a limited number of users, notably aircraft owners and operators. The idea that the users of the system, rather than the taxpaying public, should incur the costs associated with ANS provision is inherent in the commercialization process. However, ICAO sets out broad principles for the establishment of user charges, which member states are expected to comply with. ICAO states that only distance flown and aircraft weights are acceptable parameters for use in a charging system. These two factors are considered to be easy to measure, bear a reasonable relationship to the value of service received, and do not discriminate due to factors such as where the flight originated or the nation of aircraft registration.

Using performance-based evaluation to close the loop between biological and robotic navigation

In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.

Aircraft dynamic navigation for unmanned aerial vehicles

This thesis describes the investigation of an Aircraft Dynamic Navigation (ADN) approach, which incorporates an Aircraft Dynamic Model (ADM) directly into the navigation filter of a fixed-wing aircraft or UAV. The result is a novel approach that offers both performance improvements and increased reliability during short-term GPS outages. This is important in allowing future UAVs to achieve routine, unconstrained, and safe operations in commercial environments. The primary contribution of this research is the formulation Unscented Kalman Filter (UKF) which incorporates a complex, non-linear, laterally and longitudinally coupled, ADM, and sensor suite consisting of a Global Positioning System (GPS) receiver, Inertial Measurement Unit (IMU), Electronic Compass (EC), and Air Data (AD) Pitot Static System.

High-frequency global navigation satellite system���s receivers for airborne gravimetry

The development of global navigation satellite systems (GNSS) provides a solution of many applied problems with increasingly higher quality and accuracy nowadays. Researches that are carried out by the Bavarian Academy of Sciences and Humanities in Munich (BAW) in the field of airborne gravimetry are based on sophisticated data processing from high frequency GNSS receiver for kinematic aircraft positioning. Applied algorithms for inertial acceleration determination are based on the high sampling rate (50Hz) and on reducing of such factors as ionosphere scintillation and multipath at aircraft /antenna near field effects. The quality of the GNSS derived kinematic height are studied also by intercomparison with lift height variations collected by a precise high sampling rate vertical scale [1]. This work is aimed at the ways of more accurate determination of mini-aircraft altitude by means of high frequency GNSS receivers, in particular by considering their dynamic behaviour.