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The Advanced Receiver Autonomous Integrity Monitoring (ARAIM) provides an Aircraft‐Based Augmentation System function for aircraft Global Navigation Satellite System equipment. Currently, the consideration of temporal correlations of test statistics is an important update to the ARAIM baseline algorithm. However, due to the tight budgets of integrity and continuity, the updated ARAIM Fault Detection and Exclusion (FDE) is not satisfactory in availability coverage. The baseline algorithm is based on equal allocation of integrity and continuity, which causes ARAIM to be susceptible to faults and satellite outages. An availability optimisation of ARAIM FDE based on dynamic budget allocation is proposed, aiming to make full use of the prior knowledge provided by the Integrity Support Message (ISM). The contribution of each solution separation test in the ARAIM FDE to the total continuity and integrity risks is estimated, and the continuity and integrity allocation constraints are obtained. The impacts of faults and satellite outages on availability are analysed, and a predictive Protection Level (PL) for ARAIM FDE is proposed for use as an objective function for optimising risk allocation. Then, a risk allocation method based on the multiplier penalty function method is proposed. The performances of the baseline algorithm and the proposed method under the maximum Number of Effective Samples are simulated. For dual‐constellation H‐ARAIM, the optimised Horizontal PL (HPL) is 40% lower than that of the baseline algorithm on average, and the average number of critical satellites supporting RNP 0.3 is less than 1 worldwide. For the three‐constellation V‐ARIAM, the optimised HPL is 27% lower than that of the baseline algorithm on average, and the optimised Vertical PL (VPL) is 18% lower. The proposed method has high availability coverage and can better respond to the requirements for high‐performance navigation services. [ABSTRACT FROM AUTHOR]

A main challenge within inertial navigation systems involves attitude determination, which refers to the process of estimating the angles that define orientations. A new algorithm is presented to estimate a reliable and proper model for a low‐cost attitude and heading reference system (AHRS), while also, including long‐term global navigation satellite system (GNSS) outages with various dynamical manoeuvres. In the proposed approach, the initial AHRS model is continuously refined at each time step through the incorporation of complementary terms using a new prediction method. These complementary terms are determined using attitude information from the accelerometers output and the GNSS as reference systems. The proposed estimation technique undergoes mathematical analysis to ascertain stochastic stability and is further assessed through real‐world aerial experimental tests conducted with hardware‐in‐the‐loop mechanisation. The obtained results demonstrate a significant enhancement in the reliability and accuracy of the AHRS through the proposed estimation algorithm, even under GNSS blockages. The comparative results highlight the higher performance of the suggested data fusion scheme in providing a reliable and accurate model for the AHRS in normal conditions and assisting a powerful neural network‐based algorithm to provide reliable heading information even during long‐term GNSS outages under dynamical manoeuvres. [ABSTRACT FROM AUTHOR]

The authors propose an innovative solution to address challenges in terrain‐referenced navigation (TRN). The suggested solution is the interactive multiple‐model particle filter with a classification error minimisation strategy (IMM‐CPF) based on decision theory. TRN is a technique that estimates position by comparing measured terrain altitude to the digital elevation model and critically depends on obtaining accurate altitude measurements. However, these measurements can be easily contaminated to not only from sensor errors but also from vegetation effects. The TRN measurement noise model is characterised as a multi‐modal density, and it reveals an overlap between two density functions, with the mixture weight parameter varying based on surface environmental conditions. This variability can potentially degrade estimation accuracy. The proposed approach integrates truncated likelihoods into the mode estimation process to enhance mode estimation capability using a classification error minimisation strategy. The proposed strategy is based on decision theory and has been modified to be suited in the IMMPF form. The effectiveness of the proposed IMM‐CPF method is verified through simulations conducted under diverse surface conditions, demonstrating significant improvements in estimation accuracy compared to conventional algorithms. Furthermore, the significance of this method is presented in terms of computational cost and robustness. [ABSTRACT FROM AUTHOR]

An integrity monitoring of integrated navigation in the presence of slowly growing errors (SGEs) is proposed. SGEs with gradual growth over time are the worst category of latent failures. Tightly coupled inertial navigation system (INS)/Global Navigation Satellite System integration is presented by taking INS errors, bias and drift of receiver clock, baro‐altitude, pseudo‐range errors and ionospheric errors into consideration. Based on the RTCA performance standards DO‐229 and DO‐384, the simplified multi‐filters solution separation is employed for fault detection and calculation of corresponding outputs. For the fault exclusion part, the authors introduce a post pseudo‐range residual and measurement averaging method that is designed to quickly and effectively address SGEs and large measurement noises. Furthermore, the authors have designed a reconstruction logic for the filters that guarantees the continuity of the civil aviation system by considering the variation of visible satellites and historical information. The simulation results demonstrate that the proposed approach satisfies the performance requirements for civil aviation of En‐route and is able to correctly exclude faults and respond quickly in the presence of different levels of SGEs and measurement noises. [ABSTRACT FROM AUTHOR]

In laser-based space technologies where laser beams are transmitted from a ground station, it is required for the ground station to avoid irradiating aircraft with high energy lasers. A simple, inexpensive acoustic positioning technique using four microphones is developed and its performance is evaluated. It is demonstrated to be sensitive to and effective in detecting aircraft flying at short ranges. Aircraft closer than 5 km can easily be detected and the maximum range is about 10 km. The time series of two-dimensional directional position estimates are harmonic with those of ADS-B (Automatic Dependent Surveillance-Broadcast), and the precision reaches 1 degree (standard deviation) in the best case. The processing time for data collection and computation is short enough to establish a realtime feedback mechanism to stop firing laser. With its advantages and disadvantages, effective combinations with existing methods are discussed to avoid injury to the eyes, in which the acoustic approach is found to be useful to enhance safety measures in particular of low-altitude aircraft with a large angular velocity. [ABSTRACT FROM AUTHOR]

Scene matching plays a vital role in the visual positioning of aircraft. The position and orientation of aircraft can be determined by comparing acquired real-time imagery with reference imagery. To enhance precise scene matching during flight, it is imperative to conduct a comprehensive analysis of the reference imagery's matchability beforehand. Conventional approaches to image matchability analysis rely heavily on features that are manually designed. However, these features are inadequate in terms of comprehensiveness, efficiency, and taking into account the scene matching process, ultimately leading to unsatisfactory results. This paper innovatively proposes a core approach to quantifying matchability by utilizing scene information from imagery. The first proposal for generating image matchability samples through a simulation of the matching process has been developed. The RSPNet network architecture is designed to effectively leverage regional scene perception in order to accurately predict the matchability of reference imagery. This network comprises two core modules: saliency analysis and uniqueness analysis. The attention mechanism employed by saliency analysis module extracts features at different levels and scales, guaranteeing an accurate and meticulous quantification of image saliency. The uniqueness analysis module quantifies image uniqueness by comparing neighborhood scene features. The proposed method is compared with traditional and deep learning methods for experiments based on simulated datasets, respectively. The results demonstrate that RSPNet exhibits significant advantages in terms of accuracy and reliability. [ABSTRACT FROM AUTHOR]

This paper introduces a technique to transform between geometric and barometric estimates of altitude and vice-versa. Leveraging forecast numerical weather models, the method is unbiased and has a vertical error with a standard deviation of around 30 m (100 ft), regardless of aircraft altitude, which makes it significantly more precise than established comparable conversion functions. This result may find application in various domains of civil aviation, including vertical RNP, systemized airspace, and automatic landing systems. [ABSTRACT FROM AUTHOR]

The transport sector is experiencing a fast and revolutionary development, moving toward the deployment of autonomous vehicles. Thus, the accuracy of the position information and the integrity of the navigation system have become key factors. In this article, we address the problem of the enhancement of the integrity of the position provided by a global navigation satellite system receiver by exploiting sensor fusion. To this aim, we estimate the lateral offset and heading of the vehicle with respect to a georeferenced roadway centerline from the images supplied by an on-board camera. Moreover, we perform integrity monitoring based on the implementation of the solution separation in the parity space. The numerical results indicate that the use of sensor fusion and digital map allows us to attain a longitudinal protection level reduction with respect to the case in which sensor fusion is not exploited. More specifically, a decrease of about 70% is achieved when a single constellation is used, while reduction is less relevant, about 15%, when two constellations are employed. [ABSTRACT FROM AUTHOR]

Vehicle and airborne navigation users are facing more and more complex signal interference and even spoofing. If vehicles and aircraft do not strengthen their anti-spoofing ability, their navigation performance is bound to be adversely affected. global navigation satellite system (GNSS) spoofing technology has gradually become a preferred interference method for spoofer because of its high concealment and great harm. For spoofer, user terminal increasingly adopts GNSS with inertial measurement unit (IMU): tightly-coupled GNSS/IMU, on this basis, user also configures a variety of anti-spoofing techniques to effectively deal with spoofing. Even if spoofer slowly changes user's positioning, if spoofing strategy is unreasonable, it will lead to the violation of parameter rationality of coupled filter output parameters and spoofing observation, which greatly increases the difficulty of spoofing. In view of the above problems, from the perspective of spoofer, in order to effectively counter the non cooperative target of assembling tightly-coupled GNSS/IMU by using GNSS spoofing, this paper establishes GNSS spoofing mathematical model, and proposes a slowly varying spoofing algorithm to avoid tightly-coupled GNSS/IMU with multiple anti-spoofing techniques based on the analysis of the influence mechanism of spoofing on the positioning of tightly-coupled GNSS/IMU, the algorithm proposes a measurement deviation determination method to avoid a variety of anti-spoofing techniques, which can gradually pull the positioning results of coupled system, and successfully avoid anti-spoofing techniques detection of least squares residual receiver autonomous integrity monitoring (RAIM) and parameter rationality check. The experimental results show that the algorithm can gradually change positioning of tightly-coupled GNSS/IMU within 30 s, and the north, east and down displacements basically achieve the spoofing effect, the errors with the expected offset are −0.5 m, 1.9 m and 12.7 m respectively. At the same time, the detection of the above anti-spoofing techniques is avoided. The mean value of test statistics for tightly-coupled system is reduced by 75.4% and does not exceed the alarm threshold, so as to achieve the purpose of spoofing, the effectiveness and high concealment of the spoofing algorithm are proved. [ABSTRACT FROM AUTHOR]

The Stretched-FrOnt-Leg (SFOL) pulse is a high-accuracy distance measuring equipment (DME) pulse developed to support alternative positioning and navigation for aircraft during global navigation satellite system outages. To facilitate the use of the SFOL pulse, it is best to use legacy DMEs that are already deployed to transmit the SFOL pulse, rather than the current Gaussian pulse, through software changes only. When attempting to transmit the SFOL pulse in legacy DMEs, the greatest challenge is the pulse shape distortion caused by the pulse-shaping circuits and power amplifiers (PAs) in the transmission unit such that the original SFOL pulse shape is no longer preserved. This letter proposes an inverse-learning-based DME digital predistortion method and presents successfully transmitted SFOL pulses from a testbed based on a commercial legacy DME that was designed to transmit Gaussian pulses. [ABSTRACT FROM AUTHOR]

Aircraft attitude has always been an important technical parameter during flights, especially for stages such as aircraft take-off and landing. This article presents a monocular off-board vision system for relative attitude measurement of fixed-wing aircraft. In this system, a zoom imaging subsystem is set up to track and shoot the aircraft over a large distance range. Image sequences and corresponding servo data are transmitted to the processing computer for vision algorithms. A model-based attitude tracking algorithm, which requires the computer-aided design model of the aircraft, is performed to measure the relative attitude of the aircraft with respect to the reference platform. A 2-D visual tracking algorithm and a target detection algorithm are also employed to control the vision system. The proposed attitude tracking algorithm achieves competitive results on a publicly available dataset. The full system is validated in a real-flight experiment. The results revealed that the proposed system can run in real time on 1920×1080@40 Hz videos with an accuracy better than 0.5 $^\circ$. [ABSTRACT FROM AUTHOR]

In a pursuit evasion scenario, a missile (pursuer) launched from the ground or the air aims to intercept an aircraft (evader) flying in formation. This article considers the problem of whether an aircraft is aimed by a missile or not, based only on the line-of-sight (LOS) measurements from an on-board passive sensor. The motion of the missile is assumed to be governed by pure proportional navigation guidance. Previous works on this problem estimate the missile's state motion parameters, which, for a passive sensor, requires a numerical search, i.e., significant computation time, algorithm complexity and is ill-conditioned. We present a methodology that relies on the geometric relationship between the aircraft and the missile without state estimation. A plane is defined by the aircraft velocity vector and one aircraft-to-missile LOS vector, and if a second LOS vector at a subsequent time is in this plane, it is known that the missile aims at the aircraft. A coplanarity test is designed on the basis of these three vectors. We then provide a test statistic for inferring whether the airplane is aimed by the missile. An approximate distribution is used to set the threshold for detection and false alarm probabilities. Simulation results are presented for surface-to-air and air-to-air missile scenarios to illustrate the efficiency of the proposed method and compared to the state estimation method. [ABSTRACT FROM AUTHOR]

Magnetic anomaly navigation is gaining popularity as an alternative-navigation system that addresses the challenges of GPS denial. Magnetic anomaly navigation has recently been flight test proven on an F-16 aircraft. The corrupting magnetic environment on this operational platform is 2–3 orders of magnitude larger than previous flight-tests on geo-survey aircraft, while also displaying stochastic drift. The difficult magnetic environment of the platform necessitated a combination of batch and online calibration to obtain accurate navigation solutions. Superiority of the new method is shown in comparison to prior published methods. Real navigation results on the F-16 are shown to obtain accuracies 50% better than these competing methods, with low-altitude results obtaining 59-m distance root-mean-squared errors on 1.5 h flights versus 111 m using batch-only calibrations. [ABSTRACT FROM AUTHOR]

With the increasing interest in the utilization of urban airspace for unmanned aerial system (UAS) operations, be it for cargo delivery or passenger transportation, the future city sky could become quite a crowded place if all those visions become reality. In such case, the question of how close two operations could be conducted while sharing an airspace must be answered to ensure the safe and efficient use of the urban airspace. The lateral separation needed to prevent inadvertent intrusion by neighboring tracks is especially important when designing airspace corridors constrained by the urban landscape. This paper documents a series of flight tests conducted in open fields with the goal of assessing the along-track (longitudinal), cross-track (lateral),and altitude (height) deviation under two different flight conditions: operator guided operation within Visual Line of Sight (VLoS), and the waypoint-guided mission analogous to operating Beyond Visual Line of Sight (BVLoS). The flight test statistics were also compared to the Monte-Carlo based path prediction model that was used in earlier studies for collision prediction. The goal is to determine the Flight Technical Error (FTE) that forms a part of the Total System Error (TSE) for Performance Based Navigation (PBN) of UAS to support the establishment of separation requirements in urban airspace. [ABSTRACT FROM AUTHOR]

One of the most important issues facing both the American and European air traffic management systems will be to provide enough capacity to meet increasing air traffic demand while maintaining a high level of safety. In this work, we focus on the final approach flight phase and, in particular, on the missed approach procedure, which is conducted when unexpected occurrences force the aircrew to abort the landing. The current missed approach consists in recommencing the approach from the initial approach fix and, in some cases, it is just an outbound heading to wait for air traffic control instructions. In this article, we propose and evaluate the performance of a new missed approach procedure supported by current state-of-the-art communication, navigation, and surveillance technology. Our proposal, referred to as aircraft reinjection system, basically consists in identifying a gap in the inbound traffic flow, in accordance with the International Civil Aviation Organization standards, to reinject the affected aircraft and providing a new route to redirect the aircraft to that mentioned gap. Its evaluation proves that this proposal can achieve important time savings, helping to reduce the use of active runways, with the corresponding positive impact on the environment, noise, and pollution. Furthermore, and more importantly, it may enhance safety levels when the aircrew performs an unstable approach on final since they will be more willing and trained to perform an up-to-date and time-sensitive procedure rather than current old-fashioned ones. [ABSTRACT FROM AUTHOR]

In this article, we develop new stochastic tropospheric error models for positioning, fault detection, and integrity monitoring over time. We first perform time-domain and frequency-domain analyses of residual tropospheric delays observed over 12 months at multiple globally distributed locations. We then derive bounding error models for time-sequential safety-critical navigation systems including global navigation satellite systems integrated with inertial navigation systems and Kalman filter implementations of advanced receiver autonomous integrity monitoring. [ABSTRACT FROM AUTHOR]

This article develops a deep learning object detector to provide accurate six-degree-of-freedom (DoF) information of the drogue relative to a monocular camera onboard a flying unmanned aerial vehicle. An object detector helps to provide the needed information for an autonomous vehicle to dock and refuel without the need for human intervention. This object detector can detect eight different beacons by training on 8746 images of a mock drogue. Once these beacons were detected, a nonlinear least squares algorithm that uses the collinearity equations as a system model takes the beacon's location on the captured image to provide an accurate six-DoF navigation solution. These navigation solutions from the object detector were evaluated on multiple metrics and then compared to navigation solutions provided by a VICON motion tracking system. Finally, Monte Carlo analysis, using the collinearity equations as a system model, evaluates an object detector's performance with various noise levels. [ABSTRACT FROM AUTHOR]

In robot navigation tasks, such as unmanned aerial vehicle (UAV) highway traffic monitoring, it is important for a mobile robot to follow a specified desired path. However, most of the existing path-following navigation algorithms cannot guarantee global convergence to desired paths or enable following self-intersected desired paths due to the existence of singular points where navigation algorithms return unreliable or even no solutions. One typical example arises in vector-field guided path-following (VF-PF) navigation algorithms. These algorithms are based on a vector field, and the singular points are exactly where the vector field diminishes. Conventional VF-PF algorithms generate a vector field of the same dimensions as those of the space where the desired path lives. In this article, we show that it is mathematically impossible for conventional VF-PF algorithms to achieve global convergence to desired paths that are self-intersected or even just simple closed (precisely, homeomorphic to the unit circle). Motivated by this new impossibility result, we propose a novel method to transform self-intersected or simple closed desired paths to nonself-intersected and unbounded (precisely, homeomorphic to the real line) counterparts in a higher dimensional space. Corresponding to this new desired path, we construct a singularity-free guiding vector field on a higher dimensional space. The integral curves of this new guiding vector field is thus exploited to enable global convergence to the higher dimensional desired path, and therefore the projection of the integral curves on a lower dimensional subspace converge to the physical (lower dimensional) desired path. Rigorous theoretical analysis is carried out for the theoretical results using dynamical systems theory. In addition, we show both by theoretical analysis and numerical simulations that our proposed method is an extension combining conventional VF-PF algorithms and trajectory tracking algorithms. Finally, to show the practical value of our proposed approach for complex engineering systems, we conduct outdoor experiments with a fixed-wing airplane in windy environment to follow both 2-D and 3-D desired paths. [ABSTRACT FROM AUTHOR]

Recent successful flight tests have demonstrated scalar magnetic anomaly navigation to be a viable GPS-alternative navigation system. These flight tests matched magnetic field measurements to maps of the Earth's crustal magnetic field in order to navigate. Scalar magnetic navigation uses only the magnetic field intensity, not direction, in order to navigate. While it appears obvious to extend aerial magnetic navigation to use the full vector field, in practice there are substantial obstacles to doing so. This article explores the key challenges of magnetic vector navigation including current sensor limitations, lack of high frequency magnetic vector maps of the Earth's crust, and proper integration of the magnetic data with an inertial navigation system. In overcoming these challenges several key benefits of magnetic vector navigation over scalar magnetic navigation become apparent, including modestly improved navigation accuracy and greatly improved platform attitude. [ABSTRACT FROM AUTHOR]

We introduce in this article a distributed factor-graph-based algorithm for anchorless cooperative aircraft localization in a GNSS-denied scenario without fixed infrastructure. The agents use terrain-aided navigation (TAN) to perform local position estimation and exchange messages to improve their position beliefs. Internode communication cost is reduced using a hybrid Gaussian mixture model / sequential Monte Carlo (GMM/SMC) approach. Simulation results show that, even in a partially connected network where only a small part of the agents perform TAN, cooperation yields better results than all aircraft performing TAN independently. [ABSTRACT FROM AUTHOR]

Advanced receiver autonomous integrity monitoring (ARAIM) is under development to support both lateral and vertical guidance. A key component of ARAIM is the integrity support message (ISM), which contains validated input parameters including the probabilities of satellite and constellation failure. A service commitment for the former is provided in the global positioning system (GPS) performance standards, whereas further commitments from GLONASS, Galileo, and Beidou are expected to follow. However, air navigation service providers may demand some flexibility in setting the ISM. This article presents a procedure for setting ISM parameters employing a means to determine the a priori probabilities using the Bayesian inference of a Poisson process model given in the literature. This method and a novel way to accumulate the service history are used to analyze the effects of satellite block and age. Results show that while the type and age of satellite are clearly drivers in the likelihood of a fault; such effects may be accounted for without significant impact on the broadcast values. This article also addresses the probability of unscheduled satellite outages using the new method. Finally, this article gives a high-level scheme of how the validity of the ISM parameters may be assured. [ABSTRACT FROM AUTHOR]

Relative unmanned aerial vehicle attitude is estimated using only on-board radio-frequency signaling. The method uses a direction-of-arrival (DoA) vector estimate to determine two degrees-of-freedom (DoFs), a polarimetric narrowband multiple-input multiple-output (MIMO) channel estimate to specify the third DoF to within a $180^\circ$ ambiguity, and one of the several potential methods for ambiguity resolution. Simulation results demonstrate that the method accurately determines aircraft attitude, with errors proportional to DoA and MIMO channel estimate errors. This approach is useful for cooperative navigation when external navigation aids are not available, such as in GPS-denied environments. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of the autocorrelations of monitor test statistics on navigation integrity and continuity. General analytical methods are rigorously developed to evaluate the actual integrity risk and false alert probability over the exposure interval. Prior to this work, the probabilities computed based on one-sample test have been widely applied in aviation navigation. However, it will be shown that using the one-sample probability may lead to overly optimistic results, because the actual risk can be significantly higher, especially for false alert. The new methods are applied to an example problem of advanced receiver autonomous integrity monitoring. To quantify integrity, a simple but conservative upper bound is derived. As for continuity, both analytical and experimental results show that the actual false alert probability is two orders of magnitude higher than previously thought, due to the time-correlation effects. A feasible solution to mitigate this impact is provided, without degrading navigation availability. [ABSTRACT FROM AUTHOR]

In this paper, an extended signal-correction observer (ESCO) is presented for signals correction and estimation, which not only can reject the large measurement error, but also the system uncertainty can be estimated, in spite of the existence of intense stochastic non-Gaussian noise. Multi-input describing function method is proposed to analyze the ESCO robustness in frequency domain. The ESCOs are developed for position/velocity and attitude angle/angular rate integrations, respectively, and they are applied to an aircraft navigation. Based on the ESCO, the position, attitude angle, and the uncertainties in the flight dynamics are estimated. Experiments demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to assess and determine the potential of augmented reality (AR) in aerospace applications through a survey of published sources. Design/methodology/approach: This paper reviews a database of AR applications developed for the aerospace sector in academic research or industrial training and operations. The review process begins with the classification of these applications, followed by a brief discussion on the implications of AR technology in each category. Findings: AR is abundantly applied in engineering, navigation, training and simulation. There is potential for application in in-flight entertainment and communication, crew support and airport operations monitoring. Originality/value: This paper is a general review introducing existing and potential AR applications in various fields of the aerospace industry. Unlike previous publications, this article summarizes existing and emerging applications to familiarize readers with AR use in all of aerospace. The paper outlines example projects and creates a single comprehensive reference of AR advancements and its use in the aerospace industry. The paper provides individuals with a quick guide to available and emerging technology. [ABSTRACT FROM AUTHOR]

Reconstructing a 3-D scene from aerial sensor data creating a textured digital surface model (TDSM), consisting of a LiDAR point cloud and an overlaid image, is valuable in many applications including agriculture, military, surveying, and natural disaster response. When collecting LiDAR from an aircraft, the navigation system accuracy must exceed the LiDAR accuracy to properly reference returns in 3-D space. Precision navigation systems can be expensive and often require full-scale aircraft to house such systems. Synchronizing the LiDAR sensor and a camera, using a texel camera calibration, provides additional information that reduces the need for precision navigation equipment. This paper describes a bundle adjustment technique for aerial texel images that allows for relatively low-accuracy navigation systems to be used with low-cost LiDAR and camera data to form higher fidelity terrain models. The bundle adjustment objective function utilizes matching image points, measured LiDAR distances, and the texel camera calibration and does not require overlapping LiDAR scans or ground control points. The utility of this method is proven using a simulated texel camera and unmanned aerial system (UAS) flight data created from aerial photographs and elevation data. A small UAS is chosen as the target vehicle due to its relatively inexpensive hardware and operating costs, illustrating the power of this method in accurately referencing the LiDAR and camera data. In the 3-D reconstruction, the 1- $\sigma $ accuracy between LiDAR measurements across the scene is on the order of the digital camera pixel size. [ABSTRACT FROM AUTHOR]

This paper presents a vision/radar/INS integrated guidance system for shipboard landing. The vision system on the aircraft tracks landmarks on the ship and outputs their coordinates in the image. The motion information of aircraft is obtained from airborne inertial navigation system (INS). Meanwhile, the datalink receives the relative position between the ship and aircraft from the shipboard radar and the ship motion information from shipboard sensors. The federated filter is utilized to fuse the vision, radar and inertial information, and the information from INS is chosen as the reference system in the federated filter. The estimated ship motion information is utilized to calculate the glide-down path. All the guidance information is regarded as the feedback information given to the flight control system to calculate control command. A designed on-vehicle experiment shows that the vision/radar/INS integrated landing guidance system achieves satisfied results. [ABSTRACT FROM AUTHOR]

Automatic dependent surveillance-broadcast (ADS-B) is an emerging air traffic surveillance technology that overcomes the limitations of today's radar technology and enhances the air traffic control. To provide authenticity, integrity in ADS-B and to improve the computation, communications efficiency, in this paper, we propose a new, efficient, and secure pairing-free ADS-B authentication scheme with Batch Verification in ID-based framework. The proposed scheme is proven secure and is more efficient than the existing schemes. [ABSTRACT FROM AUTHOR]

In the air–ground propagation channel, multipath propagation severely affects the performance of communication, navigation, and surveillance systems used in civil aviation. To verify the performance of aeronautical wireless transmission systems independently from expensive flight trials, a channel model for computer simulations is required. Based on an exhaustive propagation measurement campaign, we propose a geometry-based stochastic channel model for the air–ground channel in a regional airport environment in the L-band. The proposed channel model allows us to correctly reproduce the non-stationarity of the channel impulse response. Thus, the channel model is suitable not only to assess the performance of communication systems, but also for ranging, i.e., for navigation systems. We validate the channel model using data from both channel sounding and as well as flight measurements performed in a navigation context. [ABSTRACT FROM AUTHOR]

Thanks to recent enormous advance of mobile and vehicular technology, it is highly expected that unmanned aerial vehicles (UAVs) are used for various applications in smart cities as well as the number of flying UAVs in the sky is increasing explosively. However, such a proliferation of UAVs accompanies additional critical issues to be considered for efficient, secure use of UAVs. One of important issues should be the privacy of people. When the UAVs fly to perform specific objectives, minimizing movements of UAVs is an important issue to minimize mission completion time and to maximize the network lifetime of UAVs. To do so, one intuitive solution is that UAVs may pass through private area of citizens whereas people do not want any penetration into own area without a permission. For those situations, we may take into account a compromise so that people can decide whether they give a differential, temporal permission for each UAV to access their areas depending on specific benefits by use of UAVs or emergent situation for public safety. In this study, we introduce a framework for privacy preserving movements of UAVs with differential UAVs’ permissions given by citizens, which is called as UAVs’ differential privacy preserving movements (UDiPP). Then, using integer linear programming, we formally define a problem whose objective is to minimize total movements of UAVs with preserving privacy of citizens. To solve the problem, we propose a novel approach with a creation of UDiPP graph and then evaluate its performance through extensive simulations. [ABSTRACT FROM AUTHOR]

A full analysis of position-domain integrity is carried out for the recently introduced generalized integer aperture bootstrapping (GIAB) technique, a data-driven method for resolving and validating global navigation satellite system carrier-phase integer ambiguities suitable for high-integrity safety-critical systems. The analysis can be extended to all integer aperture (IA) techniques that are generalized in the sense of allowing partial integer fixing. It is shown that generalized IA methods produce relative position (baseline) estimates that suffer from nonnegligible biases. Key conditional distributions of the baseline computed from GIAB-validated ambiguities are rigorously derived for both full and partial ambiguity resolution. These distributions enable evaluation of the a posteriori risk from bias in the GIAB baseline estimate. Compared to enforced position-domain integrity risk of cycle resolution, the state-of-the-art high-integrity algorithm, GIAB is shown to satisfy tighter integrity requirements for the same measurement model. [ABSTRACT FROM AUTHOR]

Highlights • Polluting gases and particulate matter are a health problem for cities. • Air pollution is dynamic; it moves through the air. • Aerial vehicles allow the pollutants measurement in air columns. • Pollution produced by cities is not local, it moves to the periphery. Abstract This paper presents the design, development and preliminary results of a sensor system that georeferences and measures atmospheric variables, polluting gases and particle pollution on ground level and lower troposphere using an unmanned aerial vehicle. The system can measure dioxide and monoxide of carbon, methane, ozone, different-diameter particle pollution, and variables such as temperature, humidity, among others. Data is registered and processed by a microcontroller system, is saved in a SD card and sent to a ground station using an Xtend radiofrequency system. Atmospheric and pollution data is published in real time on a website; reports could be generated. Some tests were performed in Envigado, Antioquia-Colombia, because the special geographic characteristics of this area increase the concentration of polluting gases in Medellín City troposphere. This equipment facilitates terrestrial and aerial measurements because is a compact and versatile device that allows optimizing predictive models of pollutant gases. [ABSTRACT FROM AUTHOR]

In the air–ground propagation channel, multipath propagation severely affects the performance of the communication, navigation, and surveillance systems used in civil aviation. To gain a deeper understanding of the air–ground channel, we are interested in the locations of objects causing multipath propagation. Therefore, in this paper we propose and experimentally validate an algorithm to localize reflectors causing multipath components based on channel sounding data collected using omnidirectional antennas. The algorithm relies on superresolution parameter estimation and tracking as well as on a localization algorithm. Using both simulations and channel sounding data collected from flight trials, we demonstrate the ability to reliably localize the reflectors causing multipath components. [ABSTRACT FROM AUTHOR]

In this paper, we argue that current state-of-the-art methods of aircraft localization such as multilateration are insufficient, in particular for modern crowdsourced air traffic networks with random, unplanned deployment geometry. We propose an alternative, a grid-based localization approach using the k-nearest neighbor (k -NN) algorithm, to deal with the identified shortcomings. Our proposal does not require any changes to the existing air traffic protocols and transmitters, and is easily implemented using only low-cost, commercial-off-the-shelf hardware. Using an algebraic multilateration algorithm for comparison, we evaluate our approach using real-world flight data collected with our collaborative sensor network OpenSky. We quantify its effectiveness in terms of aircraft location accuracy, surveillance coverage, and the verification of false position data. Our results show that the grid-based k-NN approach can increase the effective air traffic surveillance coverage compared to multilateration by a factor of up to 2.5. As it does not suffer from dilution of precision to the same extent, it is more robust in noisy environments and performs better in pre-existing, unplanned receiver deployments. We further find that the mean aircraft location accuracy can be increased by up to 41% in comparison with multilateration while also being able to pinpoint the origin of potential spoofing attacks conducted from the ground. [ABSTRACT FROM AUTHOR]

This paper proposes a novel pilot control model which reflects the following three characteristics of the pilot control behavior: stochastic, periodical, and discrete movement. The focus is on the final descent phase when the pilot controls the aircraft manually based on the flight director commands. The proposed model is developed based on an existing model as well as highly experienced pilot's comments. A flight simulator experiment is conducted and three pilots’ landing data are obtained. The parameters of the pilot model are tuned via a genetic algorithm. The simulation result reveals that the proposed model captures well the characteristics of the data obtained in the simulator experiment and shows a good accordance with actual command tracking capability. The obtained parameters also identify the difference of control strategies between the pilots. [ABSTRACT FROM PUBLISHER]

The continual growth in air traffic demand, the emergence of new flight routes, and the increased congestion at major airports are some of the important incentives for developing novel solutions to deal with increased pilot workload and improve safety. This paper introduces a novel Global Operational Concept (GOC) for commercial aviation cockpits that is intended to support pilots during peak workload situations. This GOC applies to two-flight crew operations, intentional and unintentional flight-crew reduction and total flight-crew incapacitation, and comprises different solutions that cover all safety-related crew duties across all phases of flight and serves as an interface between technology and organisations. The GOC concept was developed under the Advanced Cockpit for Reduction of Stress and Workload (ACROSS) project, which was part of the European Commission’s 7th Framework Programme (FP7) and investigated four solutions that will contribute to the reduction of pilot workload and stress by adapting cockpit applications and systems to challenging situations. [ABSTRACT FROM AUTHOR]

In this paper, we describe and evaluate a new monitor that uses inertial navigation system (INS) measurements to detect spoofing attacks on global navigation satellite system (GNSS) receivers. Spoofing detection is accomplished by monitoring the Kalman filter innovations in a tightly coupled INS/GNSS mechanization. Monitor performance is evaluated against worst case spoofing attacks, including spoofers capable of tracking vehicle position. There are two main contributions of this paper. The first is a mathematical framework to quantify postmonitor spoofing integrity risk. The second is an analytical expression of the worst case sequence of spoofed GNSS signals. We then apply these to an example spoofing attack on a Boeing 747 on final approach. The results show that GNSS spoofing is easily detected, with high integrity, unless the spoofer's position-tracking devices have unrealistic, near-perfect accuracy, and no delays. [ABSTRACT FROM AUTHOR]

To navigate in global navigation satellite systems (GNSS) signal-challenged environment, for example, foliage canopy, urban canyon, indoor, etc., high-sensitivity GNSS receivers are usually preferred for the improved acquisition and tracking capabilities. The core of high-sensitivity GNSS receiver design is to extend integration time coherently, which is optimal for improving post-signal-to-noise ratio, mitigating multipath and cross-correlation false locks, and avoiding squaring loss. In GNSS data channels, extending integration time coherently requires the navigation message data bit wipe-off. For stand-alone high-sensitivity GNSS receivers, bit wipe-off is usually achieved by using estimation algorithms (i.e., bit decoding) rather than accessing external networks (i.e., bit aiding). In this paper, the maximum-likelihood (ML) bit decoding is used to estimate the data bit values for bit wipe-off. Furthermore, the benefits of using advanced tracking algorithms?vector tracking and inertial navigation system (INS)-assisted tracking (i.e., ultratight coupling of GNSS/INS)?to improve ML bit decoding and navigation performance are analyzed. Two vehicular navigation tests are performed in dense foliage and an urban canyon environment. In the context of global positioning system L1 C/A signals, the field test results show that vector tracking and ultratight coupling can improve the successful decoding rate by up to 40% depending on signal strength. This paper also demonstrates how the signal power-based correlator selection method can address high bit error-rate problems when ML bit decoding is used for bit wipe-off in the signal-challenged environment. After implementing this algorithm, the position and velocity accuracy of the stand-alone high-sensitivity GNSS receiver has been improved about 50% after extending coherent integration time from 20 to 100 ms in the vehicular navigation tests. [ABSTRACT FROM PUBLISHER]

We consider the problem of navigating a military aircraft in a threat environment to its final destination while minimizing the maximum threat level and the length of the aircraft path. The proposed method to construct optimal low-risk aircraft paths involves a simple geometric procedure and is very computationally efficient. The effectiveness of the developed algorithm is illustrated by a number of examples and comparisons with a fuzzy logic based algorithm. [ABSTRACT FROM PUBLISHER]

A method for intermittently aiding an inertial navigation system (INS) is explored in which a ground feature of unknown position is optically tracked over a short measurement epoch—one then refers to Visual-INS. In contrast to current machine vision-based research trends, a human operator is entrusted with visually tracking the ground feature. Converted measurements of the feature position are generated from successive bearing measurements, and the estimated aircraft position. A linear regression algorithm is then applied to the converted measurements providing an estimate of the INS horizontal velocity components’ errors and also accelerometer biases. At the completion of the measurement epoch, the INS is corrected by subtracting out the estimated velocity errors and using the estimated accelerometer biases. Aiding the INS in this manner provides a significant improvement in the accuracy of the INS-provided aircraft navigation state estimates when compared to those of a free/unaided INS. Applications for this autonomous navigation method include navigation in global positioning system denied environments and/or when the use of RF transmitting navigation aids is undesirable. [ABSTRACT FROM PUBLISHER]

The calibration, in particular about the installation errors of a star sensor, is a vital problem when improving the accuracy of stellar-inertial navigation system (INS). This paper proposed an all-parameter calibration method for a ground-based stellar-INS with 12-position rotations, using a Kalman filter that can simultaneously estimate bias, scale factor, misalignments of inertial measurement unit (IMU), and installation errors of star sensor. The difference between the star vector measured by the star sensor and the gold reference generated by the star simulator is used as an observation. On the basis of observability to all parameters, the accuracy is greatly enhanced through an iterative method. Better than previous separate calibration of INS and star sensor, the proposed method offers an advantage in that installation error is slightly influenced by IMU drift and device precision. The experimental results demonstrate that all estimated parameters have good stability and repeatability, with the maximum attitude error of integrated navigation less than 6^\prime \prime after compensation, compared with 20^\prime \prime using the traditional method. It is shown that the proposed calibration method can efficiently improve the navigation performance of stellar-INS, which has been extensively used in shipborne systems, military aircraft, and missile systems. [ABSTRACT FROM AUTHOR]

This paper addresses the detection of a suddenly arriving dynamic profile of a finite duration often called a transient change. In contrast to the traditional abrupt change detection, where the post-change period is assumed to be infinitely long, the detection of a suddenly arriving transient change should be done before it disappears. The detection of transient changes after their disappearance is considered as missed. Hence, the traditional quickest change detection criterion, minimizing the average detection delays provided a prescribed false alarm rate, is compromised. The proposed optimality criterion minimizes the worst case probability of missed detection provided that the worst case probability of false alarm during a certain period is upper bounded. A suboptimal CUSUM-type transient change detection algorithm, based on a subclass of truncated Sequential Probability Ratio Tests, is proposed. The optimization of the proposed algorithm in this subclass leads to a specially designed Finite Moving Average Test. The proposed method is analyzed theoretically and by simulation. A special attention is paid to the case of Gaussian observations with a dynamic profile. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Robust aerial navigation without GPS is a challenging problem. Alternative navigation systems for airborne use are often limited by where and when they can operate. For example, terrain following systems cannot operate over oceans, and star-tracker and computer-vision systems depend on weather and daylight. Navigation using the Earth's magnetic anomaly field, which is globally available at all times, shows promise to overcome many of these limitations. We designed an airborne navigation system that utilizes only passive instruments—an optically pumped scalar magnetometer, an inertial navigation system (INS), a barometer, and a magnetic anomaly map. The navigation system uses a particle filter to correct errors in an INS as well as estimate measurement-corrupting temporal variations by comparing actual magnetometer measurements to expected measurements from the magnetic anomaly map. A complete measurement equation is presented that describes the nontrivial relationship between the real-time magnetometer measurements and the magnetic anomaly map. We validated the navigation system with real data from a flight test over Louisa, VA. Horizontal DRMS errors of 13 m were achieved over an hour long flight at the map altitude of 1000-ft MSL using a magnetic anomaly map created 3 years ago. This result should be considered as a “best case” result when using the presented methods, since the flight test was conducted in ideal conditions. The demonstrated accuracy of the navigation system shows orders of magnitude improvement over previously published magnetic navigation experimental results, indicating that the magnetic anomaly navigation is a promising addition to current global positioning system alternative and backup systems. [ABSTRACT FROM AUTHOR]

Many modern approaches to nonlinear filtering employ sample-based density approximations. These approximations are generated via random (Monte Carlo methods) or deterministic sampling [say, the unscented Kalman filter (UKF)]. The advantages of deterministic techniques are their reproducibility and that they require fewer samples. While the UKF is designed for real vector spaces, we present an approach for deterministic sampling applicable to two-dimensional periodic manifolds. This approach employs five weighted samples and matches trigonometric moments and a circular-circular correlation coefficient. [ABSTRACT FROM AUTHOR]

Currently, most airborne platforms use an Inertial Measurement Unit (IMU) to provide estimates of aircraft position, velocity, and attitude. Errors in the IMU result in a position solution that drifts over time. In order to counteract IMU drift, platforms typically integrate measurements from Global Navigation Satellite Systems (GNSS). However, many military and civilian scenarios encounter situations where GNSS may be unavailable due to intentional jamming, or when operating in challenging environments. Many solutions have been proposed that use images from an airborne camera to match features against a reference image to compute global position. These techniques require a relatively accurate prior estimate of position to converge. This leads to a situation where platforms being denied GNSS pass a threshold of position error due to IMU drift, from which current image-aided navigation system cannot recover. This paper presents a novel localization algorithm inspired by fusing state of the art Content Based Image Retrieval techniques with nonparametric Bayesian estimation strategies. We outline the framework for performing a search of a large-scale image database in order to provide a rough position estimate to an airborne platform. These techniques are analogous to solving the ?kidnapped-robot? problem, applied to airborne platforms. This framework is evaluated using actual data collected from an airborne camera and navigation system. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Due to the high flight speed of the aircraft and long range to access the ground station (GS), the channel state information (CSI) is not accurately obtained by direct feedback from the receiver to the transmitter. This makes it difficult to achieve stable transmission when the feedback codebook selection scheme is directly employed in the multiple-input multiple-output (MIMO) for the air-to-ground (A/G) communications. Therefore, in this paper, a stable transmission scheme for the A/G MIMO transmission is proposed to handle these issues. Two contributions are proposed: 1) an open-loop calibrated channel estimation scheme based on navigation filtering to offer a more accurate CSI estimation; and 2) an adaptive precoding scheme based on the correlation coefficient for stable transmission. The simulations confirm the validity and efficiency of the proposed schemes. For the 4 $\times$ 4 MIMO transmission, compared with the traditional scheme of a single antenna, the spectrum efficiency can be improved by 2 $\sim$ 4 times with a stable transmission. [ABSTRACT FROM PUBLISHER]