This work presents an analysis of arrival sequencing at Stockholm Arlanda airport. Thesequencing of arrivals is very important part of air traffic control management and assuressafe space and time distancing of arriving aircraft. In this work we use historical flight datafrom Opensky Network database. The historical flight data contains the information about allthe arrivals of the year 2018. The aim of this work is to propose the key performanceindicators (KPIs) for evaluation of the arrival sequencing at Stockholm Arlanda airport. Thethree KPIs we are considering in this work are the minimum time to final, spacing deviationand sequence pressure. We choose data subsets of different size representing different trafficsituations. We visualize the results and summarize them in tables which assures better clarityfor the comparison of the same KPIs for different data subsets. In addition, we demonstratehow the proposed KPIs can be used for evaluation of optimization results from related study.We conclude that the proposed KPIs are very useful for analysis of the arrival aircraftsequencing and help to uncover inefficiencies within the terminal manoeuvring area (TMA).

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19712号 / 工博第4167号 / 新制||工||1643(附属図書館) / 32748 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 篠原 真毅, 教授 土居 伸二, 准教授 小嶋 浩嗣 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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This thesis considers the problem of using signals of opportunity (SOO) with known direction of arrival (DOA) for aircraft positioning. SOO is a collective name for a wide range of signals not intended for navigation but which can be intercepted by the radar warning system on an aircraft. These signals can for example aid an unassisted inertial navigation system (INS) in areas where the global navigation satellite system (GNSS) is inaccessible. Challenges arise as the signals are transmitted from non-controllable sources without any guarantee of quality and availability. Hence, it is important that any estimation method utilising SOO is robust and statistically consistent in case of time-varying signals of different quality, missed detections and unreliable signals such as outliers. The problem is studied using SOO sources with either known or unknown locations. An extended Kalman filter (EKF) based solution is proposed for the first case which is shown to significantly improve the localisation performance compared to an unassisted INS in common scenarios. Yet, a number of factors affect this performance, including the measurement noise variance, the signal rate and the availability of known source locations. An outlier rejection mechanism is developed which is shown to increase the robustness of the suggested method. A numerical evaluation indicates that statistical consistency can be maintained in many situations even with the above-mentioned challenges. An EKF based simultaneous localisation and mapping (SLAM) solution is proposed for the case with unknown SOO source locations. The flight trajectory and initialisation process of new SOO sources are critical in this case. A method based on nonlinear least squares is proposed for the initialisation process, where new SOO sources are only allowed to be initialised in the filter once a set of requirements are fulfilled. This method has shown to increase the robustness during initialisation, when the outlier rejection is not applicable. When combining known and unknown SOO source locations, a more stable localisation solution is obtained compared to when all locations are unknown. Applicability of the proposed solution is verified by a numerical evaluation. The computational time increases cubically with the number of sources in the state and quadratically with the number of measurements. The time is substantially increased during landmark initialisation.

When faced with an uncertain network, travelers adjust departure time as well as route choices in response to real-time traveler information. Previous studies on algorithm design focus on adaptive route choices and cannot model adaptive departure time choices (DTC). In this thesis, the optimal adaptive departure time and route choice problem in a stochastic time-dependent network is studied. Travelers are assumed to minimize expected generalized cost which is the sum of expected travel cost and arrival delay costs. The uncertain network is modeled by jointly distributed random travel time variables for all links at all time periods. Real-time traveler information reveals realized link travel times and thus reduces uncertainties in the network. The adaptive departure time and route choice process is conceptualized as a routing policy, defined as a decision rule that specifies what node to take next at each decision node based on realized link travel times and the current time. Waiting at origin nodes is allowed to model DTCs that are dependent on traveler information. Departure time is a random variable rather than fixed as in previous studies. A new concept of action time is introduced, which is the time-of-day when a traveler starts the DTC decision process. Because of the efforts involved in processing information and making decisions, a cost could be associated with a departure made after the action time. An algorithm is designed to compute the minimum expected generalized cost routing policy and the corresponding optimal action time, from all origins to a destination for a given desired arrival time window. Computational tests are carried out on a hypothetical network and randomly generated networks. It is shown that adaptive DTCs lead to less expected generalized cost than fixed DTCs do. The benefit of adaptive DTC is larger when the variance of the travel time increases. The departure time distribution is more concentrated with a larger unit cost of departure delay. A wider arrival time window leads to a more dispersed departure time distribution, when there is no departure penalty.

This thesis aims at evaluating a proposed interferometry Angle of Arrival method for Bluetooth Low Energy and investigating the feasibility of using it together with current technology in a keyless entry access control solution. The current technology is an evaluation kit from Texas Instrument that is used together with various types of antennae arranged in arrays. An in-depth look at it revealed that it does not implement the proposed Angle of Arrival method for Bluetooth Low Energy but the deviations are minor. Results obtained from tests with delay lines show enough accuracy for a keyless entry access control solution. However, none of the tested antenna types do. The work concludes that current technology cannot be used as a keyless entry access control solution due to strong antenna dependencies. Future work is thus proposed to be done on antenna development. / Detta arbete syftar till att utvärdera en förslagen interferometri Angle of Arrival-metod för Bluetooth Low Energy samt undersöka möjligheten att använda den tillsammans med nuvarande tekniken i nyckellös åtkomstkontroll. Den nuvarande tekniken är ett utvärderingspaket från Texas Instrument som används tillsammans med olika typer av antenner. En utförlig undersökning av tekniken avslöjade att den inte implementerar den föreslagna Angle of Arrival-metod för Bluetooth Low Energy men avvikelserna är minimala. Resultat som erhållits från tester med fördröjningslinjer visar tillräckligt noggrannhet för nyckellös åtkomstkontroll. Men ingen av de testade antenntyperna gör det. Arbetet drar slutsatsen att den nuvarande tekniken inte kan användas som nyckellös åtkomstkontroll på grund av starka antennberoende. Framtida arbete föreslås således att fokusera på antennutveckling.

The Bluetooth direction finding working group proposed functionalities to the Bluetooth core that can realize Angle of Arrival estimations using interferometry. The technology can be employed to develop new access control applications. Following previous findings in Englund (2018), the purpose of this project is to investigate the feasibility of such systems when antennas are being used. The goal is to design a matchbox size antenna array which can be used by the system to distinguish between two sides in an inside-outside scenario. A number of antennas were designed, simulated and tested on a prototype. While the simulations results were consistent with the theory, the prototype measurements were not. However, it is shown that it is possible to estimate between inside and outside. / Bluetooth direction finding working group har lagt fram ett förslag om att lägga till Angle of Arrival estimerings funktionalitet baserat på en interferometri metod i Bluetooth kärnan. Tekniken kan användas för att utveckla nya åtkomstkontrolls lösningar. Detta projekt en påbyggnad av arbetet utfört av Englund (2018), syftet är att utvärdera möjligheten av en sådan åtkomstkontrolls lösning där antenner används. Målet är att designa en tändsticksask stor antenn array som kan användas av ett systemet för att särskilja mellan två sidor i ett insida-utsida scenario. Ett antal antenner konstruerades, simulerades och prototyper byggdes samt testades. Medan simuleringsresultaten var förenliga med teorin, så påvisade prototyperna inte samma beteende då resultatet skiljde sig från teorin. Projektet konstaterar dock att det är möjligt att skilja mellan insida och utsida.

A low-cost radio direction finding (RDF) VHF receiver has been investigated for development into a radio direction finding network (RDFN) with a particular focus towards public service and commercial asset tracking applications. The primary design criteria were reproducibility, low-cost, and simplicity such that public service and volunteer organizations can benefit from the technology. Two receiver designs were built and tested to allow for comparison of practicality, cost, and accuracy. A pseudo-Doppler RDF and a time difference of arrival (TDOA) receiver were built as proof-of-concept for a system design based on commercial off-the-shelf (COTS) components. The pseudo-Doppler system is a less practical implementation due to the necessity for custom hardware, a large antenna system, and an increased directional error due to multipath and weak signals. The TDOA system has potential as a very simple and low-cost RDFN implementation, but requires extremely accurate time synchronization that is difficult to achieve using COTS GPS receiver modules. The final proposed solution takes advantage of the simple TDOA hardware and multiple detection techniques (including signal strength) to produce improved locational data and ultimately provide a more accurate estimate of position. Further development and improvements to this receiver design have the potential for implementation as a low-cost radio direction finding network.

With the expansion of unmanned aircraft system (UAS) technologies, there is a growing need for UAS Traffic Management (UTM) systems to promote safe operation and development. To be successful, these UTM systems must be able to detect and track multiple drones in the presence of clutter. This paper examines the implementation of different algorithms on a compact, X-band, frequency modulated continuous wave (FMCW) radar in an effort to enable more accurate detection and estimation of drones. Several algorithms were tested through post processing on actual radar data to determine their accuracy and usefulness for this system. A promising result was achieved through the application of pulse-Doppler processing. Post processing on recorded radar data showed that a moving target indicator successfully separated a target from clutter. An improvement was also noted for the implementation of phase comparison monopulse which accurately estimated angle of arrival (AOA) and required fewer computations than digital beamforming.The second part of this thesis explains the work done on an adaptive broadband, real time beamformer for RF interference (RFI) mitigation. An effective communication system is reliable and can counteract the effects of jamming. Beamforming is an appropriate solution to RFI. To assist in this process FPGA firmware was developed to prepare signals for frequency domain beamforming. This system allows beamforming to be applied to 150 MHz of bandwidth. Future implementation will allow for signal reconstruction after beamforming and demodulation of a communication signal.

Methods for Direction of Arrival, DOA estimation of multiple objects based on phased arrayantenna technology have many advantages in for example electronic warfare and radarapplications. However, perfect calibration of an antenna array can seldom be achieved. Thepurpose of this report is to study different methods for DOA estimation and how calibration-/modelerrors affect the results. Possible methods for quantifying these kinds of errors using measurement data are suggested. This thesis consists of essentially five parts. The different studies have been carried out using MATLAB simulations as well as theoretical considerations, i.e., calculations. In the first study, examples of the possible performance of four DOA algorithms, MUSIC, TLS-ESPRIT, WSF, and DML are provided. Results are given both with and without applying spatial smoothing. The latter scheme is used for handling correlated, or even coherent, sources. The results show that, for the considered scenarios, MUSIC performs the most consistently well, while the performance of DML is inferior. ESPRIT is well-performing when spatial smoothing is applied and performs the best when the angles of two signals are very close. It has been observed that WSF with weighting matrices for optimal asymptotic performance as well as spatial smoothing applied doesn’t perform well. When applying model errors to the systemin the second study, the corresponding conclusions about the algorithms can be drawn. That separation distance between the angles and that higher SNR results in better estimates are also confirmed. Quantification of certain array errors is also considered using methods inspired by a scheme proposed in the context of nonlinear system identification. The results show that the DOA algorithms are very good at dealing with noise and that the attempted method works well when the model error is like the true signals, but different enough that it is not confused with a problem with more signals. The model error that results in the worst results is when it only affects some ofthe channels in the antenna array. The fourth study explores DOA estimation using extended Kalman filtering and concludes that it is a very good tracker of the angle over time for the considered scenarios. All of this is then applied to measured data, but due to either extensive model error, errors with processing the data, or both, the results are worse than expected. Simulations that try to replicate the measured data results in good angle estimation for the DOA algorithms. The Kalman filter also performs well in simulations.