An effective procedure to design the layout of standard and enhanced mode-S multilateration systems for airport surveillance

In this paper, an effective procedure to emplace standard and enhanced mode-S multilateration stations for airport surveillance is studied and developed. This procedure is based on meta-heuristic optimization techniques, such as genetic algorithm (GA), and is intended to obtain useful parameters for an optimal system configuration that provides acceptable performance levels. Furthermore, the procedure developed here is able to evaluate and improve previous system designs, as well as possible system enhancements. Additionally, the design strategies to be used along with the procedure proposed here are fully described. Parameters such as the number of stations, the system geometry, the kind of measurements to be used, and the system accuracy are obtained taking into account the basic requirements such as the Line of Sight, the probability of detection, and the accuracy levels. © Cambridge University Press and the European Microwave Association, 2012

Improvement of multilateration(MLAT) accuracy and convergence for airport surveillance

AbstractIn this paper, westudy, evaluate and develop the use of regularization methods to solve the location problem in multilateration systems using Mode-S signals. The Tikhonov method has been implemented as a first applicationto solve the classical system of hyperbolic equations in multilateration systems. Some simulations are obtained and the results are compared with those obtained by the well established Taylor linearization and with the Cramér-Rao Lower Bound analysis. Significant improvements are found for the applicationof Tikhonov method

Efficient location strategy for airport surveillance using mode-s multilateration systems

© Cambridge University Press and the European Microwave Association, 2012[EN] In this paper, the use of regularization methods to solve the location problem in multilateration systems, using Mode-S signals, is studied, evaluated, and developed. The Tikhonov method has been implemented as a first application to solve the classical system of hyperbolic equations in multilateration systems. Some simulations are obtained and the results are compared with those obtained by the well-established Taylor linearization and with the Cramér-Rao lower bound analysis. Significant improvements, for the accuracy, convergence, and the probability of location, are found for the application of the Tikhonov method. © Cambridge University Press and the European Microwave Association, 2012.Mr. Ivan A. Mantilla-Gaviria has been supported by a FPU scholarship (AP2008-03300) from the Spanish Ministry of Education. Moreover, the authors are grateful to Thales Italia S. p. A. (Dr. Ing. R. Scaroni) who supplied the geometry of the Multilateration system in Linate (Milan, Italy) airport.Mantilla Gaviria, IA.; Leonardi, M.; Galati, G.; Balbastre Tejedor, JV.; Reyes Davó, EDL. (2012). Efficient location strategy for airport surveillance using mode-s multilateration systems. International Journal of Microwave and Wireless Technologies. 1-8. https://doi.org/10.1017/S1759078712000104S18Bertero, M., Boccacci, P., Brakenhoff, G. J., Malfanti, F., & Voort, H. T. M. (1990). Three-dimensional image restoration and super-resolution in fluorescence confocal microscopy. Journal of Microscopy, 157(1), 3-20. doi:10.1111/j.1365-2818.1990.tb02942.xSchau, H., & Robinson, A. (1987). Passive source localization employing intersecting spherical surfaces from time-of-arrival differences. IEEE Transactions on Acoustics, Speech, and Signal Processing, 35(8), 1223-1225. doi:10.1109/tassp.1987.1165266Gfrerer, H. (1987). An a posteriori parameter choice for ordinary and iterated Tikhonov regularization of ill-posed problems leading to optimal convergence rates. Mathematics of Computation, 49(180), 507. doi:10.1090/s0025-5718-1987-0906185-4[6] Galati G. ; Leonardi M. ; Tosti M. : Multilateration (local and wide area) as a distributed sensor system: lower bounds of accuracy, in European Radar Conf., EuRAD, Amsterdam, 30–31 October 2008.[1]The European Organisation for the Safety of Air Navigation. The ATM surveillance strategy for ECAC, in European Air Traffic Management Programme, Eurocontrol, 2008.Torrieri, D. (1984). Statistical Theory of Passive Location Systems. IEEE Transactions on Aerospace and Electronic Systems, AES-20(2), 183-198. doi:10.1109/taes.1984.310439[12] Perl E. ; Gerry M.J. : Target localization using TDOA distributed antenna, US 2005/0035897 A1, USA, 17 February 2005.[2]The European Organisation for Civil Aviation Equipment. Ed-117, mops for mode s multilateration systems for use in advanced surface movement guidance and control systems (a-smgcs), in EUROCAE (Ed.), EUROCAE, November 2003.Leonardi, M., Mathias, A., & Galati, G. (2009). Two efficient localization algorithms for multilateration. International Journal of Microwave and Wireless Technologies, 1(3), 223-229. doi:10.1017/s1759078709000245Ho, K. C., & Chan, Y. T. (1993). Solution and performance analysis of geolocation by TDOA. IEEE Transactions on Aerospace and Electronic Systems, 29(4), 1311-1322. doi:10.1109/7.259534FOY, W. (1976). Position-Location Solutions by Taylor-Series Estimation. IEEE Transactions on Aerospace and Electronic Systems, AES-12(2), 187-194. doi:10.1109/taes.1976.308294Phillips, D. L. (1962). A Technique for the Numerical Solution of Certain Integral Equations of the First Kind. Journal of the ACM, 9(1), 84-97. doi:10.1145/321105.321114Hanke, M., & Raus, T. (1996). A General Heuristic for Choosing the Regularization Parameter in Ill-Posed Problems. SIAM Journal on Scientific Computing, 17(4), 956-972. doi:10.1137/0917062Golub, G. H., Heath, M., & Wahba, G. (1979). Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter. Technometrics, 21(2), 215-223. doi:10.1080/00401706.1979.10489751Harrington, R. F. (1993). Field Computation by Moment Methods. doi:10.1109/978047054463

Multi Sensor Data Fusion Architectures for Air Traffic Control Applications

Nowadays, the radar is no longer the sole technology which is able to ensure the surveillance of air traffic. The extensive deployment of satellite systems and air-to-ground data links leads to the emergence of complementary means and techniques on which a great deal of research and experiments have been carried out over the past ten years. In such an environment, the sensor data processing, which is a key element in any Air Traffic Control (ATC) centre, has been continuously upgraded so as to follow the sensor technology evolution and in the meantime improves the quality in term of continuity, integrity and accuracy criteria. This book chapter proposes a comprehensive description of the state of art and the roadmap for the future of the multi sensor data fusion architectures and techniques in use in ATC centres. The first part of the chapter describes the background of ATC centres, while the second part of the chapter points out various data fusion techniques. Multi radar data processing architecture is analysed and a brief definition of internal core tracking algorithms is given as well as a comparative benchmark based on their respective advantages and drawbacks. The third part of the chapter focuses on the most recent evolution that leads from a Multi Radar Tracking System to a Multi Sensor Tracking System. The last part of the chapter deals with the sensor data processing that will be put in operation in the next ten years. The main challenge will be to provide the same level of services in both surface and air surveillance areas in order to offer: ⢠highly accurate air and surface situation awareness to air traffic controllers, ⢠situational awareness via Traffic Information System â Broadcast (TIS-B) services to pilots and vehicle drivers, and ⢠new air and surface safety, capacity and efficiency applications to airports and airlines

Exploiting Structural Signal Information in Passive Emitter Localization

The operational use of systems for passive geolocation of radio frequency emitters poses various challenges to single sensor systems or sensor networks depending on the measurement methods. Position estimation by means of direction finding systems often requires complex receiver and antenna technique. Time (Difference) of Arrival methods (TDOA, TOA) are based on measurements regarding the signal propagation duration and generally require broadband communication links to transmit raw signal data between spatially separated receivers of a sensor network. Such bandwidth requirements are particularly challenging for applications with moving sensor nodes. This issue is addressed in this thesis and techniques that use signal structure information of the considered signals are presented which allow a drastic reduction of the communication requirements. The advantages of using knowledge of the signal structure for TDOA based emitter localization are shown using two exemplary applications. The first case example deals with the passive surveillance of the civil airspace (Air Traffic Management, ATM) using a stationary sensor network. State of the art airspace surveillance is mainly based on active radar systems (Primary Surveillance Radar, PSR), cooperative secondary radar systems (Secondary Surveillance Radar, SSR) and automatic position reports from the aircraft itself (Automatic Dependent Surveillance-Broadcast, ADS-B). SSR as well as ADS-B relies on aircrafts sending transponder signals at a center frequency of 1090 MHz. The reliability and accuracy of the position reports sent by aircrafts using ADS-B are limited and not sufficient to ensure safe airspace separation for example of two aircrafts landing on parallel runways. In the worst case, the data may even be altered with malicious intent. Using passive emitter localization and tracking based on multilateration (TDOA/hyperbolic localization), a precise situational awareness can be given which is independent of the content of the emitted transponder signals. The high concentration of sending targets and the high number of signals require special signal processing and information fusion techniques to overcome the huge amount of data. It will be shown that a multilateration network that employs those techniques can be used to improve airspace security at reasonable costs. For the second case, a concept is introduced which allows TDOA based emitter localization with only one moving observer platform. Conventional TDOA measurements are obtained using spatially distributed sensor nodes which capture an emitted signal at the same time. From those signals, the time difference of arrival is estimated. Under certain conditions, the exploitation of signal structure information allows to transfer the otherwise only spatial into a spatial and temporal measurement problem. This way, it is possible to obtain TDOA estimates over multiple measurement time steps using a single moving observer and to thus localize the emitter of the signals. The concept of direct position determination is applied to the single sensor signal structure TDOA scheme and techniques for direct single sensor TDOA are introduced. The validity and performance of the presented methods is shown in theoretical analysis in terms of Cramér-Rao Lower Bounds, Monte-Carlo simulations and by evaluation of real data gained during field experiments

Air Traffic Control Tracking Systems Performance Impacts with New Surveillance Technology Sensors

Nowadays, the radar is no longer the only technology able to ensure the surveillance of air traffic. The extensive deployment of satellite systems and air-to-ground data links lead to the emergence of other means and techniques on which a great deal of research and experiments have been carried out over the past ten years. In such an environment, the sensor data processing, which is a key element of an Air Traffic Control center, has been continuously upgraded so as to follow the sensor technology evolution and, at the same time, ensure a more efficient tracking continuity, integrity and accuracy. In this book chapter we propose to measure the impacts of the use of these new technology sensors in the tracking systems currently used for Air Traffic Control applications. The first part of the chapter describes the background of new-technology sensors that are currently used by sensor data processing systems. In addition, a brief definition of internal core tracking algorithms used in sensor data processing components, is given as well as a comparison between their respective advantages and drawbacks. The second part of the chapter focuses on the Multi Sensor Tracking System performance requirements. Investigation regarding the use of Automatic Dependent Surveillance â Broadcast reports and/or with a multi radars configuration, are conducted. The third part deals with the impacts of the âvirtual radarâ or âradar-likeâ approaches that can be used with ADS-B sensors, on the multi sensor tracking system performance. The fourth and last part of the chapter discusses the impacts of sensor data processing performance on sub-sequent safety nets functions that are: ⢠Short term conflict alerts (STCA), ⢠Minimum Safe Altitude Warnings (MSAW), and ⢠Area Proximity Warnings (APW)

A new multilateration optimization technique for air traffic management and surveillance.

Abstract not available

АЛГОРИТМ ОЦЕНКИ КООРДИНАТ ОБЪЕКТОВ ДЛЯ СИСТЕМ МУЛЬТИЛАТЕРАЦИИ

At present, multilateration systems are becoming increasingly  important in air traffic control.  This is due  to their significant advantages in compare with secondary surveillance  radar complexes. This article solves the problem of synthesizing an algorithm for object location estimation for multilateration system operating in passive mode. The synthesized algorithm is a combination of a procedure, the result  of which is a rough  estimate of the observed object  coordinates, and  an iterative  algorithm specifying  the resulting solution.  The rough estimate is the result of solving a linear system of equations. The iterative  refinement procedure is based  on the linearization of the observational equations and does not require a large number of iterations. The paper provides  a comparative statistical  analysis  of the  proposed algorithm and  the  known  Bancroft  algorithm. For an objective analysis of two algorithms, the paper derives the Cramer-Rao boundary for the correlation matrix of estimates of the observed object coordinates, which makes it possible  to determine the potential accuracy of the solution  of the problem. It is shown  that both algorithms allow obtaining estimates, the accuracy of which is close to the potentially achievable accuracy of the object location estimate. In contrast to the Bancroft  algorithm, the rough estimate of the object location is unambiguous. This virtue reduces  the total amount of computations during the algorithm implementation and reduces  the probability of anomalous errors.В настоящее время системы мультилатерации приобретают все  большее значение в управлении воздушным движением в связи  с их существенными преимуществами по сравнению со вторичными радиолокационными  комплексами. В настоящей статье синтезирован алгоритм оценки местоположения объекта для  системы мультилатерации,  работающей в пассивном режиме.  Синтезированный алгоритм представляет собой  комбинацию процедуры грубой оценки координат наблюдаемого объекта и итерационного алгоритма, уточняющего полученное решение. Грубая  оценка является результатом решения системы линейных уравнений. Итерационная процедура уточнения основана на линеаризации уравнений наблюдения и не требует большого количества итераций. В статье дан  сравнительный статистический анализ предлагаемого алгоритма и известного алгоритма Банкрофта. Для объективного анализа двух  алгоритмов получена граница Крамера–Рао для  корреляционной матрицы оценок координат наблюдаемого объекта, которая позволяет определить потенциальную  точность решения задачи. Показано, что  оба алгоритма позволяют получить оценки, точность которых близка к потенциально  достижимой точности  оценки  местоположения объекта. В  отличие от   алгоритма Банкрофта получаемая грубая оценка местоположения является  однозначной,  что  сокращает общий объем  вычислений при реализации алгоритма и уменьшает вероятность получения аномальных ошибок

Effect of Path Loss Propagation Model on the Position Estimation Accuracy of a 3-Dimensional Minimum Configuration Multilateration System

The 3-Dimensional (3-D) position estimation (PE) accuracy of a multilateration (MLAT) system depends on several factors one of which is the accuracy at which the time difference of arrival (TDOA) measurements are obtained. In this paper, signal attenuation is considered the major contributor to the TDOA estimation error and the effect of the signal attenuation based on path loss propagation model on the PE accuracy of the MLAT system is determined. The two path loss propagation models are considered namely: Okumura-Hata and the free space path loss (FSPL) model. The transmitter and receiver parameters used for the analysis are based on actual system used in the civil aviation. Monte Carlo simulation result based on square ground receiving station (GRS) configuration and at selected aircraft positions shows that the MLAT system with the Okumura-Hata model has the highest PE error. The horizontal coordinate and altitude error obtained with the Okumura-Hata are 2.5 km and 0.6 km respectively higher than that obtained with the FSPL mode

Модифицированный алгоритм Банкрофта для систем мультилатерации

In multilateration systems, Bancroft algorithm is often used to estimate the location of objects. This algorithm is synthesized for satellite navigation systems. The algorithm allows to obtain the location estimation by means of direct method and does not require significant computing costs. These properties set it apart from algorithms using optimization approaches. However, according to the results of computer simulation, the accuracy of estimation yielded by the algorithm can be several times worse than potentially enable one. The article proposes a method for modifying the Ban-croft algorithm. Modification involves refining the Bancroft estimates by applying the method of small perturbations. The article shows that the use of the proposed modification allows to increase the accuracy of estimates by 2.5–3 times and to make it equal to the Cramer-Rao boundary. At the same time, the complexity of the modified algorithm grows in-significantly.В системах мультилатерации для оценки местоположения (МП) объектов часто используется алгоритм Банкрофта, синтезированный для оценки МП объектов в спутниковых системах навигации. Алгоритм позволяет прямым способом получить оценку МП и не требует больших вычислительных затрат при реализации. Данные свойства выгодно отличают этот алгоритм от алгоритмов, работающих на основе решения оптимизационных задач. Однако, как показывают результаты математического моделирования, точность получаемых с помощью алгоритма оценок может быть в несколько раз ниже, чем потенциально достижимая. Предлагается способ модификации алгоритма Банкрофта, который состоит в уточнении оценок Банкрофта путем применения метода малых возмущений. Показано, что использование предлагаемой модификации позволяет в 2,5–3 раза увеличить точность оценок МП объекта и сделать ее равной потенциально достижимой. При этом сложность модифицированного алгоритма возрастает незначительно