Separation of SSR signals by array processing in multilateration systems

Location and identification of cooperating aircraft in the airport area (and beyond) may be implemented by multilateration (MLAT) systems using the secondary surveillance radar (SSR) mode S signals. Most of these signals, spontaneously emitted from on-board mode S transponders at a fixed carrier frequency, arrive randomly at the receiving station, as well as many mode A/C replies from legacy transponders still in use. Several SSR signals are, then, overlapped in multiple aircraft situations. Therefore, the aim of this work is the separation of overlapped SSR signals, i.e., signals superimposed in time at receiving stations. We improve the MLAT receiving station by replacing the single antenna by an array of m elements and using array signal processing techniques. In the literature, several algorithms address the general source separation problem, but a very few of them are specifically designed for a mixture of overlapping SSR replies. Unfortunately, all of them have either some shortcomings, or an expensive computational cost, or no simple practical implementation. In this paper, we use the time sparsity property of the sources to propose more reliable, simpler, and more effective algorithms based on projection techniques to separate multiple SSR signals. Real recorded signals in a live environment are used to demonstrate the effectiveness of our method

Coherent source separation based on sparsity: an application to SSR signals

Systems based on secondary surveillance radar (SSR) downlink signals, both with directional and with omni-directional antennae (such as in multilateration), are operational today and more and more installations are being planned. In this frame, high-density traffic leads to the reception of a mixture of several overlapping SSR replies. By nature, SSR sources are sparse, i.e. with amplitude equal to zero with significantly high probability. While in the literature several algorithms performing sources separation with an m-element antenna have been proposed, none has satisfactorily employed the full potential of sparsity for SSR signals. Most sparsity algorithms can separate only real-valued sources, although we present in this study two algorithms to separate the complex-valued SSR sources. Recorded signals in a live environment are used to demonstrate the effectiveness of the proposed techniques. Copyright © Cambridge University Press and the European Microwave Association 2009

The applications of satellites to communications, navigation and surveillance for aircraft operating over the contiguous United States. Volume 1 - Technical report

Satellite applications to aircraft communications, navigation, and surveillance over US including synthesized satellite network and aircraft equipment for air traffic contro

Identification of high-level functional/system requirements for future civil transports

In order to accommodate the rapid growth in commercial aviation throughout the remainder of this century, the Federal Aviation Administration (FAA) is faced with a formidable challenge to upgrade and/or modernize the National Airspace System (NAS) without compromising safety or efficiency. A recurring theme in both the Aviation System Capital Investment Plan (CIP), which has replaced the NAS Plan, and the new FAA Plan for Research, Engineering, and Development (RE&D) rely on the application of new technologies and a greater use of automation. Identifying the high-level functional and system impacts of such modernization efforts on future civil transport operational requirements, particularly in terms of cockpit functionality and information transfer, was the primary objective of this project. The FAA planning documents for the NAS of the 2005 era and beyond were surveyed; major aircraft functional capabilities and system components required for such an operating environment were identified. A hierarchical structured analysis of the information processing and flows emanating from such functional/system components were conducted and the results documented in graphical form depicting the relationships between functions and systems

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

Separation of multiple secondary surveillance radar sources in a real environment for the near-far case

Multilateration systems based on Secondary Surveillance Radar (SSR) systems and omni-directional antennae are operational today [1,2]. Assuming the replacement of the single-element antenna by an array, we proposed new algorithms to discriminate overlapped signals in previous works [3,4,5]; other solutions were also proposed in the literature [6,7,8]. Unfortunately, all have either some shortcomings, or an expensive computational cost, or no simple practical implementation. Therefore, we proposed in [9] a reliable, simple, and effective projection algorithm. Nevertheless, some issues were overlooked: in particular the relative power ratio between the signals to be separated may be important, which we study in this paper with real-life signals

Improved MDA, a case for de-garbling SSR mode S replies

Multilateration (MLAT) and Automatic Dependent Surveillance – Broadcast (ADS-B) systems exploiting the Secondary Surveillance Radar (SSR) channel suffer from garbling. This means that if two or more mode S signals impinge on the receiver at the same or very near time they could not be decoded. To alleviate this problem, many solutions have been proposed, one in particular [1] is effective for a large variety of scenarios, but excluding the cases when the replies are too much separated in time. Recently a paper [2] focused on linear algebra presented a potential solution for this case. In this work we present a practical application for the case of two mode S signals