14 research outputs found

    Interference Mitigation and Localization Based on Time-Frequency Analysis for Navigation Satellite Systems

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    Interference Mitigation and Localization Based on Time-Frequency Analysis for Navigation Satellite SystemsNowadays, the operation of global navigation satellite systems (GNSS) is imperative across a multitude of applications worldwide. The increasing reliance on accurate positioning and timing information has made more serious than ever the consequences of possible service outages in the satellite navigation systems. Among others, interference is regarded as the primary threat to their operation. Due the recent proliferation of portable interferers, notably jammers, it has now become common for GNSS receivers to endure simultaneous attacks from multiple sources of interference, which are likely spatially distributed and transmit different modulations. To the best knowledge of the author, the present dissertation is the first publication to investigate the use of the S-transform (ST) to devise countermeasures to interference. The original contributions in this context are mainly: • the formulation of a complexity-scalable ST implementable in real time as a bank of filters; • a method for characterizing and localizing multiple in-car jammers through interference snapshots that are collected by separate receivers and analysed with a clever use of the ST; • a preliminary assessment of novel methods for mitigating generic interference at the receiver end by means the ST and more computationally efficient variants of the transform. Besides GNSSs, the countermeasures to interference proposed are equivalently applicable to protect any direct-sequence spread spectrum (DS-SS) communication

    Advanced array processing techniques and systems

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    Research and development on smart antennas, which are recognized as a promising technique to improve the performance of mobile communications, have been extensive in the recent years. Smart antennas combine multiple antenna elements with a signal processing capability in both space and time to optimize its radiation and reception pattern automatically in response to the signal environment. This paper concentrates on the signal processing aspects of smart antenna systems. Smart antennas are often classified as either switched-beam or adaptive-array systems, for which a variety of algorithms have been developed to enhance the signal of interest and reject the interference. The antenna systems need to differentiate the desired signal from the interference, and normally requires either a priori knowledge or the signal direction to achieve its goal. There exists a variety of methods for direction of arrival (DOA) estimation with conflicting demands of accuracy and computation. Similarly, there are many algorithms to compute array weights to direct the maximum radiation of the array pattern toward the signal and place nulls toward the interference, each with its convergence property and computational complexity. This paper discusses some of the typical algorithms for DOA estimation and beamforming. The concept and details of each algorithm are provided. Smart antennas can significantly help in improving the performance of communication systems by increasing channel capacity and spectrum efficiency, extending range coverage, multiplexing channels with spatial division multiple access (SDMA), and compensating electronically for aperture distortion. They also reduce delay spread, multipath fading, co-channel interference, system complexity, bit error rates, and outage probability. In addition, smart antennas can locate mobile units or assist the location determination through DOA and range estimation. This capability can support and benefit many location-based services including emergency assistance, tracking services, safety services, billing services, and information services such as navigation, weather, traffic, and directory assistance

    Mutual Coupling in Phased Arrays: A Review

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    The mutual coupling between antenna elements affects the antenna parameters like terminal impedances, reflection coefficients and hence the antenna array performance in terms of radiation characteristics, output signal-to-interference noise ratio (SINR), and radar cross section (RCS). This coupling effect is also known to directly or indirectly influence the steady state and transient response, the resolution capability, interference rejection, and direction-of-arrival (DOA) estimation competence of the array. Researchers have proposed several techniques and designs for optimal performance of phased array in a given signal environment, counteracting the coupling effect. This paper presents a comprehensive review of the methods that model and mitigate the mutual coupling effect for different types of arrays. The parameters that get affected due to the presence of coupling thereby degrading the array performance are discussed. The techniques for optimization of the antenna characteristics in the presence of coupling are also included

    Neural Networks for improved signal source enumeration and localization with unsteered antenna arrays

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    Direction of Arrival estimation using unsteered antenna arrays, unlike mechanically scanned or phased arrays, requires complex algorithms which perform poorly with small aperture arrays or without a large number of observations, or snapshots. In general, these algorithms compute a sample covriance matrix to obtain the direction of arrival and some require a prior estimate of the number of signal sources. Herein, artificial neural network architectures are proposed which demonstrate improved estimation of the number of signal sources, the true signal covariance matrix, and the direction of arrival. The proposed number of source estimation network demonstrates robust performance in the case of coherent signals where conventional methods fail. For covariance matrix estimation, four different network architectures are assessed and the best performing architecture achieves a 20 times improvement in performance over the sample covariance matrix. Additionally, this network can achieve comparable performance to the sample covariance matrix with 1/8-th the amount of snapshots. For direction of arrival estimation, preliminary results are provided comparing six architectures which all demonstrate high levels of accuracy and demonstrate the benefits of progressively training artificial neural networks by training on a sequence of sub- problems and extending to the network to encapsulate the entire process

    Abstracts on Radio Direction Finding (1899 - 1995)

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    The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

    Reliable detection and characterisation of dim target via track-before-detect

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    Detection of manoeuvring and small objects is a challenging task in radar surveillance applications. Small objects in high noise background induce low signal to noise ratio (SNR) reflections. Conventional methods detect such objects by integrating multiple reflections in the same range-bearing and doppler bins in sampled versions of received signals. When the objects manoeuvre, however, these methods are likely to fail to detect them because the integration is performed without taking into account the possibility of the object movements across resolution bins. Furthermore, slowly manoeuvring objects create detection difficulties in discriminating them from radar clutter. Reflections of such objects contain micro-Doppler shifts generated by their propulsion devices. These shifts can characterise specific types of objects. In this case, estimation of these shifts is a challenging task because the front-end signals at the receiver are low SNR reflections and are the superposition of all reflections from the entire object and the noise background. Conventional estimators for this purpose only use reflections collected in a coherent processing interval (CPI) and produce poor estimate outputs. In order to achieve the desired accuracy, one requires more reflections than those collected in a CPI. This thesis mainly considers the aforementioned two difficulties and aims to develop efficient algorithms, which can detect low SNR and manoeuvring objects by incorporating long-time pulse integration and micro-doppler estimation. Main contributions in this thesis are based on the following two algorithms. The first work considers the detection of manoeuvring and small objects with radars. The radar systems are considered both co-located and separated transmitter/receiver pairs, i.e., monostatic and bistatic configurations, respectively, as well as multistatic settings involving both types. The proposed detection algorithm is capable of coherently integrating reflected signals within a CPI in all these configurations and continuing integration for an arbitrarily long time across consecutive CPIs. This approach estimates the complex value of the reflection coefficients for the integration while simultaneously estimating the object trajectory. Compounded with this simultaneous tracking and reflection coefficient estimation is the estimation of the unknown time reference shift of the separated transmitters necessary for coherent processing. The detection is made by using the resulting integration value in a Neyman-Pearson test against a constant false alarm rate threshold. The second work focuses on micro-Doppler signature estimation of manoeuvring and small rotor based unmanned aerial vehicle (UAV) systems with a monostatic radar. The micro-Doppler signature is considered rotation frequencies generated by rotating rotor blades of the UAVs. This estimation uses a maximum likelihood (ML) approach that finds rotation frequencies to maximise a likelihood function conditioned on an object trajectory, complex reflection coefficients, and rotation frequencies. In particular, the proposed algorithm uses an expectation-maximisation (EM) approach such that the expectation of the likelihood mentioned above is approximated by using the state distributions generated from Bayesian recursive filtering for the trajectory estimation. The reflection coefficients and the rotation frequencies are estimated by maximising this approximated expectation. As a result, this algorithm is capable of simultaneously tracking the trajectory and estimating the reflection coefficients and the rotation frequencies of the UAVs before the decision on the object presence is made

    Bearing estimation techniques for improved performance spread spectrum receivers

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    The main topic of this thesis is the use of bearing estimation techniques combined with multiple antenna elements for spread spectrum receivers. The motivation behind this work is twofold: firstly, this type of receiver structure may offer the ability to locate the position of a mobile radio in an urban environment. Secondly, these algorithms permit the application of space division multiple access (SDMA) to cellular mobile radio, which can offer large system capacity increases. The structure of these receivers may naturally be divided into two parts: signal detection and spatial filtering blocks. The signal detection problem involves locating the bearings of the multipath components which arise from the transmission of the desired user’s signal. There are a number of approaches to this problem, but here the MUSIC algorithm will be adopted. This algorithm requires an initial estimate of the number of signals impinging on the receiver, a task which can be performed by model order determination techniques. A major deficiency of MUSIC is its inability to resolve the highly–correlated and coherent multipath signals which frequently occur in a spread spectrum system. One of the simplest ways to overcome this problem is to employ spatial smoothing techniques, which trade the size of the antenna array for the ability to resolve coherent signals. The minimum description length (MDL) is one method for determining the signal model order and it can easily be extended to calculating the required degree of spatial smoothing. In this thesis, an approach to analysing the probability of correct model order determination for the MDL with spatial smoothing is presented. The performance of MUSIC, combined with spatial smoothing, is also of great significance. Two smoothing algorithms, spatial smoothing and forward–backward spatial smoothing, are analysed to compare their performance. If SDMA techniques are to be deployed in cellular systems, it is important to first estimate the performance improvements available from applying antenna array spatial filters. Initially, an additive white Gaussian noise channel is used for estimating the capacity of a perfect power–controlled code division multiple access system with SDMA techniques. Results suggest that the mean interference levels are almost halved as the antenna array size doubles, permitting large capacity increases. More realistic multipath models for urban cellular radio channels are also considered. If the transmitter gives rise to a number of point source multipath components, the bearing estimation receiver is able to capture the signal energy of each multipath. However, when a multipath component has significant angular spread, bearing estimation receivers need to combine separate directional components, at an increased cost in complexity, to obtain similar results to a matched filter. Finally, a source location algorithm for urban environments is presented, based on bearing estimation of multipath components. This algorithm requires accurate knowledge of the positions of the major multipath reflectors present in the environment. With this knowledge it is possible to determine the position of a transmitting mobile unit. Simulation results suggest that the algorithm is very sensitive to angular separation of the multipath components used for the source location technique

    Phobos: The design and implementation of embedded software for a low cost radar warning receiver

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    This portfolio thesis describes work undertaken by the author under the Engineering Doctorate program of the Institute for System Level Integration. It was carried out in conjunction with the sponsor company Teledyne Defence Limited. A radar warning receiver is a device used to detect and identify the emissions of radars. They were originally developed during the Second World War and are found today on a variety of military platforms as part of the platform’s defensive systems. Teledyne Defence has designed and built components and electronic subsystems for the defence industry since the 1970s. This thesis documents part of the work carried out to create Phobos, Teledyne Defence’s first complete radar warning receiver. Phobos was designed to be the first low cost radar warning receiver. This was made possible by the reuse of existing Teledyne Defence products, commercial off the shelf hardware and advanced UK government algorithms. The challenges of this integration are described and discussed, with detail given of the software architecture and the development of the embedded application. Performance of the embedded system as a whole is described and qualified within the context of a low cost system
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