205 research outputs found

    Partially adaptive array signal processing with application to airborne radar

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    3-D Beamspace ML Based Bearing Estimator Incorporating Frequency Diversity and Interference Cancellation

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    The problem of low-angle radar tracking utilizing an array of antennas is considered. In the low-angle environment, echoes return from a low flying target via a specular path as well as a direct path. The problem is compounded by the fact that the two signals arrive within a beamwidth of each other and are usually fully correlated, or coherent. In addition, the SNR at each antenna element is typically low and only a small number of data samples, or snapshots, is available for processing due to the rapid movement of the target. Theoretical studies indicates that the Maximum Likelihood (ML) method is the only reliable estimation procedure in this type of scenario. However, the classical ML estimator involves a multi-dimensional search over a multi-modal surface and is consequently computationally burdensome. In order to facilitate real time processing, we here propose the idea of beamspace domain processing in which the element space snapshot vectors are first operated on by a reduced Butler matrix composed of three orthogonal beamforming weight vectors facilitating a simple, closed-form Beamspace Domain ML (BDML) estimator for the direct and specular path angles. The computational simplicity of the method arises from the fact that the respective beams associated with the three columns of the reduced Butler matrix have all but three nulls in common. The performance of the BDML estimator is enhanced by incorporating the estimation of the complex reflection coefficient and the bisector angle, respectively, for the symmetric and nonsymmetric multipath cases. To minimize the probability of track breaking, the use of frequency diversity is incorporated. The concept of coherent signal subspace processing is invoked as a means for retaining the computational simplicity of single frequency operation. With proper selection of the auxiliary frequencies, it is shown that perfect focusing may be achieved without iterating. In order to combat the effects of strong interfering sources, a novel scheme is presented for adaptively forming the three beams which retains the feature of common nulls

    Array signal processing robust to pointing errors

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    The objective of this thesis is to design computationally efficient DOA (direction-of- arrival) estimation algorithms and beamformers robust to pointing errors, by harnessing the antenna geometrical information and received signals. Initially, two fast root-MUSIC-type DOA estimation algorithms are developed, which can be applied in arbitrary arrays. Instead of computing all roots, the first proposed iterative algorithm calculates the wanted roots only. The second IDFT-based method obtains the DOAs by scanning a few circles in parallel and thus the rooting is avoided. Both proposed algorithms, with less computational burden, have the asymptotically similar performance to the extended root-MUSIC. The second main contribution in this thesis is concerned with the matched direction beamformer (MDB), without using the interference subspace. The manifold vector of the desired signal is modeled as a vector lying in a known linear subspace, but the associated linear combination vector is otherwise unknown due to pointing errors. This vector can be found by computing the principal eigen-vector of a certain rank-one matrix. Then a MDB is constructed which is robust to both pointing errors and overestimation of the signal subspace dimension. Finally, an interference cancellation beamformer robust to pointing errors is considered. By means of vector space projections, much of the pointing error can be eliminated. A one-step power estimation is derived by using the theory of covariance fitting. Then an estimate-and-subtract interference canceller beamformer is proposed, in which the power inversion problem is avoided and the interferences can be cancelled completely

    Radar Signal Processing for Interference Mitigation

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    It is necessary for radars to suppress interferences to near the noise level to achieve the best performance in target detection and measurements. In this dissertation work, innovative signal processing approaches are proposed to effectively mitigate two of the most common types of interferences: jammers and clutter. Two types of radar systems are considered for developing new signal processing algorithms: phased-array radar and multiple-input multiple-output (MIMO) radar. For phased-array radar, an innovative target-clutter feature-based recognition approach termed as Beam-Doppler Image Feature Recognition (BDIFR) is proposed to detect moving targets in inhomogeneous clutter. Moreover, a new ground moving target detection algorithm is proposed for airborne radar. The essence of this algorithm is to compensate for the ground clutter Doppler shift caused by the moving platform and then to cancel the Doppler-compensated clutter using MTI filters that are commonly used in ground-based radar systems. Without the need of clutter estimation, the new algorithms outperform the conventional Space-Time Adaptive Processing (STAP) algorithm in ground moving target detection in inhomogeneous clutter. For MIMO radar, a time-efficient reduced-dimensional clutter suppression algorithm termed as Reduced-dimension Space-time Adaptive Processing (RSTAP) is proposed to minimize the number of the training samples required for clutter estimation. To deal with highly heterogeneous clutter more effectively, we also proposed a robust deterministic STAP algorithm operating on snapshot-to-snapshot basis. For cancelling jammers in the radar mainlobe direction, an innovative jamming elimination approach is proposed based on coherent MIMO radar adaptive beamforming. When combined with mutual information (MI) based cognitive radar transmit waveform design, this new approach can be used to enable spectrum sharing effectively between radar and wireless communication systems. The proposed interference mitigation approaches are validated by carrying out simulations for typical radar operation scenarios. The advantages of the proposed interference mitigation methods over the existing signal processing techniques are demonstrated both analytically and empirically

    MIMO Systems

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    In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

    Signals and Images in Sea Technologies

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    Life below water is the 14th Sustainable Development Goal (SDG) envisaged by the United Nations and is aimed at conserving and sustainably using the oceans, seas, and marine resources for sustainable development. It is not difficult to argue that signals and image technologies may play an essential role in achieving the foreseen targets linked to SDG 14. Besides increasing the general knowledge of ocean health by means of data analysis, methodologies based on signal and image processing can be helpful in environmental monitoring, in protecting and restoring ecosystems, in finding new sensor technologies for green routing and eco-friendly ships, in providing tools for implementing best practices for sustainable fishing, as well as in defining frameworks and intelligent systems for enforcing sea law and making the sea a safer and more secure place. Imaging is also a key element for the exploration of the underwater world for various scopes, ranging from the predictive maintenance of sub-sea pipelines and other infrastructure projects, to the discovery, documentation, and protection of sunken cultural heritage. The scope of this Special Issue encompasses investigations into techniques and ICT approaches and, in particular, the study and application of signal- and image-based methods and, in turn, exploration of the advantages of their application in the previously mentioned areas

    Multiple Antenna-based GPS Multipath Mitigation using Code Carrier Information

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐ๊ณตํ•™๋ถ€, 2013. 8. ์ตœ์ง„์˜.์—ฌ๋Ÿฌ ์‘์šฉ๋ถ„์•ผ์—์„œ ์ˆ˜ ์–ต๋Œ€์˜ GPS(Global Positioning System) ์ˆ˜์‹ ๊ธฐ๊ฐ€ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ์ง€๋งŒ, GPS์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” ์œ„์น˜๊ธฐ๋ฐ˜ ์„œ๋น„์Šค(LBS: Location Based Services)์—์„œ๋Š” ์—ฌ์ „ํžˆ ๋‹ค์ค‘๊ฒฝ๋กœ ์˜ค์ฐจ์™€ ๊ฐ™์€ ์ „ํŒŒ ๋ฐฉํ•ด๊ฐ€ ๋ฐœ์ƒํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์˜ค์ฐจ๋“ค๋กœ ์ธํ•˜์—ฌ ์ƒ๊ด€ํ•จ์ˆ˜์˜ ์™œ๊ณก์€ ๊ฑฐ๋ฆฌ ์˜ค์ฐจ๊ฐ€ ๋ฐœ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ด์œ ๋กœ ์ธํ•˜์—ฌ GPS์„ ์ด์šฉํ•œ ํ•ญ๋ฒ• ์‹œ์Šคํ…œ์—์„œ์˜ ์œ„์น˜ ์ •ํ™•๋„ ํ–ฅ์ƒ์„ ์œ„ํ•˜์—ฌ, ๋‹ค์ค‘๊ฒฝ๋กœ ์˜ค์ฐจ๋ฅผ ํšจ๊ณผ ์ ์œผ๋กœ ์ค„์ด๊ธฐ ์œ„ํ•œ ๊ฐ•์ธํ•˜๊ณ  ํ˜„์‹ค์ ์ธ ๋ฐฉ๋ฒ•์ด ์š”๊ตฌ๋œ๋‹ค. ๋‹ค์ค‘๊ฒฝ๋กœ๋Š” GPS ์‹ ํ˜ธ๊ฐ€ ์žฅ์• ๋ฌผ์— ์˜ํ•ด ๋ฐ˜์‚ฌ๋‚˜ ํšŒ์ ˆ ๋˜์–ด ์ˆ˜์‹ ๊ธฐ์— ๋„์ฐฉํ•  ๋•Œ ์ž˜ ์ผ์–ด๋‚œ๋‹ค. ๊ฐ€์‹œ๊ฒฝ๋กœ ์‹ ํ˜ธ์— ๊ฒฐํ•ฉ๋œ ๋‹ค์ค‘๊ฒฝ๋กœ ์‹ ํ˜ธ๋Š” GPS ์ˆ˜์‹ ๊ธฐ์˜ ์ƒ๊ด€ํ•จ์ˆ˜์˜ ๋ณ€ํ˜•์„ ์ผ์œผํ‚ค๋ฉฐ ๊ถ๊ทน์ ์œผ๋กœ ์ฐจ๋ณ„ํ•จ์ˆ˜์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋ฏ€๋กœ ๊ฑฐ๋ฆฌ์˜ค์ฐจ๋ฅผ ๋ฐœ์ƒ์‹œํ‚จ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ๋‹ค์ค‘๊ฒฝ๋กœ ์˜ค์ฐจ๋Š” ์œ„์„ฑํ•ญ๋ฒ• ์‹œ์Šคํ…œ์—์„œ์˜ ์œ„์น˜์ •ํ™•๋„ ํ–ฅ์ƒ์„ ์œ„ํ•ด ํ•ด๊ฒฐ ๋˜์–ด์•ผ ๋  ๋ฌธ์ œ๋กœ ์Ÿ์ ์ด ๋˜์–ด์™”๋‹ค. ์ตœ๊ทผ์—๋Š” ์ด๋Ÿฌํ•œ ์ „ํŒŒ ๊ฐ„์„ญ์‹ ํ˜ธ๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•˜์—ฌ ๋‹ค์ค‘๊ฐœ์˜ ์•ˆํ…Œ๋‚˜(Multiple Antenna)๋ฅผ ์ด์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์ด GPS ํ•ญ๋ฒ• ์‹œ์Šคํ…œ์—์„œ ์ด์šฉ๋˜๊ณ  ์žˆ๋‹ค. ํ˜„ ์‹œ์ ์—์„œ, ๋‹ค์ค‘๊ฐœ์˜ ์•ˆํ…Œ๋‚˜๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ์‘์šฉ๋ถ„์•ผ๋Š” ์ฃผ๋กœ ํ•™์ˆ ์ ์ธ ์—ฐ๊ตฌ ๋ฐ ๋ณต์žกํ•œ ๊ตฐ์‚ฌ์šฉ ์—ฐ๊ตฌ๋กœ ์ฃผ๋กœ ์ง„ํ–‰ ๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์•ˆํ…Œ๋‚˜ ์ œ์ž‘ ๋ฐฉ๋ฒ• ๋ฐ ์ „๊ธฐ์  ์‹œ์Šคํ…œ์˜ ๊ธ‰๊ฒฉํ•œ ๋ฐœ์ „์œผ๋กœ ์ธํ•ด ์ด์ „์˜ ํ•˜๋“œ์›จ์–ด ๋ฐ ์†Œํ”„์›จ์–ด์ ์ธ ๋ฌธ์ œ๋ฅผ ์‰ฝ๊ฒŒ ํ•ด๊ฒฐ ๋จ์— ๋”ฐ๋ผ ๊ฐ€๊นŒ์šด ๋ฏธ๋ž˜์—๋Š” ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ๊ธฐ๋ฐ˜์˜ ์ˆ˜์‹ ๊ธฐ๊ฐ€ ๋ฏผ๊ฐ„ ์ƒ์šฉ๋ถ„์•ผ๋กœ ํ™•๋Œ€ ๋  ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ์ด ๋œ๋‹ค. ๋˜ํ•œ ์•ˆํ…Œ๋‚˜ ์ˆ˜์‹ ๊ธฐ RF๋‹จ์˜ ์†Œํ˜•ํ™”๋กœ ์ธํ•˜์—ฌ ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ์‹œ์Šคํ…œ์—์„œ์˜ ์•ˆํ…Œ๋‚˜ ํฌ๊ธฐ ๋ฌธ์ œ์  ๋˜ํ•œ ํ•ด๊ฒฐ ๊ฐ€๋Šฅํ•˜๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋‹ค์ค‘ GPS ์•ˆํ…Œ๋‚˜๋ฅผ ์ด์šฉํ•˜์—ฌ GPS ํ•ญ๋ฒ•์—์„œ์˜ ์ „ํŒŒ ๊ฐ„์„ญ ๋ฐ ๋‹ค์ค‘๊ฒฝ๋กœ ์˜ค์ฐจ ๊ฐ์‡„์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐ•ํ•œ ์ „ํŒŒ ๊ฐ„์„ญ ๋ฐ ๋‹ค์ค‘๊ฒฝ๋กœ ์‹ ํ˜ธ์— ๋Œ€ํ•˜์—ฌ ๊ณต๊ฐ„ ์ฒ˜๋ฆฌ ๊ธฐ๋ฒ•์„ ์ ์šฉํ•œ๋‹ค. ์ œ์•ˆ๋œ ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์€ ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜๋ฅผ ๊ธฐ๋ฐ˜์˜ ์ฝ”๋“œ ์ผ€๋ฆฌ์–ด ์ •๋ณด๋ฅผ ์ด์šฉํ•œ ๊ณต๊ฐ„์ฒ˜๋ฆฌ ๊ธฐ๋ฒ•์œผ๋กœ ์ „ํŒŒ ๊ฐ„์„ญ ๋ฐ ๋‹ค์ค‘๊ฒฝ๋กœ ์˜ค์ฐจ๋ฅผ ์™„ํ™”์‹œํ‚ค๋ฉฐ, ๋˜ํ•œ ๋น”ํ˜•์„ฑ ๊ธฐ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ์‹ ํ˜ธ ๋Œ€ ์žก์Œ ๋น„์œจ์„ ์ตœ๋Œ€๋กœ ํ•œ๋‹ค. ์ œ์•ˆ๋œ ์„ฑ๋Šฅ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์†Œํ”„ํŠธ์›จ์–ด GPS ์ˆ˜์‹ ๊ธฐ๋ฅผ ์‚ฌ์šฉ๋œ๋‹ค. ์†Œํ”„ํŠธ์›จ์–ด GPS ์ˆ˜์‹ ๊ธฐ๋ฅผ ์ด์šฉํ•œ ์‹ ํ˜ธ์ฒ˜๋ฆฌ ๊ธฐ๋ฒ•์€ ์ƒˆ๋กœ์šด ์žฅ๋น„์˜ ์ œํ’ˆํ™” ๋ฐ GPS ์‹ ํ˜ธ ๋ถ„์„์— ์žฅ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ GPS ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋ถ„์„ ๋ฐ ์ˆ˜์‹ ๊ธฐ ์„ฑ๋Šฅ ํ–ฅ์ƒ ๊ฒ€์ฆ ๋“ฑ ์—ฌ๋Ÿฌ ์—ฐ๊ตฌ๋ถ„์•ผ์—์„œ ๋„๋ฆฌ ์ด์šฉ๋˜๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์˜ ์„ฑ๋Šฅ ๊ฒ€์ฆ์„ ์œ„ํ•˜์—ฌ ์ปดํ“จํ„ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ ๊ฐ€๊ณต IF ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•œ ์†Œํ”„ํŠธ์›จ์–ด ์ˆ˜์‹ ๊ธฐ ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ•œ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ์ „ํŒŒ ๊ฐ„์„ญ ๋ฐ ๋‹ค์ค‘๊ฒฝ๋กœ ์˜ค์ฐจ ๊ฐ์‡„์— ๊ฐ•์ธํ•˜๋ฉฐ, GPS ํ•ญ๋ฒ•์‹œ์Šคํ…œ์—์„œ์˜ ์œ„์น˜์ •ํ™•๋„ ํ–ฅ์ƒ์— ๊ฐ€๋Šฅ์„ฑ์„ ๋ณด์—ฌ์ค€๋‹ค. ๊ทธ๋กœ๋ฏ€๋กœ ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ์ฐจ๋Ÿ‰ ํ•ญ๋ฒ• ์‘์šฉ๋ถ„์•ผ์—์„œ ๋ฐฉํ•ด์‹ ํ˜ธ ๊ฐ์‡„์— ์‚ฌ์šฉ๋  ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋œ๋‹ค.Although hundreds of millions of receivers are used all around the world, the performance of location-based services(LBS) provided by GPS is still compromised by interference which includes unintentional distortion of correlation function due to multipath propagation. For this reason, the requirement for proper mitigation techniques becomes crucial in GPS receivers for robust, accurate, and reliable positioning. Multipath propagation can easily occur when environmental features cause combinations of reflected and diffracted replica signals to arrive at the receiving antenna. These signals which are combined with the original line-of-sight (LOS) signal can cause distortion of the receiver correlation function and ultimately distortion of the discrimination functionhence, errors in range estimation occur. Therefore, multipath error in the satellite navigation system to improve location accuracy is an important issue to be addressed. Recently, interference mitigation techniques utilizing multiple antennas have gained significant attention in GPS navigation systems. Although at the time of this dissertation, employing multiple antennas in GPS applications is mostly limited to academic research and possibly complicated military applications, it is expected that in the near future, antenna array-based receivers will also become widespread in civilian commercial markets. Rapid advances in antenna design technology and electronic systems make previously challenging problems in hardware and software easier to solve. Furthermore, due to the significant effort devoted to miniaturization of RF front-ends and antennas, the size of antenna array based receivers will no longer be a problem. Given the above, this dissertation investigates multiple antenna-based GPS the interference suppression and multipath mitigation. Firstly, a modified spatial processing technique is proposed that is capable of mitigating both high power interference and coherent and correlated GPS multipath signals. The use of spatial-temporal processing for GPS multipath mitigation is studied. A new method utilizing code carrier information based on multiple antennas is proposed to deal with highly correlated multipath components and to increase the signal to noise ratio of the beamformer by synthesizing antenna array processing. In order to verify the proposed method, a software defined GPS receiver is used. Software-based GPS signal processing technique has already produced benefits for prototyping new equipment and analyzing GPS signal quality. Not only do such receivers provide an excellent research tool for GPS algorithm verification, they also improve GPS receiver performance in a wide range of conditions. In this dissertation, the enhancement of the proposed method is presented in terms of the simulations and software defined GPS receiver using simulated IF data. From the result, the proposed method is robust to interference suppression, and multipath mitigation, and shows a strong possibility for use in improving location accuracy. Thus, this method can be employed to mitigate interference signals in vehicular navigation applications.Contents Abstract i Acknowledgements iv Contents v List of Figures x List of Tables xiv Chapter 1.Introduction 1 1.1 Introduction 1 1.2 Background and Motivation 2 1.2.1 Strong Narrowband and Wideband Interference 6 1.2.2 Multipath 7 1.3 Antenna Array Processing in GPS 11 1.3.1 Interference Suppression 11 1.3.2 Multipath Mitigation 13 1.4 Software-Defined GPS Receiver 15 1.5 Objective and Contribution 17 1.6 Dissertation Outline 18 Chapter 2. Global Positioning System 21 2.1 GPS System Overview 21 2.2 Basic Concept of GSP 25 2.3 Determining Satellite to User 28 2.4 Calculation of User Position 33 2.5 GPS Error Sources 40 2.5.1 Receiver Clock Bias 41 2.5.2 Satellite Clock Bias 42 2.5.3 Atmospheric Delay 43 2.5.4 Ephemeris Delay 46 2.5.5 Multipath Error 47 2.5.6 Receiver Noise 55 2.6 Summary 55 Chapter 3. Antenna Array Processing and Beamforming 56 3.1 Background on Antenna Arrays and Beamformers 56 3.1.1 Signal Model 59 3.2 Conventional Optimum Beamformers 69 3.2.1 Minimum Variance Distortionless Response Beamformer 69 3.2.2 Maximum Likelihood Estimator 71 3.2.3 Maximum Signal to Noise Interference Ratio Beamformer 72 3.2.4 Minimum Power Distortionless Response Beamformer 75 3.2.5 Linear Constrained Minimum Variance and Linear Constrained Minimum Power Beamformers 76 3.2.6 Eigenvector Beamformer 77 3.3 Space-Time Processing 81 3.4 Array Calibration 85 3.5 Summary 86 Chapter 4. Multipath Mitigation using Code-Carrier Information 87 4.1 Introduction 87 4.2 Interference Suppression and Multipath Mitigation 88 4.2.1 Signal Model 88 4.2.2 Interference Suppression by Subspace Projection 90 4.2.3 Multipath Mitigation by Subspace Projection 93 4.3 Determination of Multipath Satellites using Code-carrier Information 95 4.4 MSR Beamformer 100 4.5 Simulation Results 102 4.5.1 Subspace Projection and Beamforming 102 4.5.2 Performance Comparison 109 4.6 Summary 111 Chapter 5. Performance Verification using Software-Defined GPS Receiver 113 5.1 Introduction 113 5.2 Software-Defined GPS Receiver Methodology 114 5.2.1 Software-Defined GPS Receiver Signals 115 5.2.2 Software-Defined GPS Receiver Modules 116 5.3 Architecture of Software-Defined GPS Receiver 120 5.3.1 GPS Signal Generation 120 5.3.2 Interference Signal Generation 124 5.3.1 Front-End Signal Processing 125 5.4 Experimental Results 126 5.3.1 Static Environments 128 5.3.2 Dynamic Environments 133 5.5 Summary 136 Chapter 6. Conclusions and Future Work 138 6.1 Conclusions 138 6.2 Future Work 139 Bibliography 142 Appendix 168 Abstract in Korean 170 Acknowledgments 173Docto

    The electronically steerable parasitic array radiator antenna for wireless communications : signal processing and emerging techniques

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    Smart antenna technology is expected to play an important role in future wireless communication networks in order to use the spectrum efficiently, improve the quality of service, reduce the costs of establishing new wireless paradigms and reduce the energy consumption in wireless networks. Generally, smart antennas exploit multiple widely spaced active elements, which are connected to separate radio frequency (RF) chains. Therefore, they are only applicable to base stations (BSs) and access points, by contrast with modern compact wireless terminals with constraints on size, power and complexity. This dissertation considers an alternative smart antenna system the electronically steerable parasitic array radiator (ESPAR) which uses only a single RF chain, coupled with multiple parasitic elements. The ESPAR antenna is of significant interest because of its flexibility in beamforming by tuning a number of easy-to-implement reactance loads connected to parasitic elements; however, parasitic elements require no expensive RF circuits. This work concentrates on the study of the ESPAR antenna for compact transceivers in order to achieve some emerging techniques in wireless communications. The work begins by presenting the work principle and modeling of the ESPAR antenna and describes the reactance-domain signal processing that is suited to the single active antenna array, which are fundamental factors throughout this thesis. The major contribution in this chapter is the adaptive beamforming method based on the ESPAR antenna. In order to achieve fast convergent beamforming for the ESPAR antenna, a modified minimum variance distortionless response (MVDR) beamfomer is proposed. With reactance-domain signal processing, the ESPAR array obtains a correlation matrix of receive signals as the input to the MVDR optimization problem. To design a set of feasible reactance loads for a desired beampattern, the MVDR optimization problem is reformulated as a convex optimization problem constraining an optimized weight vector close to a feasible solution. Finally, the necessary reactance loads are optimized by iterating the convex problem and a simple projector. In addition, the generic algorithm-based beamforming method has also studied for the ESPAR antenna. Blind interference alignment (BIA) is a promising technique for providing an optimal degree of freedom in a multi-user, multiple-inputsingle-output broadcast channel, without the requirements of channel state information at the transmitters. Its key is antenna mode switching at the receive antenna. The ESPAR antenna is able to provide a practical solution to beampattern switching (one kind of antenna mode switching) for the implementation of BIA. In this chapter, three beamforming methods are proposed for providing the required number of beampatterns that are exploited across one super symbol for creating the channel fluctuation patterns seen by receivers. These manually created channel fluctuation patterns are jointly combined with the designed spacetime precoding in order to align the inter-user interference. Furthermore, the directional beampatterns designed in the ESPAR antenna are demonstrated to improve the performance of BIA by alleviating the noise amplification. The ESPAR antenna is studied as the solution to interference mitigation in small cell networks. Specifically, ESPARs analog beamforming presented in the previous chapter is exploited to suppress inter-cell interference for the system scenario, scheduling only one user to be served by each small BS at a single time. In addition, the ESPAR-based BIA is employed to mitigate both inter-cell and intracell interference for the system scenario, scheduling a small number of users to be simultaneously served by each small BS for a single time. In the cognitive radio (CR) paradigm, the ESPAR antenna is employed for spatial spectrum sensing in order to utilize the new angle dimension in the spectrum space besides the conventional frequency, time and space dimensions. The twostage spatial spectrum sensing method is proposed based on the ESPAR antenna being targeted at identifying white spectrum space, including the new angle dimension. At the first stage, the occupancy of a specific frequency band is detected by conventional spectrum-sensing methods, including energy detector and eigenvalue-based methods implemented with the switched-beam ESPAR antenna. With the presence of primary users, their directions are estimated at the second stage, by high-resolution angle-of-arrival (AoA) estimation algorithms. Specifically, the compressive sensing technology has been studied for AoA detection with the ESPAR antenna, which is demonstrated to provide high-resolution estimation results and even to outperform the reactance-domain multiple signal classification
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