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- Lanne, Maria, 1975
(författare)
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Antenna array systems : electromagnetic and signal processing aspects
- 2005
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A simple and commonly used model of an array antenna consists of identical sensors, which are equidistantly located along a line. But in reality the array antennas do not look this way. The elements are not perfectly positioned, and sometimes they are even placed on a curved surface (conformal arrays). The antenna elements are not identical, and there are active components within the array which change with time and temperature. Due to the mutual coupling, the elements will also interact. The excitation of one element will change the excitation of the neighboring elements, which means that the elements near the edges of the array will perform differently from the ones in the middle. The real world array antennas are non-planar, imperfect, finite and their performance is changed by the mutual coupling. The purpose of the present thesis is to study these aspects. The papers which this thesis is based on includes the following topics. Different shapes of conformal array antennas have been studied with an optimality criterion of maximizing the gain over the scan region, to the smallest possible cost. A calibration method for an active array antenna with replaceable transmit-receive modules has been studied. The calibration method together with the exchange of the transmit-receive modules (which are not identical) are shown to give rise to a substantial degradation of the radiation pattern. Methods to avoid these problems are suggested. The mutual coupling for an infinite array of strip dipoles has been calculated and compared to measurements on a finite array of dipoles. The performance of the elements close to the edges of an array of dipole elements has been estimated using measurements for the elements in the center of the array. The difference between the real and the ideal array is a question of electromagnetics, but in this thesis it is also studied from a signal processing perspective. Whether or not the difference is a problem is determined by if the signal processing still gives the desired result. To determine the differences and to compensate for the differences are also signal processing problems. Future work will include studies of the requirements of the mutual coupling modelling in different beam forming methods.
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| 2. |
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| 3. |
- Lanne, Maria, 1975
(författare)
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Phased array calibration and beamforming using signal processing
- 2007
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Array antennas have a wide range of applications which includesground and airborne radar, weather radar and anti-collision radar.In addition, equally important applications exist forcommunications, both on earth and to satellites in space, as wellas for medical applications such as the detection and treatment oftumors.The modern trend in array design is to use digital beamforming andto integrate the antennas with the rest of the system moreclosely. This adds new possibilities, but also contributes to makethe system expensive. To make full use of the new technology, thisthesis presents a direction dependent signal processing arraycalibration method. The new method, called local calibration, alsoallows for larger array imperfections and, possibly, a loweroverall array cost. In contrast to other non-parametriccalibration methods, the proposed method can handle positionerrors and shows good performance also for sparse calibrationgrids, which is demonstrated by high resolution direction ofarrival estimation. The local calibration has also been includedin a convex beampattern optimization, which makes it possible toachieve a uniform sidelobe level also with unknown sensor positionerrors in the array. The embedded element pattern is included inthe optimization by extracting the direction dependence of thereceived power from the calibration. Another application for thelocal calibration method is to reduce the number of necessarycalibration measurements by calculating pseudo calibration datafrom a sparse grid of measured calibration data.Array signal processing is often performed assuming Uniform LinearArrays (ULAs), although this model is far too simple to reveal thetrue behavior of array antennas. Throughout this thesis, morerealistic models including mutual coupling and array imperfectionsare used. Specifically, the impact of mutual coupling and positionerrors on the adaptive beamforming performance in linear andcircular arrays is studied. In the studied cases, the circulararray is found to be more sensitive to neglecting the mutualcoupling. Robust adaptive methods are commonly used to handlemodel uncertainties, such as unknown mutual coupling, but evenbetter performance can be achieved if these methods are combinedwith a calibration.
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| 4. |
- Lundgren, Astrid, 1978, et al.
(författare)
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Array calibration using local models
- 2006
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Ingår i: Antenn 06, Nordic Antenna Symposium. ; , s. 251-256
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 5. |
- Viberg, Mats, 1961, et al.
(författare)
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Calibration in Array Processing
- 2009
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Ingår i: Classical and Modern Direction-of-Arrival Estimation. ; , s. 93-124
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- High-resolution direction-or-arrival estimation has been an active area of research since late 1970's. The methods find a wide range of applications, including passive listening arrays, radar and sonar, and spatial (or space-time) characterization of wireless communication channels. Conventional beamforming-based techniques for direction estimation are limited by the aperture (or physical size) of the array. In contrast, parametric methods promise an unlimited resolution in theory. These methods take advantage of a precise mathematical model of the received array data, for example due to incoming plane waves. In practice, the resolution and estimation accuracy is limited by noise as well as errors in the assumed data model. The focus of this chapter is on modeling errors, and in particular calibration techniques to mitigate such errors. Perhaps the most natural and common approach is to measure the response of the array in an anechoic chamber. These calibration measurements are then used to update the data model, either in the form of explicit unknown parameters or in a non-parametric way. Under favorable conditions it is also possible to estimate the response model together with the unknown directions, so-called auto-calibration. The purpose of this chapter is to give an overview of existing techniques and discuss their respective pros and cons. We will also elaborate on how the methods can be extended to more general situations, for example including frequency and polarization dependence. It should be mentioned that practical calibration also involves hardware adjustments, to compensate for temperature drift etc. The methods considered here can be classified as software calibration, where errors are handled by adjusting the assumed data model rather than correcting for it.
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