| 1. |
- Choudhary, Vipin
(author)
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Nondestructive testing and antenna measurements using UWB radar in industrial applications
- 2021
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Licentiate thesis (other academic/artistic)abstract
- Many industries are rapidly substituting the manual test operations and move towards automated operations using modern technologies.Modern technologies such as digital cameras, sonic sensors, infrared sensors, and radar and lidar systems are used for non-destructive testingoperations. Among all the different sensors, radar systems have theability to penetrate built structures (dielectric materials), which makes them flexible and suitable for a wide range of industrial and military applications in non-destructive sensing. Such examples are the detection of damages in goods manufacturing, monitoring the health of manystructures, object detection through the wall for security purposes, etc.In particular, ultra-wide-band (UWB) radar systems are beneficial inproviding high measurement accuracy and simultaneously reduced sensitivityto passive interference (such as rain, smoke, mist etc.), immunity to external radiation and noise.The objectives of this thesis are: I) to investigate electrically small concealed structures using synthetic aperture radar (SAR), II) to determinethe complex refractive index of objects using an UWB radar system,and III) to answer to the question how we can reduce the mutual coupling (cross talk) in an UWB radar system with collocated transmitand receive antennae. In objective I, the aim is non-destructive testing of built structures, such as in concrete slab manufacturing or for use in the renovation process. In addition electrically small periodic meshes,and their orientation, could not be distinguished in conventional SAR images. The proposed polarimetric analysis method demonstrates the usefulness of the singular value decomposition (SVD) using back projection algorithm (BPA) in extracting information about shape and for classifying an electrically small object. Further in this thesis for objective II, a new method for determining the complex refractive index (or equivalently the complex relative permittivity) of objects with planar interfaces is presented. The proposed method is relatively insensitive to hardware-impairments such as frequency-dependence of antennas and analog front end. The objects can be finite in size and at a finite distance. The limits in size and distance for the method to be valid are experimentally investigated. Hence, the method is designed for industrial in-line measurements onobjects on conveyor belts. Furthermore, in the following parts of this thesis −objective III− we investigate and show how a microwave metamaterial based absorber can be used to improve the performance of aradar system for short range applications, when positioned between the transmit and receive antennas. As results, the error in estimated target distance is reduced and clutter reduction is improved.
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| 2. |
- Alizadeh, Mahmoud
(author)
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Characterisation, Modelling and Digital Pre-DistortionTechniques for RF Transmitters in Wireless Systems
- 2019
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Doctoral thesis (other academic/artistic)abstract
- Wireless systems have become an inevitable part of modern technologies serving humankind. The rapid growth towards large dimensional systems, e.g. 5th generation (5G) technologies, incurs needs for improving the performance of the systems and considering aspects to make them as far as possible environmentally friendly in terms of power efficiency, cost, and so on. One of the key parts of every wireless communication system is the radio frequency (RF) power amplifier (PA), which consumes the largest percentage of the total energy. Hence, accurate models of RF PAs can be used to optimize their design and to compensate for signal distortions. This thesis starts with two methods for frequency-domain characterisation to analyse the dynamic behaviour of PAs in 3rd-order non-linear systems. Firstly, two-tone signals superimposed on large-signals are used to analyse the frequency-domain symmetry properties of inter-modulation (IM) distortions and Volterra kernels in different dynamic regions of RF PAs in a single-input single-output (SISO) system. Secondly, three-tone signals are used to characterise the 3rd-order self- and cross-Volterra kernels of RF PAs in a 3 × 3 multiple-input multiple-output (MIMO) system. The main block structures of the models are determined by analysing the frequency-domain symmetry properties of the Volterra kernels in different three-dimensional (3D) frequency spaces. This approach significantly simplifies the structure of the 3rd-order non-linear MIMO model.The following parts of the thesis investigate techniques for behavioural modelling and linearising RF PAs. A piece-wise modelling technique is proposed to characterise the dynamic behaviour and to mitigate the impairments of non-linear RF PAs at different operating points (regions). A set of thresholds decompose the input signal into several sub-signals that drive the RF PAs at different operating points. At each operating point, the PAs are modelled by one sub-model, and hence, the complete model consists of several sub-models. The proposed technique reduces the model errors compared to conventional piece-wise modelling techniques.A block structure modelling technique is proposed for RF PAs in a MIMO system based on the results of the three-tone characterisation technique. The main structures of the 3rd- and higher-order systems are formulated based on the frequency dependence of each block. Hence, the model can describe more relevant interconnections between the inputs and outputs than conventional polynomial-type models.This thesis studies the behavioural modelling and compensation techniques in both the time and the frequency domains for RF PAs in a 3 × 3MIMO system. The 3D time-domain technique is an extension of conventional 2D generalised memory polynomial (GMP) techniques. To reduce the computational complexity, a frequency-domain technique is proposed that is efficient and feasible for systems with long memory effects. In this technique, the parameters of the model are estimated within narrow sub-bands. Each sub-band requires only a few parameters, and hence the size of the model for each sub-band is reduced.
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| 3. |
- Amin, Shoaib Amin, 1985-
(author)
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Characterization and Linearization of Multi-channel RF Power Amplifiers
- 2015
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Licentiate thesis (other academic/artistic)abstract
- The demands for high data rates and broadband wireless access require the development of wireless systems that can support wide and multi-band signals. To deploy these signals, new radio frequency (RF) front-ends are required which impose new challenges in terms of power consumption efficiency and sources of distortion e.g., nonlinearity. These challenges are more pronounced in power amplifiers (PAs) that degrade the overall performance of the RF transmitter. Since it is difficult to optimize the linearity and efficiency characteristics of a PA simultaneously, a trade-off is needed. At high input power, a PA exhibits high efficiency at the expense of linearity. On the other hand, at low input power, a PA is linear at the expense of the efficiency. To achieve linearity and efficiency at the same time, digital pre-distortion (DPD) is often used to compensate for the PA nonlinearity at high input power. In case of multi-channel PAs, input and output signals of different channels interact with each other due to cross-talk. Therefore, these PAs exhibit different nonlinear behavior than the single-input single-output (SISO) PAs. The DPD techniques developed for SISO PAs do not result in adequate performance when used for multi-channel PAs. Hence, an accurate behavioral modeling is essential for the development of DPD for multi-channel RF PAs. In this thesis, we propose three novel behavioral models and DPD schemes for nonlinear multiple-input multiple-output (MIMO) transmitters in presence of cross-talk. A study of the source of cross-talk in MIMO transmitters have been investigated to derive simple and powerful modeling schemes. These models are extensions of a SISO generalized memory polynomial model. A comparative study with a previously published MIMO model is also presented. The effect of coherent and partially non-coherent signal generationon DPD performance is also highlighted. It is shown experimentally that with partially non-coherent signal generation, the performance of the DPD degrades compared to coherent signal generation. In context of multi-channel RF transmitters, PA behavioral models and DPD schemes suffer from a large number of model parameters with the increase in nonlinear order and memory depth. This growth leads to high complexity model identification and implementation. We have designed a DPD scheme for MIMO PAs using a sparse estimation technique for reducing model complexity. This technique also increases the numerical stability when linear least square estimation model identification is used. A method to characterize the memory effects in a nonlinear concurrent dual-band PAs is also presented. Compared to the SISO PAs, concurrent dual-band PAs are not only affected by intermodulation distortions but also by cross-modulation distortions. The characterization of memory effects inconcurrent dual-band transmitter is performed by injecting a two-tone test signal in each input channel of the transmitter. Asymmetric energy surfaces are introduced for the intermodulation and cross-modulation products, which can be used to identify the power and frequency regions where the memory effects are dominant.
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| 4. |
- Choudhary, Vipin, et al.
(author)
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A Singular Value Decomposition Based Approach for Classifying Concealed Objects in Short Range Polarimetric Radar Imaging
- 2019
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In: Progress in Electromagnetics Research Symposium. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728134031 ; , s. 4109-4115
-
Conference paper (peer-reviewed)abstract
- In current research one of the main challenges in short range synthetic aperture radar (SAR) is electrically small structures and objects, which tend to unclear reinforced or through the wall objects, object orientation angle, and obscure contribution to extract the position of concealed multiple small objects. In this paper, ultra-wide-band (UWB) polarimetric radar was used to study reinforced objects and for estimation of object angle at short range. Electrically small 1D periodic mesh, 2D periodic meshes and differently oriented small objects or meshes could not be distinguished in conventional SAR images. A radar system with transmit and receive antennae mounted on a two dimensional scanning grid was used. The aim is non-destructive testing of built structures, in concrete slab manufacturing and for use in the renovation process. UWB short range radar data and images corresponding to different polarization states were analysed by using singular value decomposition (SVD). To perform decomposition, the proposed approach applies SVD to image data matrices produced from the back projection algorithm (BPA) to classify the different objects and identify the object angle. Then, sets of singular-components of different polarization states are analysed to classify objects. Also, the BPA algorithm is performed to construct the object images from the polarimetric radar signals. The object reflection varied with the polarimetric state of the UWB radar, which contributes to different object signatures (i.e., object intensity) since the object signature depends on the orientation, the size, and the number of objects. Object orientation with respect to the radar system and object anisotropy could be determined from the ratio of the different polarimetric singular-components. This proposed complex data analysis method demonstrates the usefulness of the SVD using BPA in extracting more information about and for classifying an object.
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| 5. |
- Olfat, Ehsan
(author)
-
Parameter Estimation of Nonlinearities in Future Wireless Systems
- 2018
-
Doctoral thesis (other academic/artistic)abstract
- Nowadays, our every-day life is immersed with wireless communications.From our hand-held cell-phones to televisions to navigation systems in cars, all and all are using wireless communications. This usage will even be enormouslyexpanded due to the introduction of the era of 5G-based Internet-of-Things(IoT) which consists wearables, sensors and more smart appliances.Orthogonal frequency division multiplexing is a very well-known commu-nication method which has been utilized in modern standards and technolo-gies due to its high spectral efficiency, simple frequency-domain equalization,and robustness against inter-symbol interference. Nevertheless, the major do-wnside of OFDM systems is the large fluctuations of the amplitudes of theirsignals causing high peak-to-average-power-ratio (PAPR). This forces the po-wer amplifier (PA) in the transmitter’s RF front-end to work in its saturationregion, hence introducing nonlinear distortion to the transmitted signal. Thisis particularly challenging in low-cost and low-power (and even low-weight)devices where a high-quality PA with a large dynamic range is not affordable,using complex digital processing techniques to mitigate the PAPR or to line-arize the PA is not computationally feasible, and introducing input back-offto change the operating point of the PA is not desirable due to decreasingthe power efficiency of the PA, which can be problematic because of the shortbattery-life. On the other hand, there are more resources available for a high-quality base station (or IoT gateway) in terms of power, budget, space and computational complexity, which motivates transferring all the complexity and cost to them and implement receiver-side nonlinearity estimation and compensation algorithms.To compensate the effects of a nonlinear PA on the transmitted signal and lastly detect them correctly, an iterative detection algorithm has been proposed in the literature. However, to use this algorithm successfully, thereceiver first needs to estimate the nonlinearity parameters. The importanceof this is more noticeable in the 5G-based Internet-of-Things networks, inwhich presumedly, numerous low-cost and low-power devices aim to transmitdata to a base station (or an IoT gateway).The focus of this thesis is on estimating the nonlinearity parameters al-ong with channel estimation, nonlinearity distortion mitigation, and symboldetection in future wireless systems deploying OFDM. In particular, we firstconsider an OFDM system with a limiter (clipper) communicating over anAWGN channel, and derive a maximum-likelihood estimator of the clippingamplitude. Next, we consider OFDM systems tranceiving over multi-pathfading channels, and propose a joint channel and clipping amplitude esti-mation algorithm using block-type frequency-domain pilots. Furthermore, we propose a new packet-frame consisting time-domain and frequency-domain pilots to separately estimate channel and clipping amplitude. After, we consider a broader types of memory less nonlinear PA models, and propose a jointestimation-detection algorithm to jointly estimate the nonlinearity parame-ters and channel and detect symbols. Finally, the joint channel and clipping amplitude estimation algorithm is extended to SIMO-OFDM systems. The performance of all of these algorithms are verified by means of simulations
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