Modern day cars are often equipped with a vision system that collects informa- tion about the car and its surroundings. Camera calibration is extremely impor- tant in order to maintain high accuracy in an automotive safety applications. The cameras are calibrated offline in the factory, however the mounting of the camera may change slowly over time. If the angles of the actual mounting of the cam- era are known compensation for the angles can be done in software. Therefore, online calibration is desirable. This master’s thesis describes how to dynamically calibrate the roll angle. Two different methods have been implemented and compared.The first detects verti- cal edges in the image, such as houses and lamp posts. The second one method detects license plates on other cars in front of the camera in order to calculate the roll angle. The two methods are evaluated and the results are discussed. The results of the methods are very varied, and the method that turned out to give the best results was the one that detects vertical edges.

In practice, there exist many error sources which distort the antenna array pattern. For example, elements of antenna arrays influence each other (known as mutual coupling), mismatches in cables and element positions affects the antenna radiation pattern and also unequal gain and phase characteristics of RF receiver distorts the received signal. These effects generally degrade the array performance. They cause an increase in sidelobe levels with an accompanying decrease in gain. Also, these errors limit the performance of direction finding (DF) algorithms. So, in order to have low sidelobe level, good performance in direction finding and beamforming, calibration is necessary. In the literature, there exist many algorithms proposed for the calibration of errors. Calibration method used in this thesis assumes that there is a linear transformation between ideal signal and measurements. Calibration matrix is formed by using measurements. In this work, we look for the adequate number of measurements for successful calibration. Performance of calibration method may depend on the angle interval from which measurements are taken. So, the width of the data collection angle interval is also studied. Moreover, in real life, measurements can be collected from equally or randomly spaced angles. Does it affect the performance of calibration? The answer of this question is also inspected in this thesis. Additionally, the performance of algorithm under noise is studied. Performance evaluation is done for both elevation and azimuth sectors. Simulations are carried out on MATLABTM and Ansoft HFSS software package.

DCU2 (Drive Control Unit 2) is an important control system used in applications for train systems that are configured by a set of parameters. Traditionally, parameterization is conducted by using an excel workbook during the software development. The parameters are set up and further export the parameters to the compilation step. Such approach has a number of disadvantages, e.g., delays on the validation and verification steps, system configuration overhead, and suboptimal system reliability generated by the parameter configurations. To improve the parameterization process, this thesis implements a model-based software architecture approach and automotive industry standards via rapid prototyping by using scrum methodology. We do this by using Matlab/Simulink, TDL (Time Description Language) and UML (Unified Modeling Language) architectural description languages to enable different views of the software architecture. We then develop different prototypes that implement ASAM (Association for Standardization of Automation and Measuring Systems) standards like XCP protocol over Ethernet (code ASAM MCD-1 XCP V1.1.0) and ASAP2 (code ASAM MCD-2 MC) in every scrum sprint. An evaluation then shows that the thesis successfully implements previously defined standards that use commercial tools from e.g., Vector, proving that the parameter‟s unit control can be handled via online calibration and measurement, leading to a significant improvement in Bombardier‟s software development process in a distributed development environment.

This master thesis project was done together with Saab Dynamics in Linköping the spring of 2022 and aims to perform an online IMU-camera calibration using an AprilTag board. Experiments are conducted on two different types of datasets, the public dataset Euroc and internal datasets from Saab. The calibration is done iteratively by solving a series of nonlinear optimization problems without any initial knowledge of the sensor configuration. The method is largely based on work by Huang and collaborators. Other than just finding the transformation between the IMU and the camera, the biases in the IMU, and the time delay between the two sensors are also explored. By comparing the resulting transformation with Kalibr, the current state of the art offline calibration toolbox, it is possible to conclude that the model can find and correct for the biases in the gyroscope. Therefore it is important to include these biases in the model. The model is able to roughly find the time shift between the two sensors but has more difficulties correcting for it. The thesis also aims to explore ways of compiling a good dataset for calibration. Results show that it is desirable to avoid rapid movements as well as images gathered at distances from the AprilTag board that very a lot. Also, having a shorter exposure time is useful to not lose AprilTag detections.

本論文探討當自變數存在測量誤差時，羅吉斯迴歸模型的估計問題，並將此結果應用在電腦化適性測驗中的線上校準問題。在變動長度電腦化測驗的假設下，我們證明了估計量的強收斂性。試題反應理論被廣泛地使用在電腦化適性測驗上，其假設受試者在試題的表現情形與本身的能力，可以透過試題特徵曲線加以詮釋，羅吉斯迴歸模式是最常見的試題反應模式。藉由適性測驗的施行，考題的選取可以依據不同受試者，選擇最適合的題目。因此，相較於傳統測驗而言，在適性測驗中，題目的消耗量更為快速。在題庫的維護與管理上，新試題的補充與試題校準便為非常重要的工作。線上試題校準意指在線上測驗進行中，同時進行試題校準。因此，受試者的能力估計會存在測量誤差。從統計的觀點，線上校準面臨的困難，可以解釋為在非線性模型下，當自變數有測量誤差時的實驗設計問題。我們利用序貫設計降低測量誤差，得到更精確的估計，相較於傳統的試題校準，可以節省更多的時間及成本。我們利用處理測量誤差的技巧，進一步應用序貫設計的方法，處理在線上校準中，受試者能力存在測量誤差的問題。 / In this dissertation, we focus on the estimate in logistic regression models when the independent variables are subject to some measurement errors. The problem of this dissertation is motivated by online calibration in Computerized Adaptive Testing (CAT). We apply the measurement error model techniques and adaptive sequential design methodology to the online calibration problem of CAT. We prove that the estimates of item parameters are strongly consistent under the variable length CAT setup. In an adaptive testing scheme, examinees are presented with different sets of items chosen from a pre-calibrated item pool. Thus the speed of attrition in items will be very fast, and replenishing of item pool is essential for CAT. The online calibration scheme in CAT refers to estimating the item parameters of new, un-calibrated items by presenting them to examinees during the course of their ability testing together with previously calibrated items. Therefore, the estimated latent trait levels of examinees are used as the design points for estimating the parameter of the new items, and naturally these designs, the estimated latent trait levels, are subject to some estimating errors. Thus the problem of the online calibration under CAT setup can be formulated as a sequential estimation problem with measurement errors in the independent variables, which are also chosen sequentially. Item Response Theory (IRT) is the most commonly used psychometric model in CAT, and the logistic type models are the most popular models used in IRT based tests. That's why the nonlinear design problem and the nonlinear measurement error models are involved. Sequential design procedures proposed here can provide more accurate estimates of parameters, and are more efficient in terms of sample size (number of examinees used in calibration). In traditional calibration process in paper-and-pencil tests, we usually have to pay for the examinees joining the pre-test calibration process. In online calibration, there will be less cost, since we are able to assign new items to the examinees during the operational test. Therefore, the proposed procedures will be cost-effective as well as time-effective.