• A PORTABLE SOLUTION FOR ON-SITE ANALYSIS AND VISUALIZATION OF RACE CAR TELEMETRY DATA

      Backhaus, Christopher; Boyer, Kyle; Elmadani, Safwan; Houston, Paul; Ruckle, Sean; Marcellin, Michael; Univ Arizona (International Foundation for Telemetering, 2018-11)
      The University of Arizona Baja Racing Team competes annually in a grueling off-road racing competition designed to test the durability of each team’s vehicle. For the last several years, we have been creating and improving upon a telemetry system for the car in order to provide live data and analysis to the driver and pit crew during races, as well as to inform the design of future vehicles. This year, we have created a portable system consisting of a high-performance computer running a custom software package in a ruggedized case with a variety of networking gear. The software is built around a modular, multithreaded analysis engine and can perform live and retrospective analysis on data received from multiple sources, the results of which can be displayed using the built-in GUI or accessed via web interface.
    • SPARSE CHANNEL ESTIMATION WITH REGULARIZATION METHODS IN MASSIVE MIMO SYSTEMS

      Peken, Ture; Tandon, Ravi; Bose, Tamal; Univ Arizona (International Foundation for Telemetering, 2018-11)
      Massive multiple-input multiple-output (MIMO) technology has recently gained a lot of at- tention as a candidate technology for the next generation wireless systems. With a higher number of antennas, pilot-based channel estimation faces a limitation in the number of or- thogonal pilots to be used among users in all cells. Sparse channel estimation by using regularization methods can reduce the pilots compared to pilot-based channel estimation. In this paper, we study two regularization methods: least absolute shrinkage and selection operator (lasso) and elastic net. We investigate the performance of least squares (LS), lasso, and elastic net when the sparsity of the channel changes over time. We study the optimum tuning parameters for lasso and elastic net based channel estimators to achieve the best performance with the di erent number of pilots and values of signal-to-noise ratio (SNR). Finally, we present the asymptotic analysis of LS, lasso, and elastic net based channel esti- mators.
    • WIRING HARNESS CONSTRUCTION AND DATA PROTOCOL SELECTION FOR HIGH NOISE APPLICATIONS

      Schultz, Aaron; Marcellin, Michael; Univ Arizona (International Foundation for Telemetering, 2018-11)
      The main problem with wired data transmission is exposure to electrical noise. In environments with extremely high noise levels, special care needs to be taken in order to accurately send data between two or more devices. In the case of motorsports, extreme noise on any critical data lines can cause engine failure, putting the driver’s safety at risk. The purpose of this paper is to explain effective construction techniques for noise reduction in a wiring harness, as well as to review how certain serial data protocols will handle errors in harsh conditions.