Design and Implementation of an FMCW Radar Signal Processing Module for Automotive Applications

Suleymanov, S. (2016) Design and Implementation of an FMCW Radar Signal Processing Module for Automotive Applications.

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Abstract:In the recent years, the radar technology, once used predominantly in the military, has started to emerge in numerous civilian applications. One of the areas that this technology appeared is the automotive industry. Nowadays, we can find various radars in modern cars that are used to assist a driver to ensure a safe drive and increase the quality of the driving experience. The future of the automotive industry promises to offer a fully autonomous car which is able to drive itself without any driver assistance. These vehicles will require powerful radar sensors that can provide precise information about the surrounding of the vehicle. These sensors will also need a computing platform that can ensure real-time processing of the received signals. The subject of this thesis is to investigate the processing platforms for the real-time signal processing of the automotive FMCW radar developed at the NXP Semiconductors. The radar sensor is designed to be used in the self-driving vehicles. The thesis first investigates the signal processing algorithm for the MIMO FMCW radar. It is found that the signal processing consists of the three-dimensional FFT processing. Taking into account the algorithm and the real-time requirements of the application, the processing capability of the Starburst MPSoC, 32 core real-time multiprocessor system developed at the University of Twente, has been evaluated as a base-band processor for the signal processing. It was found that the multiprocessor system is not capable to meet the real-time constraints of the application. As an alternative processing platform, an FPGA implementation of the algorithm was proposed and implemented in the Virtex-6 FPGA. The implementations uses pre-built Xilinx IP cores as hardware components to build the architecture. The architecture also includes a MicroBlaze core which is used to generate the artificial input data for the algorithm and manage the operation of hardware components through software. The results of the implementation show that the architecture can provide reliable outputs regarding the range, velocity and bearing information. The accuracy of the results are limited by the range, velocity and angular resolution which are determined by the specific parameters of the RF front-end and the designed waveform pattern. However, the real-time performance on the architecture cannot be achieved due to the high latencies introduced by the memory transpose operations. A few techniques have been tested to decrease the latency bottleneck caused by the SDRAM transpose processes, however none of them have shown any significant improvements.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:53 electrotechnology
Programme:Embedded Systems MSc (60331)
Link to this item:http://purl.utwente.nl/essays/70986
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