文件名称:
Radar Signal Processing Design and Implementation for Machine Learning
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上传时间: 2019-07-01
详细说明：Radar Signal Processing Design and Implementation for Machine Learningabstract
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 mee
t the real-time constraints of the applicati
As an alternative processing platform, an FPGa implement ation of the
algorithm was proposed and implemented in the virtex-6 FPGA. The imple-
mentations uses pre-built Xilinx IP cores as hardware components to build
the architecture. The architecture also includes a micro blaze core which is
lsed 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 resolu
ABSTrAcT
tion 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 improvenents
Contents
Abstrac
List of Figure
List of Tables
List of Acronyms
工
ntroduction
1.1 Context
1.2 FMCW Radar Fundamentals
112
1. 3 Research platform
1.1 ProbleIn description
2 FMCW Signal Processing
2.1 FMCW Signal analysis
2.2 MIMO Radar Concept
15
2.2.1 MIMO Signal Modell
15
3 Requirements
3.1 Matlab model
3.2 Computational Analysis
3.3 Architecture Considerations
22
4 Signal-flow Analysis.
24
4 System Implementation
29
4. 1 The algorithm
29
4. 2 The hardware components
31
FFT Corel
④:2,2 AXI DMA Core
4.2.3 Memory Interface Corel
33
4.2.4 Microblaze Corel
33
CONTENTS
4. 3 The architecture and operation
5 Results and Analysis
39
,— Results
39
ha
ardware Resource Usage
.,39
⑤J2ests......
⑤L3 Performance
5.2 Analysis
43
5.2.1 Evaluation
6 Conclusion
47
6
onclusion
6.2 Future Workl
List of Figures
FMCW radar block diagram
4
1.2 Xilinx ML605 development board
1.3 NXP Semiconductor's automotive radar chip
2.1 FMCW sawtooth signal model
2.2 FMCW signal 2D FFT processing
14
2.3 Principle of phase interferometry [1
14
2.4 TX and RX antennas of Mimo rada
2.5 Virtual antenna array ......
10
3. 1 Range-Doppler Spectrum
20
3. 2 Birdseye view
3. 3 Radar scannings
24
3. 4 Signal Flow Graph of 3D FFT Procesing
25
1 Sigal processing algorithinl flowchart
31
4.2 The architecture of the inplementation
34
8 An example transpose operation
35
5. 1 Processes and their performance
Vll
LIST OF FIGURES
List of tables
2.1 Parameter table
12
5.1 Resourcc usage of the architecture
40
5.2 Radar test results
5.3 Timing results of the implementation
LIST OF TABLES
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