230 research outputs found
์ค์๊ฐ ๊ทผ๊ฑฐ๋ฆฌ ์์ํ๋ฅผ ์ํ MIMO ์ญํฉ์ฑ ๊ฐ๊ตฌ ๋ ์ด๋ ์์คํ
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๊ณต๊ณผ๋ํ ์ ๊ธฐยท์ ๋ณด๊ณตํ๋ถ, 2022. 8. ๋จ์์ฑ.Microwave and millimeter wave (micro/mmW) imaging systems have advantages over other imaging systems in that they have penetration properties over non-metallic structures and non-ionization. However, these systems are commercially applicable in limited areas. Depending on the quality and size of the images, a system can be expensive and images cannot be provided in real-time. To overcome the challenges of the current micro/mmW imaging system, it is critical to suggest a new system concept and prove its potential benefits and hazards by demonstrating the testbed. This dissertation presents Ku1DMIC, a wide-band micro/mmW imaging system using Ku-band and 1D-MIMO array, which can overcome the challenges above. For cost-effective 3D imaging capabilities, Ku1DMIC uses 1D-MIMO array configuration and inverse synthetic aperture radar (ISAR) technique. At the same time, Ku1DMIC supports real-time data acquisition through a system-level design of a seamless interface with frequency modulated continuous wave (FMCW) radar. To show the feasibility of 3D imaging with Ku1DMIC and its real-time capabilities, an accelerated imaging algorithm, 1D-MIMO-ISAR RSA, is proposed and demonstrated. The detailed contributions of the dissertation are as follows.
First, this dissertation presents Ku1DMIC โ a Ku-band MIMO frequency-modulated continuous-wave (FMCW) radar experimental platform with real-time 2D near-field imaging capabilities. The proposed system uses Ku-band to cover the wider illumination area given the limited number of antennas and uses a fast ramp and wide-band FMCW waveform for rapid radar data acquisition while providing high-resolution images. The key design aspect behind the platform is stability, reconfigurability, and real-time capabilities, which allows investigating the exploration of the systemโs strengths and weaknesses. To satisfy the design aspect, a digitally assisted platform is proposed and realized based on an AMD-Xilinx UltraScale+ Radio Frequency System on Chip (RFSoC). The experimental investigation for real-time 2D imaging has proved the ability of video-rate imaging at around 60 frames per second.
Second, a waveform digital pre-distortion (DPD) method and calibration method are proposed to enhance the image quality. Even if a clean FMCW waveform is generated with the aid of the optimized waveform generator, the signal will inevitably suffer from distortion, especially in the RF subsystem of the platform. In near-field imaging applications, the waveform DPD is not effective at suppressing distortion in wide-band FMCW radar systems. To solve this issue, the LO-DPD architecture and binary search based DPD algorithm are proposed to make the waveform DPD effective in Ku1DMIC. Furthermore, an image-domain optimization correction method is proposed to compensate for the remaining errors that cannot be eliminated by the waveform DPD. For robustness to various unwanted signals such as noise and clutter signals, two regularized least squares problems are applied and compared: the generalized Tikhonov regularization and the total variation (TV) regularization. Through various 2D imaging experiments, it is confirmed that both methods can enhance the image quality by reducing the sidelobe level.
Lastly, the research is conducted to realize real-time 3D imaging by applying the ISAR technique to Ku1DMIC. The realization of real-time 3D imaging using 1D-MIMO array configuration is impactful in that this configuration can significantly reduce the costs of the 3D imaging system and enable imaging of moving objects. To this end, the signal model for the 1D-MIMO-ISAR configuration is presented, and then the 1D-MIMO-ISAR range stacking algorithm (RSA) is proposed to accelerate the imaging reconstruction process. The proposed 1D-MIMO-ISAR RSA can reconstruct images within hundreds of milliseconds while maintaining almost the same image quality as the back-projection algorithm, bringing potential use for real-time 3D imaging. It also describes strategies for setting ROI, considering the real-world situations in which objects enter and exit the field of view, and allocating GPU memory. Extensive simulations and experiments have demonstrated the feasibility and potential benefits of 1D-MIMO-IASR configuration and 1D-MIMO-ISAR RSA.๋ง์ดํฌ๋กํ ๋ฐ ๋ฐ๋ฆฌ๋ฏธํฐํ(micro/mmW) ์์ํ ์์คํ
์ ๋น๊ธ์ ๊ตฌ์กฐ ๋ฐ ๋น์ด์จํ์ ๋นํด ์นจํฌ ํน์ฑ์ด ์๋ค๋ ์ ์์ ๋ค๋ฅธ ์ด๋ฏธ์ง ์์คํ
์ ๋นํด ์ฅ์ ์ด ์๋ค.
๊ทธ๋ฌ๋ ์ด๋ฌํ ์์คํ
์ ์ ํ๋ ์์ญ์์๋ง ์์
์ ์ผ๋ก ์ ์ฉ๋๊ณ ์๋ค. ์ด๋ฏธ์ง์ ํ์ง๊ณผ ํฌ๊ธฐ์ ๋ฐ๋ผ ์์คํ
์ด ๋งค์ฐ ๊ณ ๊ฐ์ผ ์ ์์ผ๋ฉฐ ์ด๋ฏธ์ง๋ฅผ ์ค์๊ฐ์ผ๋ก ์ ๊ณตํ ์ ์๋ ํํฉ์ด๋ค.
ํ์ฌ์ micro/mmW ์ด๋ฏธ์ง ์์คํ
์ ๋ฌธ์ ๋ฅผ ๊ทน๋ณตํ๋ ค๋ฉด ์๋ก์ด ์์คํ
๊ฐ๋
์ ์ ์ํ๊ณ ํ
์คํธ๋ฒ ๋๋ฅผ ์์ฐํ์ฌ ์ ์ฌ์ ์ธ ์ด์ ๊ณผ ์ํ์ ์
์ฆํ๋ ๊ฒ์ด ์ค์ํ๋ค.
๋ณธ ๋
ผ๋ฌธ์์๋ Ku-band์ 1D-MIMO ์ด๋ ์ด๋ฅผ ์ด์ฉํ ๊ด๋์ญ micro/mmW ์ด๋ฏธ์ง ์์คํ
์ธ Ku1DMIC๋ฅผ ์ ์ํ์ฌ ์์ ๊ฐ์ ๋ฌธ์ ์ ์ ๊ทน๋ณตํ ์ ์๋ค.
๋น์ฉ ํจ์จ์ ์ธ 3์ฐจ์ ์์ํ ๊ธฐ๋ฅ์ ์ํด Ku1DMIC๋ 1D-MIMO ๋ฐฐ์ด ๊ธฐ์ ๊ณผ ISAR(Inverse Synthetic Aperture Radar) ๊ธฐ์ ์ ์ฌ์ฉํ๋ค.
๋์์ Ku1DMIC๋ ์ฃผํ์ ๋ณ์กฐ ์ฐ์ํ (FMCW) ๋ ์ด๋์์ ์ํํ ์ธํฐํ์ด์ค์ ์์คํ
์์ค ์ค๊ณ๋ฅผ ํตํด ์ค์๊ฐ ๋ฐ์ดํฐ ์์ง์ ์ง์ํ๋ค.
Ku1DMIC๋ฅผ ์ฌ์ฉํ 3์ฐจ์ ์์ํ์ ๊ตฌํ ๋ฐ ์ค์๊ฐ ๊ธฐ๋ฅ์ ๊ฐ๋ฅ์ฑ์ ๋ณด์ฌ์ฃผ๊ธฐ ์ํด, 2์ฐจ์ ์์ํ๋ฅผ ์ํ 1D-MIMO RSA๊ณผ 3์ฐจ์ ์์ํ๋ฅผ ์ํ 1D-MIMO-ISAR RSA๊ฐ ์ ์๋๊ณ Ku1DMIC์์ ๊ตฌํ๋๋ค.
๋ฐ๋ผ์, ๋ณธ ํ์ ๋
ผ๋ฌธ์ ์ฃผ์ ๊ธฐ์ฌ๋ Ku-band 1D-MIMO ๋ฐฐ์ด ๊ธฐ๋ฐ ์์ํ ์์คํ
ํ๋กํ ํ์
์ ๊ฐ๋ฐ ๋ฐ ํ
์คํธํ๊ณ , ISAR ๊ธฐ๋ฐ 3์ฐจ์ ์์ํ ๊ธฐ๋ฅ์ ๊ฒ์ฌํ๊ณ , ์ค์๊ฐ 3์ฐจ์ ์์ํ ๊ฐ๋ฅ์ฑ์ ์กฐ์ฌํ๋ ๊ฒ์ด๋ค.
์ด์ ๋ํ ์ธ๋ถ์ ์ธ ๊ธฐ์ฌ ํญ๋ชฉ์ ๋ค์๊ณผ ๊ฐ๋ค.
์ฒซ์งธ, ์ค์๊ฐ 2D ๊ทผ๊ฑฐ๋ฆฌ์ฅ ์ด๋ฏธ์ง ๊ธฐ๋ฅ์ ๊ฐ์ถ Ku ๋์ญ MIMO ์ฃผํ์ ๋ณ์กฐ ์ฐ์ํ(FMCW) ๋ ์ด๋ ์คํ ํ๋ซํผ์ธ Ku1DMIC๋ฅผ ์ ์ํ๋ค.
์ ์ํ๋ ์์คํ
์ ์ ํ๋ ์์ ์ํ
๋์์ ๋ ๋์ ์กฐ๋ช
์์ญ์ ์ปค๋ฒํ๊ธฐ ์ํด Ku ๋์ญ์ ์ฌ์ฉํ๊ณ ๊ณ ํด์๋ ์ด๋ฏธ์ง๋ฅผ ์ ๊ณตํ๋ฉด์ ๋น ๋ฅธ ๋ ์ด๋ ๋ฐ์ดํฐ ์์ง์ ์ํด ๊ณ ์ ๋จํ ๋ฐ ๊ด๋์ญ FMCW ํํ์ ์ฌ์ฉํ๋ค.
ํ๋ซํผ์ ํต์ฌ ์ค๊ณ ์์น์ ์์ ์ฑ, ์ฌ๊ตฌ์ฑ ๊ฐ๋ฅ์ฑ ๋ฐ ์ค์๊ฐ ๊ธฐ๋ฅ์ผ๋ก ์์คํ
์ ๊ฐ์ ๊ณผ ์ฝ์ ์ ๊ด๋ฒ์ํ๊ฒ ํ์ํ๋ค.
์ค๊ณ ์์น์ ๋ง์กฑ์ํค๊ธฐ ์ํด AMD-Xilinx UltraScale+ RFSoC(Radio Frequency System on Chip)๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ๋์งํธ ์ง์ ํ๋ซํผ์ ์ ์ํ๊ณ ๊ตฌํํ๋ค.
์ค์๊ฐ 2D ์ด๋ฏธ์ง์ ๋ํ ์คํ์ ์กฐ์ฌ๋ ์ด๋น ์ฝ 60ํ๋ ์์์ ๋น๋์ค ์๋ ์ด๋ฏธ์ง์ ๋ฅ๋ ฅ์ ์
์ฆํ๋ค.
๋์งธ, ์์ ํ์ง ํฅ์์ ์ํ ํํ ๋์งํธ ์ ์น์๊ณก(DPD) ๋ฐฉ๋ฒ๊ณผ ๋ณด์ ๋ฐฉ๋ฒ์ ์ ์ํ๋ค.
์ต์ ํ๋ ํํ ๋ฐ์๊ธฐ์ ๋์์ผ๋ก ๊นจ๋ํ FMCW ํํ์ด ์์ฑ๋๋๋ผ๋ ํนํ ํ๋ซํผ์ RF ํ์ ์์คํ
์์ ์ ํธ๋ ํ์ฐ์ ์ผ๋ก ์๊ณก์ ๊ฒช๊ฒ๋๋ค.
๊ทผ๊ฑฐ๋ฆฌ ์์ํ ์์ฉ ๋ถ์ผ์์๋ ํํ DPD๋ ๊ด๋์ญ FMCW ๋ ์ด๋ ์์คํ
์ ์๊ณก์ ์ต์ ํ๋ ๋ฐ ํจ๊ณผ์ ์ด์ง ์๋ค.
์ด ๋ฌธ์ ๋ฅผ ํด๊ฒฐํ๊ธฐ ์ํด Ku1DMIC์์ ํํ DPD๊ฐ ์ ํจํ๋๋ก LO-DPD ์ํคํ
์ฒ์ ์ด์ง ํ์ ๊ธฐ๋ฐ DPD ์๊ณ ๋ฆฌ์ฆ์ ์ ์ํ๋ค.
๋ํ, ํํ DPD๋ก ์ ๊ฑฐํ ์ ์๋ ๋๋จธ์ง ์ค๋ฅ๋ฅผ ๋ณด์ํ๊ธฐ ์ํด ์ด๋ฏธ์ง ์์ญ ์ต์ ํ ๋ณด์ ๋ฐฉ๋ฒ์ ์ ์ํ๋ค.
๋
ธ์ด์ฆ ๋ฐ ํด๋ฌํฐ ์ ํธ์ ๊ฐ์ ๋ค์ํ ์์น ์๋ ์ ํธ์ ๋ํ ๊ฒฌ๊ณ ์ฑ์ ์ํด ์ผ๋ฐํ๋ Tikhonov ์ ๊ทํ ๋ฐ ์ ์ฒด ๋ณ๋(TV) ์ ๊ทํ๋ผ๋ ๋ ๊ฐ์ง ์ ๊ทํ๋ ์ต์ ์์น ๋ฌธ์ ๋ฅผ ์ ์ฉ ํ ๋น๊ตํ๋ค.
๋ค์ํ 2์ฐจ์ ์์ํ ์คํ์ ํตํด ๋ ๋ฐฉ๋ฒ ๋ชจ๋ ๋ถ์ฝ ๋ ๋ฒจ์ ์ค์ฌ ํ์ง์ ํฅ์์ํฌ ์ ์์์ ํ์ธํ๋ค.
๋ง์ง๋ง์ผ๋ก, ISAR ๊ธฐ๋ฒ์ 2์ฐจ์ ์์ ํ๋ซํผ์ ์ ์ฉํ์ฌ ์ค์๊ฐ 3์ฐจ์ ์์์ ๊ตฌํํ๊ธฐ ์ํ ์ฐ๊ตฌ๋ฅผ ์งํํ๋ค.
1D-MIMO-ISAR ๊ตฌ์ฑ์์ ์ค์๊ฐ 3D ์ด๋ฏธ์ง์ ๊ตฌํ์ ์ด๋ฌํ ๊ตฌ์ฑ์ด 3D ์ด๋ฏธ์ง ์์คํ
์ ๋น์ฉ์ ํฌ๊ฒ ์ค์ผ ์ ์๋ค๋ ์ ์์ ์ํฅ๋ ฅ์ด ์๋ค.
๋ฐ๋ผ์ ์ด ๋
ผ๋ฌธ์์๋ 1D-MIMO-ISAR ๊ตฌ์ฑ์ ๋ํ ์ด๋ฏธ์ง ์ฌ๊ตฌ์ฑ์ ๊ฐ์ํํ๊ธฐ ์ํด 1D-MIMO-ISAR ๋ฒ์ ์คํํน ์๊ณ ๋ฆฌ์ฆ(RSA)์ ์ ์ํ๋ค.
์ ์๋ 1D-MIMO-ISAR RSA๋ ๋๋ฆฌ ์๋ ค์ง Back-Projection ์๊ณ ๋ฆฌ์ฆ๊ณผ ๊ฑฐ์ ๋์ผํ ์ด๋ฏธ์ง ํ์ง์ ์ ์งํ๋ฉด์๋ ์๋ฐฑ ๋ฐ๋ฆฌ์ด ์ด๋ด์ ์ด๋ฏธ์ง๋ฅผ ์ฌ๊ตฌ์ฑํจ์ผ๋ก์จ ์ค์๊ฐ ์์ํ์ ๋ํ ๊ฐ๋ฅ์ฑ์ ๋ณด์ฌ์ค๋ค.
๋ํ ๋ฌผ์ฒด๊ฐ ์์ผ์ ๋ค์ด์ค๊ณ ๋๊ฐ๋ ์ค์ ์ํฉ์ ๊ณ ๋ คํ๊ธฐ ์ํ ROI ์ค์ , ๊ทธ๋ฆฌ๊ณ ๋ฉ๋ชจ๋ฆฌ ํ ๋น์ ๋ํ ์ ๋ต์ ์ค๋ช
ํ๋ค.
๊ด๋ฒ์ํ ์๋ฎฌ๋ ์ด์
๊ณผ ์คํ์ ํตํด 1D-MIMO-IASR ๊ตฌ์ฑ ๋ฐ 1D-MIMO-ISAR RSA์ ๊ฐ๋ฅ์ฑ๊ณผ ์ ์ฌ์ ์ด์ ์ ํ์ธํ๋ค.1 INTRODUCTION 1
1.1 Microwave and millimeter-wave imaging 1
1.2 Imaging with radar system 2
1.3 Challenges and motivation 5
1.4 Outline of the dissertation 8
2 FUNDAMENTAL OF TWO-DIMENSIONAL IMAGING USING A MIMO RADAR 9
2.1 Signal model 9
2.2 Consideration of waveform 12
2.3 Image reconstruction algorithm 16
2.3.1 Back-projection algorithm 16
2.3.2 1D-MIMO range-migration algorithm 20
2.3.3 1D-MIMO range stacking algorithm 27
2.4 Sampling criteria and resolution 31
2.5 Simulation results 36
3 MIMO-FMCW RADAR IMPLEMENTATION WITH 16 TX - 16 RX ONE- DIMENSIONAL ARRAYS 46
3.1 Wide-band FMCW waveform generator architecture 46
3.2 Overall system architecture 48
3.3 Antenna and RF transceiver module 53
3.4 Wide-band FMCW waveform generator 55
3.5 FPGA-based digital hardware design 63
3.6 System integration and software design 71
3.7 Testing and measurement 75
3.7.1 Chirp waveform measurement 75
3.7.2 Range profile measurement 77
3.7.3 2-D imaging test 79
4 METHODS OF IMAGE QUALITY ENHANCEMENT 84
4.1 Signal model 84
4.2 Digital pre-distortion of chirp signal 86
4.2.1 Proposed DPD hardware system 86
4.2.2 Proposed DPD algorithm 88
4.2.3 Measurement results 90
4.3 Robust calibration method for signal distortion 97
4.3.1 Signal model 98
4.3.2 Problem formulation 99
4.3.3 Measurement results 105
5 THREE-DIMENSIONAL IMAGING USING 1-D ARRAY SYSTEM AND ISAR TECHNIQUE 110
5.1 Formulation for 1D-MIMO-ISAR RSA 111
5.2 Algorithm implementation 114
5.3 Simulation results 120
5.4 Experimental results 122
6 CONCLUSIONS AND FUTURE WORK 127
6.1 Conclusions 127
6.2 Future work 129
6.2.1 Effects of antenna polarization in the Ku-band 129
6.2.2 Forward-looking near-field ISAR configuration 130
6.2.3 Estimation of the movement errors in ISAR configuration 131
Abstract (In Korean) 145
Acknowlegement 148๋ฐ
Non-Contact Human Motion Sensing Using Radar Techniques
Human motion analysis has recently gained a lot of interest in the research community due to its widespread applications. A full understanding of normal motion from human limb joint trajectory tracking could be essential to develop and establish a scientific basis for correcting any abnormalities. Technology to analyze human motion has significantly advanced in the last few years. However, there is a need to develop a non-invasive, cost effective gait analysis system that can be functional indoors or outdoors 24/7 without hindering the normal daily activities for the subjects being monitored or invading their privacy. Out of the various methods for human gait analysis, radar technique is a non-invasive method, and can be carried out remotely. For one subject monitoring, single tone radars can be utilized for motion capturing of a single target, while ultra-wideband radars can be used for multi-subject tracking. But there are still some challenges that need to be overcome for utilizing radars for motion analysis, such as sophisticated signal processing requirements, sensitivity to noise, and hardware imperfections. The goal of this research is to overcome these challenges and realize a non-contact gait analysis system capable of extracting different organ trajectories (like the torso, hands and legs) from a complex human motion such as walking. The implemented system can be hugely beneficial for applications such as treating patients with joint problems, athlete performance analysis, motion classification, and so on
Behind-wall target detection using micro-doppler effects
Abstract: During the last decade technology for seeing through walls and through dense vegetation has interested many researchers. This technology offers excellent opportunities for military and police applications, though applications are not limited to the military and police; they go beyond those applications to where detecting a target behind an obstacle is needed. To be able to disclose the location and velocity of obscured targets, scientistsโ resort to electromagnetic wave propagation. Thus, through-the-wall radar (TWR) is technology used to propagate electromagnetic waves towards a target through a wall. Though TWR is a promising technology, it has been reported that TWR imaging (TWRI) poses a range of ambiguities in target characterisation and detection. These ambiguities are related to the thickness and electric properties of walls. It has been reported that the mechanical and electric properties of the wall defocus the target image rendered by the radar. The defocusing problem is the phenomenon of displacing the target away from its true location when the image is rendered. Thus, the operator of the TWR will have a wrong position, not the real position of the target. Defocusing is not the only problem observed while the signal is travelling through the wall. Target classification, wall modelling and others are areas that need investigation...D.Ing. (Electrical and Electronic Engineering
Noncontact Vital Signs Detection
Human health condition can be accessed by measurement of vital signs, i.e., respiratory rate (RR), heart rate (HR), blood oxygen level, temperature and blood pressure. Due to drawbacks of contact sensors in measurement, non-contact sensors such as imaging photoplethysmogram (IPPG) and Doppler radar system have been proposed for cardiorespiratory rates detection by researchers.The UWB pulse Doppler radars provide high resolution range-time-frequency information. It is bestowed with advantages of low transmitted power, through-wall capabilities, and high resolution in localization. However, the poor signal to noise ratio (SNR) makes it challenging for UWB radar systems to accurately detect the heartbeat of a subject. To solve the problem, phased-methods have been proposed to extract the phase variations in the reflected pulses modulated by human tiny thorax motions. Advance signal processing method, i.e., state space method, can not only be used to enhance SNR of human vital signs detection, but also enable the micro-Doppler trajectories extraction of walking subject from UWB radar data.Stepped Frequency Continuous Wave (SFCW) radar is an alternative technique useful to remotely monitor human subject activities. Compared with UWB pulse radar, it relieves the stress on requirement of high sampling rate analog-to-digital converter (ADC) and possesses higher signal-to-noise-ratio (SNR) in vital signs detection. However, conventional SFCW radar suffers from long data acquisition time to step over many frequencies. To solve this problem, multi-channel SFCW radar has been proposed to step through different frequency bandwidths simultaneously. Compressed sensing (CS) can further reduce the data acquisition time by randomly stepping through 20% of the original frequency steps.In this work, SFCW system is implemented with low cost, off-the-shelf surface mount components to make the radar sensors portable. Experimental results collected from both pulse and SFCW radar systems have been validated with commercial contact sensors and satisfactory results are shown
Bio-Radar Applications for Remote Vital Signs Monitoring
Nowadays, most vital signs monitoring techniques used in a medical context and/or daily
life routines require direct contact with skin, which can become uncomfortable or even
impractical to be used regularly. Radar technology has been appointed as one of the most
promising contactless tools to overcome these hurdles. However, there is a lack of studies
that cover a comprehensive assessment of this technology when applied in real-world
environments. This dissertation aims to study radar technology for remote vital signs
monitoring, more specifically, in respiratory and heartbeat sensing.
Two off-the-shelf radars, based on impulse radio ultra-wideband and frequency modu lated continuous wave technology, were customized to be used in a small proof of concept
experiment with 10 healthy participants. Each subject was monitored with both radars
at three different distances for two distinct conditions: breathing and voluntary apnea.
Signals processing algorithms were developed to detect and estimate respiratory and
heartbeat parameters, assessed using qualitative and quantitative methods.
Concerning respiration, a minimum error of 1.6% was found when radar respiratory
peaks signals were directly compared with their reference, whereas a minimum mean
absolute error of 0.3 RPM was obtained for the respiration rate. Concerning heartbeats,
their expression in radar signals was not as clear as the respiration ones, however a
minimum mean absolute error of 1.8 BPM for heartbeat was achieved after applying a
novel selective algorithm developed to validate if heart rate value was estimated with
reliability.
The results proved the potential for radars to be used in respiratory and heartbeat
contactless sensing, showing that the employed methods can be already used in some mo tionless situations. Notwithstanding, further work is required to improve the developed
algorithms in order to obtain more robust and accurate systems.Atualmente, a maioria das tรฉcnicas usadas para a monitorizaรงรฃo de sinais vitais em
contexto mรฉdicos e/ou diรกrio requer contacto direto com a pele, o que poderรก tornar-se
incรณmodo ou atรฉ mesmo inviรกvel em certas situaรงรตes. A tecnologia radar tem vindo a ser
apontada como uma das mais promissoras ferramentas para mediรงรฃo de sinais vitais ร
distรขncia e sem contacto. Todavia, sรฃo necessรกrios mais estudos que permitam avaliar esta
tecnologia quando aplicada a situaรงรตes mais reais. Esta dissertaรงรฃo tem como objetivo o
estudo da tecnologia radar aplicada no contexto de mediรงรฃo remota de sinais vitais, mais
concretamente, na mediรงรฃo de atividade respiratรณria e cardรญaca.
Dois aparelhos radar, baseados em tecnologia banda ultra larga por rรกdio de impulso
e em tecnologia de onda continua modulada por frequรชncia, foram configurados e usados
numa prova de conceito com 10 participantes. Cada sujeito foi monitorizado com cada
um dos radar em duas situaรงรตes distintas: respirando e em apneia voluntรกria. Algorit mos de processamento de sinal foram desenvolvidos para detetar e estimar parรขmetros
respiratรณrios e cardรญacos, avaliados atravรฉs de mรฉtodos qualitativos e quantitativos.
Em relaรงรฃo ร respiraรงรฃo, o menor erro obtido foi de 1,6% quando os sinais de radar
respiratรณrios foram comparados diretamente com os sinais de referรชncia, enquanto que,
um erro mรฉdio absoluto mรญnimo de 0,3 RPM foi obtido para a estimaรงรฃo da frequรชncia
respiratรณria via radar. A expressรฃo cardรญaca nos sinais radar nรฃo se revelou tรฃo evidente
como a respiratรณria, no entanto, um erro mรฉdio absoluto mรญnimo de 1,8 BPM foi obtido
para a estimaรงรฃo da frequรชncia cardรญaca apรณs a aplicaรงรฃo de um novo algoritmo seletivo,
desenvolvido para validar a confianรงa dos valores obtidos.
Os resultados obtidos provaram o potencial do uso de radares na mediรงรฃo de atividade
respiratรณria e cardรญaca sem contacto, sendo esta tecnologia viรกvel de ser implementada em
situaรงรตes onde nรฃo existe muito movimento. Nรฃo obstante, os algoritmos desenvolvidos
devem ser aperfeiรงoados no futuro de forma a obter sistemas mais robustos e precisos
Compressive Sensing and Its Applications in Automotive Radar Systems
Die Entwicklung in Richtung zu autonomem Fahren verspricht, kรผnftig einen sicheren
Verkehr ohne tรถdliche Unfรคlle zu ermรถglichen, indem menschliche Fahrer vollstรคndig
ersetzt werden. Dadurch entfรคllt der Faktor des menschlichen Fehlers, der aus
Mรผdigkeit, Unachtsamkeit oder Alkoholeinfluss resultiert. Um jedoch eine breite
Akzeptanz fรผr autonome Fahrzeuge zu erreichen und es somit eines Tages vollstรคndig
umzusetzen, sind noch eine Vielzahl von Herausforderungen zu lรถsen. Da in einem
autonomen Fahrzeug kein menschlicher Fahrer mehr in Notfรคllen eingreifen kann,
mรผssen sich autonome Fahrzeuge auf leistungsfรคhige und robuste Sensorsysteme
verlassen kรถnnen, um in kritischen Situationen auch unter widrigen Bedingungen
angemessen reagieren zu kรถnnen. Daher ist die Entwicklung von Sensorsystemen
erforderlich, die fรผr Funktionalitรคten jenseits der aktuellen advanced driver assistance
systems eingesetzt werden kรถnnen. Dies resultiert in neuen Anforderungen, die erfรผllt
werden mรผssen, um sichere und zuverlรคssige autonome Fahrzeuge zu realisieren, die
weder Fahrzeuginsassen noch Passanten gefรคhrden. Radarsysteme gehรถren zu den
Schlรผsselkomponenten unter der Vielzahl der verfรผgbaren Sensorsysteme, da sie im
Gegensatz zu visuellen Sensoren von widrigen Wetter- und Umgebungsbedingungen
kaum beeintrรคchtigt werden. Darรผber hinaus liefern Radarsysteme zusรคtzliche
Umgebungsinformationen wie Abstand, Winkel und relative Geschwindigkeit zwischen
Sensor und reflektierenden Zielen. Die vorliegende Dissertation deckt im Wesentlichen
zwei Hauptaspekte der Forschung und Entwicklung auf dem Gebiet der Radarsysteme
im Automobilbereich ab. Ein Aspekt ist die Steigerung der Effizienz und Robustheit
der Signalerfassung und -verarbeitung fรผr die Radarperzeption. Der andere Aspekt ist
die Beschleunigung der Validierung und Verifizierung von automated cyber-physical
systems, die parallel zum Automatisierungsgrad auch eine hรถhere Komplexitรคt
aufweisen.
Nach der Analyse zahlreicher mรถglicher Compressive Sensing Methoden, die im
Bereich Fahrzeugradarsysteme angewendet werden kรถnnen, wird ein rauschmoduliertes
gepulstes Radarsystem vorgestellt, das kommerzielle Fahrzeugradarsysteme in
seiner Robustheit gegenรผber Rauschen รผbertrifft. Die Nachteile anderer gepulster
Radarsysteme hinsichtlich des Signalerfassungsaufwands und der Laufzeit werden
durch die Verwendung eines Compressive Sensing-Signalerfassungs- und Rekonstruktionsverfahrens
in Kombination mit einer Rauschmodulation deutlich verringert.
Mit Compressive Sensing konnte der Aufwand fรผr die Signalerfassung um 70% reduziert
werden, wรคhrend gleichzeitig die Robustheit der Radarwahrnehmung auch fรผr signal-to-noise-ratio-Pegel nahe oder unter Null erreicht wird. Mit einem validierten
Radarsensormodell wurde das Rauschradarsystem emuliert und mit einem
kommerziellen Fahrzeugradarsystem verglichen. Datengetriebene Wettermodelle
wurden entwickelt und wรคhrend der Simulation angewendet, um die Radarleistung
unter widrigen Bedingungen zu bewerten. Wรคhrend eine Besprรผhung mit Wasser die
Radomdรคmpfung um 10 dB erhรถht und Spritzwasser sogar um 20 dB, ergibt sich die
eigentliche Begrenzung aus der Rauschzahl und Empfindlichkeit des Empfรคngers. Es
konnte bewiesen werden, dass das vorgeschlagene Compressive Sensing Rauschradarsystem
mit einer zusรคtzlichen Signaldรคmpfung von bis zu 60 dB umgehen kann
und damit eine hohe Robustheit in ungรผnstigen Umwelt- und Wetterbedingungen
aufweist.
Neben der Robustheit wird auch die Interferenz berรผcksichtigt. Zum einen wird
die erhรถhte Stรถrfestigkeit des Stรถrradarsystems nachgewiesen. Auf der anderen
Seite werden die Auswirkungen auf bestehende Fahrzeugradarsysteme bewertet und
Strategien zur Minderung der Auswirkungen vorgestellt.
Die Struktur der Arbeit ist folgende. Nach der Einfรผhrung der Grundlagen
und Methoden fรผr Fahrzeugradarsysteme werden die Theorie und Metriken hinter
Compressive Sensing gezeigt. Darรผber hinaus werden weitere Aspekte wie Umgebungsbedingungen,
unterschiedliche Radararchitekturen und Interferenz erlรคutert.
Der Stand der Technik gibt einen รberblick รผber Compressive Sensing-Ansรคtze und
Implementierungen mit einem Fokus auf Radar. Darรผber hinaus werden Aspekte
von Fahrzeug- und Rauschradarsystemen behandelt. Der Hauptteil beginnt mit
der Vorstellung verschiedener Ansรคtze zur Nutzung von Compressive Sensing fรผr
Fahrzeugradarsysteme, die in der Lage sind, die Erfassung und Wahrnehmung von
Radarsignalen zu verbessern oder zu erweitern. Anschlieรend wird der Fokus auf
ein Rauschradarsystem gelegt, das mit Compressive Sensing eine effiziente Signalerfassung
und -rekonstruktion ermรถglicht. Es wurde mit verschiedenen Compressive
Sensing-Metriken analysiert und in einer Proof-of-Concept-Simulation bewertet. Mit
einer Emulation des Rauschradarsystems wurde das Potential der Compressive Sensing
Signalerfassung und -verarbeitung in einem realistischeren Szenario demonstriert.
Die Entwicklung und Validierung des zugrunde liegenden Sensormodells wird ebenso
dokumentiert wie die Entwicklung der datengetriebenen Wettermodelle. Nach der
Betrachtung von Interferenz und der Koexistenz des Rauschradars mit kommerziellen
Radarsystemen schlieรt ein letztes Kapitel mit Schlussfolgerungen und einem
Ausblick die Arbeit ab.Developments towards autonomous driving promise to lead to safer traffic, where fatal
accidents can be avoided after making human drivers obsolete and hence removing
the factor of human error. However, to ensure the acceptance of automated driving
and make it a reality one day, still a huge amount of challenges need to be solved.
With having no human supervisors, automated vehicles have to rely on capable and
robust sensor systems to ensure adequate reactions in critical situations, even during
adverse conditions. Therefore, the development of sensor systems is required that
can be applied for functionalities beyond current advanced driver assistance systems.
New requirements need to be met in order to realize safe and reliable automated
vehicles that do not harm passersby.
Radar systems belong to the key components among the variety of sensor systems.
Other than visual sensors, radar is less vulnerable towards adverse weather and
environment conditions. In addition, radar provides complementary environment
information such as target distance, angular position or relative velocity, too. The
thesis ad hand covers basically two main aspects of research and development in the
field of automotive radar systems. One aspect is to increase efficiency and robustness
in signal acquisition and processing for radar perception. The other aspect is to
accelerate validation and verification of automated cyber-physical systems that
feature more complexity along with the level of automation.
After analyzing a variety of possible Compressive Sensing methods for automotive
radar systems, a noise modulated pulsed radar system is suggested in the thesis at
hand, which outperforms commercial automotive radar systems in its robustness
towards noise. Compared to other pulsed radar systems, their drawbacks regarding
signal acquisition effort and computation run time are resolved by using noise modulation
for implementing a Compressive Sensing signal acquisition and reconstruction
method. Using Compressive Sensing, the effort in signal acquisition was reduced by
70%, while obtaining a radar perception robustness even for signal-to-noise-ratio
levels close to or below zero. With a validated radar sensor model the noise radar
was emulated and compared to a commercial automotive radar system. Data-driven
weather models were developed and applied during simulation to evaluate radar performance
in adverse conditions. While water sprinkles increase radome attenuation
by 10 dB and splash water even by 20 dB, the actual limitation comes from noise
figure and sensitivity of the receiver. The additional signal attenuation that can be
handled by the proposed compressive sensing noise radar system proved to be even up to 60 dB, which ensures a high robustness of the receiver during adverse weather
and environment conditions.
Besides robustness, interference is also considered. On the one hand the increased
robustness towards interference of the noise radar system is demonstrated. On
the other hand, the impact on existing automotive radar systems is evaluated and
strategies to mitigate the impact are presented.
The structure of the thesis is the following. After introducing basic principles
and methods for automotive radar systems, the theory and metrics of Compressive
Sensing is presented. Furthermore some particular aspects are highlighted such as
environmental conditions, different radar architectures and interference. The state of
the art provides an overview on Compressive Sensing approaches and implementations
with focus on radar. In addition, it covers automotive radar and noise radar related
aspects. The main part starts with presenting different approaches on making use
of Compressive Sensing for automotive radar systems, that are capable of either
improving or extending radar signal acquisition and perception. Afterwards the focus
is put on a noise radar system that uses Compressive Sensing for an efficient signal
acquisition and reconstruction. It was analyzed using different Compressive Sensing
metrics and evaluated in a proof-of-concept simulation. With an emulation of the
noise radar system the feasibility of the Compressive Sensing signal acquisition and
processing was demonstrated in a more realistic scenario. The development and
validation of the underlying sensor model is documented as well as the development
of the data-driven weather models. After considering interference and co-existence
with commercial radar systems, a final chapter with conclusions and an outlook
completes the work
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Realization of Integrated Coherent LiDAR
LiDAR (Light Detection and Ranging) captures high-definition real-time 3D images of the surrounding environment through active sensing with infrared lasers. It has unique advantages that can compensate the fundamental limitations in camera-based 3D imaging via vision algorithms or RADARs, which makes it an important sensing modality to guarantee robust autonomy in self-driving cars. However, high price tag of existing commercial LiDAR modules based on mechanical beam scanners and intensity-based detection scheme makes them unusable in the context of mass produced consumer products.The focus of thesis is on the integrated coherent LiDAR with optical phased array-based solid-state beam steering, which has great potential to dramatically bring down the cost of a LiDAR module. It begins with an overview of LiDAR implementation options and system requirements in the context of autonomous vehicles, which leads us to conclude that beam-steering coherent FMCW LiDAR in optical C-band is indeed the best implementation strategy to realize low-cost automotive LiDARs. Motivated by this observation, a quantitative framework for evaluating FMCW LiDAR performance is also introduced to predict the design that satisfies car-grade performance requirements. Then the thesis presents the silicon implementation results from our single-chip optical phased array and integrated coherent LiDAR prototype. Our implementations leverage the 3D heterogeneous integration platform, where custom silicon photonics and nanoscale CMOS fabricated at a 300 mm wafer facility are combined at the wafer-scale to minimize the unit cost without I/O density issues. After discussing remaining challenges and possible ways to enhance the operating range and system reliability, this thesis finally addresses the problem of fundamental trade-off between phase noise and wavelength tuning in FMCW laser source, and present circuit- and algorithm-level techniques to enable FMCW measurements beyond inherent laser coherence range limit
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