Multiradar Data Fusion for Respiratory Measurement of Multiple People

This study proposes a data fusion method for multiradar systems to enable measurement of the respiration of multiple people located at arbitrary positions. Using the proposed method, the individual respiration rates of multiple people can be measured, even when echoes from some of these people cannot be received by one of the radar systems because of shadowing. In addition, the proposed method does not require information about the positions and orientations of the radar systems used because the method can estimate the layout of these radar systems by identifying multiple human targets that can be measured from different angles using multiple radar systems. When a single target person can be measured using multiple radar systems simultaneously, the proposed method selects an accurate signal from among the multiple signals based on the spectral characteristics. To verify the effectiveness of the proposed method, we performed experiments based on two scenarios with different layouts that involved seven participants and two radar systems. Through these experiments, the proposed method was demonstrated to be capable of measuring the respiration of all seven people by overcoming the shadowing issue. In the two scenarios, the average errors of the proposed method in estimating the respiration rates were 0.33 and 1.24 respirations per minute (rpm), respectively, thus demonstrating accurate and simultaneous respiratory measurements of multiple people using the multiradar system

Multiradar Data Fusion for Respiratory Measurement of Multiple People

This study proposes a data fusion method for multiradar systems to enable measurement of the respiration of multiple people located at arbitrary positions. Using the proposed method, the individual respiration rates of multiple people can be measured, even when echoes from some of these people cannot be received by one of the radar systems because of shadowing. In addition, the proposed method does not require information about the positions and orientations of the radar systems used because the method can estimate the layout of these radar systems by identifying multiple human targets that can be measured from different angles using multiple radar systems. When a single target person can be measured using multiple radar systems simultaneously, the proposed method selects an accurate signal from among the multiple signals based on the spectral characteristics. To verify the effectiveness of the proposed method, we performed experiments based on two scenarios with different layouts that involved seven participants and two radar systems. Through these experiments, the proposed method was demonstrated to be capable of measuring the respiration of all seven people by overcoming the shadowing issue. In the two scenarios, the average errors of the proposed method in estimating the respiration rates were 0.33 and 1.24 respirations per minute (rpm), respectively, thus demonstrating accurate and simultaneous respiratory measurements of multiple people using the multiradar system

Occupancy Based Household Energy Disaggregation using Ultra Wideband Radar and Electrical Signature Profiles

Human behaviour and occupancy accounts for a substantial proportion of variation in the energy efficiency pro le of domestic buildings. Yet while people often claim that they would like to reduce their energy bills, rhetoric frequently fails to match action due to the effort involved in understand- ing and changing deeply engrained energy consumption habits. Here, we present and, through dedicated experiments, test in-house developed soft-ware to remotely identify appliance energy usage within buildings, using energy equipment which could be placed at the electricity meter location. Furthermore, we monitor and compare the occupancy of the location under study through Ultra-Wideband (UWB) radar technology and compare the resulting data with those received from the power monitoring software, via time synchronization. These signals when mapped together can potentially provide both occupancy and speci c appliances power consumption, which could enable energy usage segregation on a yet impossible scale as well as usage attributable to occupancy behaviour. Such knowledge forms the basis for the implementation of automated energy saving actions based on a households unique energy profi le

Occupancy based household energy disaggregation using ultra wideband radar and electrical signature profiles

Human behaviour and occupancy accounts for a substantial proportion of variation in the energy efficiency pro le of domestic buildings. Yet while people often claim that they would like to reduce their energy bills, rhetoric frequently fails to match action due to the effort involved in understand- ing and changing deeply engrained energy consumption habits. Here, we present and, through dedicated experiments, test in-house developed soft-ware to remotely identify appliance energy usage within buildings, using energy equipment which could be placed at the electricity meter location. Furthermore, we monitor and compare the occupancy of the location under study through Ultra-Wideband (UWB) radar technology and compare the resulting data with those received from the power monitoring software, via time synchronization. These signals when mapped together can potentially provide both occupancy and speci c appliances power consumption, which could enable energy usage segregation on a yet impossible scale as well as usage attributable to occupancy behaviour. Such knowledge forms the basis for the implementation of automated energy saving actions based on a households unique energy profi le

EFFICIENT PARAMETER ESTIMATION METHODS FOR AUTOMOTIVE RADAR SYSTEMS

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 2. 김성철.As the demand for safety and convenience in the automotive-technology field increased, many applications of advanced driving assistance systems were developed. To provide driving information, among the sensors, such as cameras sensor, light detection and ranging sensor, radar sensor, and ultrasonic sensor, a radar sensor is known to exhibit excellent performance in terms of visibility for different weather conditions. Especially with the legislation of the adaptive cruise control system and autonomous emergency braking system in a global environment, the market of the automotive radar sensor is expected to grow explosively. At present, the development of cost-effective radar offering high performance with small size is required. In addition, the radar system should be enforced to have a simultaneous functionality for both long and short ranges. Thus, challenging issues still remain with respect to radar signal processing including high-resolution parameter estimation, multi-target detection, clutter suppression, and interference mitigation. For high-resolution parameter estimation, direction-of-arrival (DOA) estimation method has been investigated to identify the target object under complex unban environment. To separate closely spaced target having similar range and distance, high-resolution techniques, such as multiple signal classification (MUSIC), the estimation of signal parameters via rotational invariance techniques (ESPRIT), and maximum likelihood (ML) algorithm, are applied for automotive radars. In general, cycle time for radar system, which is the processing time for one snapshot, is very short, thus to establish a high-resolution estimation algorithm with computational efficiency is additional issue. On the other hands, multi-target detection scheme is required to identify many targets in the field of view. Multi-target detection is regarded as target pairing solution, whose task is to associate frequency components obtained from multiple targets. Under certain conditions, the association may fail and real target may be combined to ghost components. Thus, reliable paring or association method is essential for automotive radar systems. The clutter denotes undesired echoes due to reflected wave from background environment, which includes guardrail, traffic signs, and stationary structures around the load. To minimize the effect of clutter, conventional radar systems use high pass filter based on the assumption that the clutter is stationary with energy concentrated in the low frequency domain. However, the clutter is presented with various energy and frequency under automotive radar environment. Especially, under the specific environment with iron materials, target component is not detected due to clutter with large power. Mutual interference is a crucial issue that must be resolved for improved safety functions. Given the increasing number of automotive radar sensors operating at the same instant, the probability that radar sensors may receive signals from other radar sensors gradually increases. In such a situation, the system may fail to detect the correct target given the serious interference. Effective countermeasures, therefore, have to be considered. In this dissertation, we propose efficient parameter estimation methods for automotive radar system. The proposed methods include the radar signal processing issues as above described, respectively. First, the high-resolution DOA estimation method is proposed by using frequency domain analysis. The scheme is based on the MUSIC algorithm, which use distinct beat frequency of the target. The target beat frequency also gives distance and velocity. Thus, the proposed algorithm provides either high-resolution angle information of target or natural target pairing solution. Secondly, we propose the clutter suppression method under iron-tunnel conditions. The clutter in iron-tunnel environments is known to severely degrade the target detection performance because of the signal reflection from iron structures. The suppression scheme is based on cepstral analysis of received signal. By using periodical characteristic of the iron-tunnel clutter, the suppressed frequency response is obtained. Finally, the interference mitigation scheme is studied. Mutual interference between frequency modulated continuous waveform (FMCW) radars appears in the form of increased noise levels in the frequency domain and results in a failure to separate the target object from interferer. Thus, we propose a high-resolution frequency estimation technique for use in interference environments.Chapter 1. Introduction 1 1.1 Background 1 1.2 ADAS Applications for Automotive Radar 3 1.3 Motivation and Organization 5 Chapter 2. High-Resolution Direction-of-Arrvial Estimation with Pairing function for Automotive Radar Systems 8 2.1 Introduction 8 2.2 High-Resolution DOA Estimation for automotive Radars 10 2.2.1 DOA Estimation in the Time-domain Processing 11 2.2.2 DOA Estimation in the Frequency-domain Processing 15 2.3 Simulation Result 18 2.3.1 Simulation setup 18 2.3.2 Performance Comparison of the DOA Estimation in Time- and Frquency-domain Processing 19 2.3.3 Performance Analysis of the DOA Estimation in Frequency-domain 23 2.4 Conclusion 26 Chapter 3. Clutter Suppression Method of Iron Tunnel using Cepstral Analysis for Automotive Radars 27 3.1 Introduction 27 3.2 Clutter Suppression under Iron Tunnels 30 3.2.1 Radar Model of an Iron Tunnel 30 3.2.2 Cepstrum Analysis of an Iron Tunnel 33 3.2.3 Cepstrum Based Clutter Suppression Method 36 3.3 Experimental Result 39 3.4 Conclusion 46 Chapter 4. Interference Mitigation by High-Resolution Frequency Estimation in Automotive FMCW Radar 47 4.1 Introduction 47 4.2 Automotive FMCW Radars in an Interference Environment 50 4.2.1 The Same Sign-Chirp Case 54 4.2.2 The Different Sign-Chirp Case 56 4.3 High-Resolution Frequency Estimation Method 58 4.3.1 Data Model 58 4.3.2 Estimation of Correlation Matrix 61 4.3.3 Application of the MUSIC Algorithm 62 4.3.4 Application of the MUSIC Algorithm 63 4.3.5 Number of Frequency Estimation 65 4.4 Experimental Result 66 4.5 Conclusion 71 Bibliography 72 Abstract in Korean 78Docto

An FPGA-based 77 GHzs RADAR signal processing system for automotive collision avoidance

An FPGA implementable Verilog HDL based signal processing algorithm has been developed to detect the range and velocity of target vehicles using a MEMS based 77 GHz LFMCW long range automotive radar. The algorithm generates a tuning voltage to control a GaAs based VCO to produce a triangular chirp signal, controls the operation of MEMS components, and finally processes the IF signal to determine the range and veolicty of the detected targets. The Verilog HDL code has been developed targeting the Xilinx Virtex-5 SX50T FPGA. The developed algorithm enables the MEMS radar to detect 24 targets in an optimum timespan of 6.42 ms in the range of 0.4 to 200 m with a range resolution of 0.19 m and a maximum range error 0.25 m. A maximum relative velocity of ±300 km/h can be determined with a velocity resolution in HDL of 0.95 m/s and a maximum velocity error of 0.83 m/s with a sweep duration of 1 ms

Improving the Vertical Accuracy of Indoor Positioning for Emergency Communication

The emergency communication systems are undergoing a transition from the PSTN-based legacy system to an IP-based next generation system. In the next generation system, GPS accurately provides a user's location when the user makes an emergency call outdoors using a mobile phone. Indoor positioning, however, presents a challenge because GPS does not generally work indoors. Moreover, unlike outdoors, vertical accuracy is critical indoors because an error of few meters will send emergency responders to a different floor in a building. This paper presents an indoor positioning system which focuses on improving the accuracy of vertical location. We aim to provide floor-level accuracy with minimal infrastructure support. Our approach is to use multiple sensors available in today's smartphones to trace users' vertical movements inside buildings. We make three contributions. First, we present the elevator module for tracking a user's movement in elevators. The elevator module addresses three core challenges that make it difficult to accurately derive displacement from acceleration. Second, we present the stairway module which determines the number of floors a user has traveled on foot. Unlike previous systems that track users' foot steps, our stairway module uses a novel landing counting technique. Third, we present a hybrid architecture that combines the sensor-based components with minimal and practical infrastructure. The infrastructure provides initial anchor and periodic corrections of a user's vertical location indoors. The architecture strikes the right balance between the accuracy of location and the feasibility of deployment for the purpose of emergency communication

Collaborative Indoor Positioning Systems: A Systematic Review

Research and development in Collaborative Indoor Positioning Systems (CIPSs) is growing steadily due to their potential to improve on the performance of their non-collaborative counterparts. In contrast to the outdoors scenario, where Global Navigation Satellite System is widely adopted, in (collaborative) indoor positioning systems a large variety of technologies, techniques, and methods is being used. Moreover, the diversity of evaluation procedures and scenarios hinders a direct comparison. This paper presents a systematic review that gives a general view of the current CIPSs. A total of 84 works, published between 2006 and 2020, have been identified. These articles were analyzed and classified according to the described system’s architecture, infrastructure, technologies, techniques, methods, and evaluation. The results indicate a growing interest in collaborative positioning, and the trend tend to be towards the use of distributed architectures and infrastructure-less systems. Moreover, the most used technologies to determine the collaborative positioning between users are wireless communication technologies (Wi-Fi, Ultra-WideBand, and Bluetooth). The predominant collaborative positioning techniques are Received Signal Strength Indication, Fingerprinting, and Time of Arrival/Flight, and the collaborative methods are particle filters, Belief Propagation, Extended Kalman Filter, and Least Squares. Simulations are used as the main evaluation procedure. On the basis of the analysis and results, several promising future research avenues and gaps in research were identified

Advances in UWB-based Indoor Position Estimation and its Application in Fall Detection

In an indoor propagation environment, the position of an Object of Interest (OOI) is typically estimated by cleverly manipulating range or proximity measurements that are obtained from a series of reference node combinations. In a noise-free propagation scenario, these measured parameters are fed into conventional position estimation techniques and an accurate estimate of the OOI’s position is obtained. In practice, the propagation scenario is never quite noise-free; hence the OOI’s position estimate is obtained in error. Ultra-Wideband (UWB) is a wireless communication technology that is able to resolve individual multipath components and this ensures that it is capable of estimating the arrival time of the first signal path. The implication of this lies in the fact that the accuracy of the range or proximity measurements obtained from the reference node combinations is guaranteed; hence leading to a reliable estimate of the OOI’s position. In the research work presented in this thesis, the body of knowledge that relates to indoor position estimation is advanced upon. With a primary focus of enhancing the estimation accuracy of indoor position estimation systems, UWB is utilised as the underlying wireless communications technology. The challenges faced by current UWBbased position estimation systems are identified and tackled directly. Specifically, the position estimation error that is due to multipath propagation is addressed and a pre-localisation algorithm that serves the purpose of resolving individual multipath UWB signals in the immediate environment is proposed. Additionally, a novel position estimation technique coined as Time Reflection of Arrival (TROA) is presented in this thesis. Through a series of Mean Squared Error (MSE) and Cram´er-Rao Lower Bound (CRLB) analyses, TROA is shown to be very effective when compared to TOA and the typically unvoiced TSOA technique. In the last section of this thesis, an application of UWB in the area of Biomedical Engineering is demonstrated. Specifically, UWB-based position estimation is used to define a novel fall detection algorithm tailored for Dementia patients