Pub Date : 2020-01-01DOI: 10.1109/WiSNeT46826.2020.9037492
Daniel Rodriguez, Changzhi Li
A low-power and low-cost 5.8-GHz 2-port monostatic Doppler radar was designed, fabricated and tested for small motion detection. The implemented RF board is based on a new radar architecture that features a compact size and only one active device. Unlike conventional board level radar systems, it does not use separate Tx/Rx signal chains. With a single antenna for Tx/Rx, it does not use any low noise amplifier (LNA) or circulator in the RF front-end. Besides the local oscillator (LO), there is no more active device that consumes DC power. The fabricated radar system has dimensions of 20.6 mm $times 26.5$ mm $(mathrm{L}times mathrm{W})$ and a power consumption of 290 mW in continuous operation, which could be significantly reduced based on duty cycling. In addition, a low conversion loss of 3.6 dB was achieved. The high sensitivity of the proposed architecture was demonstrated by successfully measuring a $50 mu mathrm{m}$ sinusoidal movement.
设计、制造并测试了一种低功耗、低成本的5.8 ghz 2端口单站多普勒小运动探测雷达。实现的射频板基于一种新型雷达架构，其特点是尺寸紧凑，只有一个有源器件。与传统的板级雷达系统不同，它不使用单独的Tx/Rx信号链。使用单天线的Tx/Rx，它不使用任何低噪声放大器(LNA)或循环器在射频前端。除了本振(LO)，没有更多的有源器件消耗直流电源。制造的雷达系统尺寸为20.6 mm × 26.5 mm ( mathm {L} × mathm {W})，连续工作功耗为290 mW，基于占空比可以显着降低功耗。此外，还实现了3.6 dB的低转换损耗。通过成功测量$50 mu mathm {m}$正弦运动，证明了所提出结构的高灵敏度。
{"title":"A Low-Power and Low-Cost Monostatic Radar Based on a Novel 2-Port Transceiver Chain","authors":"Daniel Rodriguez, Changzhi Li","doi":"10.1109/WiSNeT46826.2020.9037492","DOIUrl":"https://doi.org/10.1109/WiSNeT46826.2020.9037492","url":null,"abstract":"A low-power and low-cost 5.8-GHz 2-port monostatic Doppler radar was designed, fabricated and tested for small motion detection. The implemented RF board is based on a new radar architecture that features a compact size and only one active device. Unlike conventional board level radar systems, it does not use separate Tx/Rx signal chains. With a single antenna for Tx/Rx, it does not use any low noise amplifier (LNA) or circulator in the RF front-end. Besides the local oscillator (LO), there is no more active device that consumes DC power. The fabricated radar system has dimensions of 20.6 mm $times 26.5$ mm $(mathrm{L}times mathrm{W})$ and a power consumption of 290 mW in continuous operation, which could be significantly reduced based on duty cycling. In addition, a low conversion loss of 3.6 dB was achieved. The high sensitivity of the proposed architecture was demonstrated by successfully measuring a $50 mu mathrm{m}$ sinusoidal movement.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126724672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1109/WiSNeT46826.2020.9037574
Anand Dubey, Jonas Fuchs, Torsten Reissland, R. Weigel, F. Lurz
Unlike optical imaging, it’s difficult to extract descriptive features from radar data for problems like classification of different targets. This paper takes the advantage of different neural network based architectures such as convolutional neural networks and long-short term memory to propose an end-to-end framework for classification of vulnerable road users. To make the network’s prediction more reliable for automotive applications, a new concept of network uncertainty is introduced to the defined architectures. The signal processing tool chain described in this paper achieves higher accuracy than state-of-the-art algorithms while maintaining latency requirement for automotive applications.
{"title":"Uncertainty Analysis of Deep Neural Network for Classification of Vulnerable Road Users using micro-Doppler","authors":"Anand Dubey, Jonas Fuchs, Torsten Reissland, R. Weigel, F. Lurz","doi":"10.1109/WiSNeT46826.2020.9037574","DOIUrl":"https://doi.org/10.1109/WiSNeT46826.2020.9037574","url":null,"abstract":"Unlike optical imaging, it’s difficult to extract descriptive features from radar data for problems like classification of different targets. This paper takes the advantage of different neural network based architectures such as convolutional neural networks and long-short term memory to propose an end-to-end framework for classification of vulnerable road users. To make the network’s prediction more reliable for automotive applications, a new concept of network uncertainty is introduced to the defined architectures. The signal processing tool chain described in this paper achieves higher accuracy than state-of-the-art algorithms while maintaining latency requirement for automotive applications.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121550076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1109/WiSNeT46826.2020.9037497
Jennifer M. Williams, F. Gao, Yi Qian, C. Song, R. Khanna, Huaping Liu
Modern society expects connectivity and autonomy amidst the internet of things (IoT) paradigm. Automation and sustainability of consumer and industrial systems is paramount to satisfy demand and transform standards. Low-power wireless sensor networks (WSNs) have proven widely successful for bridging the gap but typically depend on batteries. The next generation of devices can be batteryless or self-sustainable with energy harvesting (EH). This work presents an EH design and analysis model for a system to collect solar and radio frequency energy and store the energy until needed for WSN activities. The viability of the model is demonstrated with two micro-controller-based implementations and applied to data center monitoring.
{"title":"Solar and RF Energy Harvesting Design Model for Sustainable Wireless Sensor Tags","authors":"Jennifer M. Williams, F. Gao, Yi Qian, C. Song, R. Khanna, Huaping Liu","doi":"10.1109/WiSNeT46826.2020.9037497","DOIUrl":"https://doi.org/10.1109/WiSNeT46826.2020.9037497","url":null,"abstract":"Modern society expects connectivity and autonomy amidst the internet of things (IoT) paradigm. Automation and sustainability of consumer and industrial systems is paramount to satisfy demand and transform standards. Low-power wireless sensor networks (WSNs) have proven widely successful for bridging the gap but typically depend on batteries. The next generation of devices can be batteryless or self-sustainable with energy harvesting (EH). This work presents an EH design and analysis model for a system to collect solar and radio frequency energy and store the energy until needed for WSN activities. The viability of the model is demonstrated with two micro-controller-based implementations and applied to data center monitoring.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114764291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1109/WiSNeT46826.2020.9037583
Prateek Nallabolu, Changzhi Li
Compressed Sensing (CS) has provided a viable approach to undersample a sparse signal and reconstruct it perfectly. In this paper, the simulation results of a frequency-modulated continuous-wave (FMCW) radar, which employs a CS based data acquisition and reconstruction algorithm to recover a sparse 2-D target frame using fewer number of scans are presented. A 16-element antenna array based on digital beamforming approach is used on the receiver end to obtain random spatial measurements of the target frame, which is the key to compressed sensing. A linear relationship is established between the total received FMCW beat signal for each scan and the 2-D sparse target frame using a basis transform matrix. Simulations of the proposed radar are performed in MATLAB and the reconstruction results for different noise levels are presented.
{"title":"A Novel Radar Imaging Method Based on Random Illuminations Using FMCW Radar","authors":"Prateek Nallabolu, Changzhi Li","doi":"10.1109/WiSNeT46826.2020.9037583","DOIUrl":"https://doi.org/10.1109/WiSNeT46826.2020.9037583","url":null,"abstract":"Compressed Sensing (CS) has provided a viable approach to undersample a sparse signal and reconstruct it perfectly. In this paper, the simulation results of a frequency-modulated continuous-wave (FMCW) radar, which employs a CS based data acquisition and reconstruction algorithm to recover a sparse 2-D target frame using fewer number of scans are presented. A 16-element antenna array based on digital beamforming approach is used on the receiver end to obtain random spatial measurements of the target frame, which is the key to compressed sensing. A linear relationship is established between the total received FMCW beat signal for each scan and the 2-D sparse target frame using a basis transform matrix. Simulations of the proposed radar are performed in MATLAB and the reconstruction results for different noise levels are presented.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127478897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1109/WiSNeT46826.2020.9037602
Christian Dorn, S. Erhardt, R. Weigel, A. Koelpin, F. Lurz
In this publication a method for direction-of-arrival measurements is introduced. It allows very low cost implementations. Instead of using multiple wide-band receivers with an antenna each, a single narrow-band receiver is used in combination with six antennas. The different antenna signals are time multiplexed to the receiver using an integrated 6-to-l RF switch. Signal processing allows to synchronize the corresponding signals to allow the calculation of the incident angle. As exact synchronization is not necessary, fast transitions between multiple frequencies are possible and therefore accuracy can be significantly increased.
{"title":"Low-Cost Direction-of-Arrival Measurements using Multiplexed Antenna Switching","authors":"Christian Dorn, S. Erhardt, R. Weigel, A. Koelpin, F. Lurz","doi":"10.1109/WiSNeT46826.2020.9037602","DOIUrl":"https://doi.org/10.1109/WiSNeT46826.2020.9037602","url":null,"abstract":"In this publication a method for direction-of-arrival measurements is introduced. It allows very low cost implementations. Instead of using multiple wide-band receivers with an antenna each, a single narrow-band receiver is used in combination with six antennas. The different antenna signals are time multiplexed to the receiver using an integrated 6-to-l RF switch. Signal processing allows to synchronize the corresponding signals to allow the calculation of the incident angle. As exact synchronization is not necessary, fast transitions between multiple frequencies are possible and therefore accuracy can be significantly increased.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122131931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1109/WiSNeT46826.2020.9037603
F. Michler, Kilin Shi, S. Schellenberger, B. Scheiner, F. Lurz, R. Weigel, A. Koelpin
This paper investigates the influence of nonlinearities on relative distance measurements by continuous-wave radar systems. For the case of a six-port receiver architecture, a mathematical relationship between detector nonlinearity and measurement error is derived. Moreover, a generalized sinusoidal error model, which fits both six-port and mixer-based radar systems, is used to study the effect of nonlinear mixing when one or more displacement movements with different amplitudes are to be detected.
{"title":"On the Impact of System Nonlinearities in Continuous-Wave Radar Systems for Vital Parameter Sensing","authors":"F. Michler, Kilin Shi, S. Schellenberger, B. Scheiner, F. Lurz, R. Weigel, A. Koelpin","doi":"10.1109/WiSNeT46826.2020.9037603","DOIUrl":"https://doi.org/10.1109/WiSNeT46826.2020.9037603","url":null,"abstract":"This paper investigates the influence of nonlinearities on relative distance measurements by continuous-wave radar systems. For the case of a six-port receiver architecture, a mathematical relationship between detector nonlinearity and measurement error is derived. Moreover, a generalized sinusoidal error model, which fits both six-port and mixer-based radar systems, is used to study the effect of nonlinear mixing when one or more displacement movements with different amplitudes are to be detected.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132758268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1109/WiSNeT46826.2020.9037614
Takumi Mizushima, R. Nakamura, H. Hadama
This paper experimentally investigates the reflection characteristics of 24/26 GHz ultra-wideband radar echoes from various types of flying drones. Five types of drones with different shapes, sizes, and the number of rotor blades (Matrice 600, 3DR Solo, Phantom 3, Mavic pro, and Bebop drone) were used in the experiment. For comparison, we also investigated the reflection characteristics from a radio-controlled flapping bird (Bionic bird). As a result, by using a UWB radar with high range resolution, we have confirmed that the echoes from the rotors, which are unique features of drone, can be detected for all the drones used in the experiment. In addition, we have also confirmed that there is a noticeable difference between the echoes of the drones and the flapping bird. The difference is expected to be effective to distinguish between drones and birds.
{"title":"Reflection Characteristics of Ultra-wideband Radar Echoes from Various Drones in Flight","authors":"Takumi Mizushima, R. Nakamura, H. Hadama","doi":"10.1109/WiSNeT46826.2020.9037614","DOIUrl":"https://doi.org/10.1109/WiSNeT46826.2020.9037614","url":null,"abstract":"This paper experimentally investigates the reflection characteristics of 24/26 GHz ultra-wideband radar echoes from various types of flying drones. Five types of drones with different shapes, sizes, and the number of rotor blades (Matrice 600, 3DR Solo, Phantom 3, Mavic pro, and Bebop drone) were used in the experiment. For comparison, we also investigated the reflection characteristics from a radio-controlled flapping bird (Bionic bird). As a result, by using a UWB radar with high range resolution, we have confirmed that the echoes from the rotors, which are unique features of drone, can be detected for all the drones used in the experiment. In addition, we have also confirmed that there is a noticeable difference between the echoes of the drones and the flapping bird. The difference is expected to be effective to distinguish between drones and birds.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129815806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1109/WiSNeT46826.2020.9037506
Torsten Reissland, M. Sporer, B. Scheiner, F. Pflaum, A. Hagelauer, R. Weigel, F. Lurz
This paper presents a multiplexed short range frequency modulated continuous wave (FMCW) radar system and an algorithmic approach for the detection of targets. The algorithm uses a heuristic particle filter to track potential targets before they are actually detected. The detection algorithm is compared to a well-known constant false alarm rate (CFAR) detector. The whole setup is tested on real-life data in an industrial scenario.
{"title":"Track-before-Detect Short Range Radar System for Industrial Applications","authors":"Torsten Reissland, M. Sporer, B. Scheiner, F. Pflaum, A. Hagelauer, R. Weigel, F. Lurz","doi":"10.1109/WiSNeT46826.2020.9037506","DOIUrl":"https://doi.org/10.1109/WiSNeT46826.2020.9037506","url":null,"abstract":"This paper presents a multiplexed short range frequency modulated continuous wave (FMCW) radar system and an algorithmic approach for the detection of targets. The algorithm uses a heuristic particle filter to track potential targets before they are actually detected. The detection algorithm is compared to a well-known constant false alarm rate (CFAR) detector. The whole setup is tested on real-life data in an industrial scenario.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"30 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120905402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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