Pub Date : 2024-08-12DOI: 10.1109/TRS.2024.3442692
Jeroen Overdevest;Arie G. C. Koppelaar;Jihwan Youn;Xinyi Wei;Ruud J. G. van Sloun
The proliferation of active radar sensors deployed in vehicles has increased the need for mitigating automotive radar-to-radar interference. While simple avoidance and mitigation methods are still effective today, the expected crowded spectrum allocations pose new challenges that likely require more sophisticated techniques. In particular, interference mitigation methods that can handle significant levels of radar signal corruption are required. To this end, we propose neurally augmented analytically learned fast iterative shrinkage thresholding algorithm (NA-ALFISTA), which is a neural network-based solution for reconstructing time-domain radar signals by leveraging sparsity in the range-Doppler map (RDM). The neural augmentation network is deployed as a single gated recurrent unit (GRU) cell that captures the radar signal statistics along the unfolded layers of fast-iterative shrinkage thresholding algorithm (FISTA)-based sparse recovery, which significantly boosts the convergence rate. It estimates the next layer’s parameters necessary in ALFISTA based on the previous layer’s output. The proposed method is compared to state-of-the-art detect-and-repair methods and source separation methods in simulated data and real-world measurements.
{"title":"Neurally Augmented Deep Unfolding for Automotive Radar Interference Mitigation","authors":"Jeroen Overdevest;Arie G. C. Koppelaar;Jihwan Youn;Xinyi Wei;Ruud J. G. van Sloun","doi":"10.1109/TRS.2024.3442692","DOIUrl":"https://doi.org/10.1109/TRS.2024.3442692","url":null,"abstract":"The proliferation of active radar sensors deployed in vehicles has increased the need for mitigating automotive radar-to-radar interference. While simple avoidance and mitigation methods are still effective today, the expected crowded spectrum allocations pose new challenges that likely require more sophisticated techniques. In particular, interference mitigation methods that can handle significant levels of radar signal corruption are required. To this end, we propose neurally augmented analytically learned fast iterative shrinkage thresholding algorithm (NA-ALFISTA), which is a neural network-based solution for reconstructing time-domain radar signals by leveraging sparsity in the range-Doppler map (RDM). The neural augmentation network is deployed as a single gated recurrent unit (GRU) cell that captures the radar signal statistics along the unfolded layers of fast-iterative shrinkage thresholding algorithm (FISTA)-based sparse recovery, which significantly boosts the convergence rate. It estimates the next layer’s parameters necessary in ALFISTA based on the previous layer’s output. The proposed method is compared to state-of-the-art detect-and-repair methods and source separation methods in simulated data and real-world measurements.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"712-724"},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117881","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 : 2024-07-15DOI: 10.1109/TRS.2024.3428450
Trevor Van Hoosier;Jordan Alexander;Mariah Montgomery;Austin Egbert;Justin Roessler;Charles Baylis;Robert J. Marks
Due to increasing congestion in the radar frequencies due to reallocations, the pressure upon radar systems to avoid interference through dynamically changing operating frequency has intensified. Many modern radar systems (often called “cognitive radar” systems) often have the ability to sense and avoid interference. Through the use of reconfigurable transmitter circuitry, the front end can be quickly reconfigured following a change in frequency to maximize output power and, hence, detection range. With the implementation of a fast, plasma-switch impedance tuner paired with an efficient circuit optimization, the ability to change tuner setting within a single radar pulse repetition interval (PRI) has been previously demonstrated. To carry out impedance-tuning optimization measurements for each PRI, an efficient data storage and lookup method is needed. In this article, we demonstrate how hybrid storage with a hash table can be used with an efficient, cache replacement algorithm on a software-defined radio (SDR) platform to enable continuous operation with pulse-to-pulse optimization. This data storage approach minimizes overhead in storage of circuit optimization settings, allowing faster optimization of the circuit to maximize output power. By maximizing output power quickly, it is expected that the radar will experience better signal-to-interference-plus-noise ratio and accurate detection of targets at greater ranges.
由于重新分配导致雷达频率日益拥挤，雷达系统通过动态改变工作频率来避免干扰的压力也随之增大。许多现代雷达系统（通常称为 "认知雷达 "系统）通常都具有感知和避免干扰的能力。通过使用可重新配置的发射机电路，前端可在频率改变后迅速重新配置，以最大限度地提高输出功率，从而扩大探测范围。通过实施快速等离子体开关阻抗调谐器和高效的电路优化，先前已经展示了在单个雷达脉冲重复间隔（PRI）内改变调谐器设置的能力。为了对每个 PRI 进行阻抗调谐优化测量，需要一种高效的数据存储和查找方法。在本文中，我们演示了如何在软件定义无线电 (SDR) 平台上使用哈希表混合存储和高效的缓存替换算法，以实现脉冲到脉冲优化的连续操作。这种数据存储方法最大限度地减少了电路优化设置的存储开销，从而可以更快地优化电路，最大限度地提高输出功率。通过快速实现输出功率最大化，雷达有望获得更好的信号干扰加噪声比，并在更大范围内精确探测目标。
{"title":"A Hybrid Data Storage Method for Pulse-to-Pulse Optimizations","authors":"Trevor Van Hoosier;Jordan Alexander;Mariah Montgomery;Austin Egbert;Justin Roessler;Charles Baylis;Robert J. Marks","doi":"10.1109/TRS.2024.3428450","DOIUrl":"https://doi.org/10.1109/TRS.2024.3428450","url":null,"abstract":"Due to increasing congestion in the radar frequencies due to reallocations, the pressure upon radar systems to avoid interference through dynamically changing operating frequency has intensified. Many modern radar systems (often called “cognitive radar” systems) often have the ability to sense and avoid interference. Through the use of reconfigurable transmitter circuitry, the front end can be quickly reconfigured following a change in frequency to maximize output power and, hence, detection range. With the implementation of a fast, plasma-switch impedance tuner paired with an efficient circuit optimization, the ability to change tuner setting within a single radar pulse repetition interval (PRI) has been previously demonstrated. To carry out impedance-tuning optimization measurements for each PRI, an efficient data storage and lookup method is needed. In this article, we demonstrate how hybrid storage with a hash table can be used with an efficient, cache replacement algorithm on a software-defined radio (SDR) platform to enable continuous operation with pulse-to-pulse optimization. This data storage approach minimizes overhead in storage of circuit optimization settings, allowing faster optimization of the circuit to maximize output power. By maximizing output power quickly, it is expected that the radar will experience better signal-to-interference-plus-noise ratio and accurate detection of targets at greater ranges.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"899-909"},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324350","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 : 2024-07-08DOI: 10.1109/TRS.2024.3425275
Christos G. Tsinos;Aakash Arora;Theodoros A. Tsiftsis
In this article, the problem of linear precoding and radar receive beamforming design for joint radar-communication (JRC) systems is studied. A multiple antenna base station (BS) that serves multiple single-antenna user terminals on the downlink is assumed. Furthermore, the BS employs a simultaneous radar function in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. In this work, we jointly design the JRC linear precoder and the radar receive beamformer, thus aiming to optimize the performance of the radar part while maintaining a desired quality of service (QoS) for the communication one subject to a total transmit power constraint. To that end, we formulate a challenging fractional nonconvex optimization problem via which the optimal precoder and radar receive beamformer are derived. Then, we develop algorithmic solutions based on the majorization–minimization (MM) principle and the semidefinite relaxation (SDR) methodology for the formulated optimization problem. The performance of both the proposed solutions is examined and compared to the one of a system that supports only the radar functionality via numerical results.
{"title":"Joint Radar-Communication Systems by Optimizing Radar Performance and Quality of Service for Communication Users","authors":"Christos G. Tsinos;Aakash Arora;Theodoros A. Tsiftsis","doi":"10.1109/TRS.2024.3425275","DOIUrl":"https://doi.org/10.1109/TRS.2024.3425275","url":null,"abstract":"In this article, the problem of linear precoding and radar receive beamforming design for joint radar-communication (JRC) systems is studied. A multiple antenna base station (BS) that serves multiple single-antenna user terminals on the downlink is assumed. Furthermore, the BS employs a simultaneous radar function in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. In this work, we jointly design the JRC linear precoder and the radar receive beamformer, thus aiming to optimize the performance of the radar part while maintaining a desired quality of service (QoS) for the communication one subject to a total transmit power constraint. To that end, we formulate a challenging fractional nonconvex optimization problem via which the optimal precoder and radar receive beamformer are derived. Then, we develop algorithmic solutions based on the majorization–minimization (MM) principle and the semidefinite relaxation (SDR) methodology for the formulated optimization problem. The performance of both the proposed solutions is examined and compared to the one of a system that supports only the radar functionality via numerical results.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"778-790"},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142173955","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}
The last few years suggest the rising interest of both, academia and industry, toward the application of polarimetry in the automotive radar world. The perspective of a more accurate comprehension of the surrounding environment through the use of orthogonal polarizations has now become very attractive, given the rising number of antennas available to automotive radar technology. This article aims to present a fully polarimetric automotive radar front end. The requirements of a polarimetric automotive radar are investigated and the design of a $12 times 16$ antenna system, working in the band 76–81 GHz, and fulfilling them is presented. The system calibration was carried out using a dihedral corner reflector. Its characteristics were analyzed in detail and exploited to reach an optimal alignment with the radar, thus allowing the polarimetric calibration through the measurement of only one target and one scattering matrix. The validity of the system and the potential impact of polarimetry on automotive radar applications are verified and presented through several real-radar measurements, both in a controlled environment in the anechoic chamber and outdoors. Different applications are investigated, such as multipath detection and target classification, by applying the Pauli decomposition to the polarimetric data.
过去几年来，学术界和工业界对偏振测量法在汽车雷达领域的应用兴趣日渐浓厚。由于汽车雷达技术可使用的天线数量不断增加，通过使用正交偏振来更准确地了解周围环境的前景现在变得非常有吸引力。本文旨在介绍一种全极化汽车雷达前端。文章对极化汽车雷达的要求进行了研究，并介绍了在 76-81 GHz 频段工作并满足这些要求的 $12 times 16$ 天线系统的设计。系统校准使用了一个斜角反射器。对其特性进行了详细分析，并利用其达到与雷达的最佳对准，从而只需测量一个目标和一个散射矩阵即可进行极坐标校准。该系统的有效性以及偏振测量法对汽车雷达应用的潜在影响，通过电波暗室受控环境和室外的几次实际雷达测量得到了验证和展示。通过对极化数据应用保利分解，研究了不同的应用，如多径检测和目标分类。
{"title":"Fully Polarimetric Automotive Radar: Proof of Concept","authors":"Alessandro Tinti;Simon Tejero Alfageme;Sergi Duque Biarge;Jordi Balcells-Ventura;Nils Pohl","doi":"10.1109/TRS.2024.3423631","DOIUrl":"https://doi.org/10.1109/TRS.2024.3423631","url":null,"abstract":"The last few years suggest the rising interest of both, academia and industry, toward the application of polarimetry in the automotive radar world. The perspective of a more accurate comprehension of the surrounding environment through the use of orthogonal polarizations has now become very attractive, given the rising number of antennas available to automotive radar technology. This article aims to present a fully polarimetric automotive radar front end. The requirements of a polarimetric automotive radar are investigated and the design of a \u0000<inline-formula> <tex-math>$12 times 16$ </tex-math></inline-formula>\u0000 antenna system, working in the band 76–81 GHz, and fulfilling them is presented. The system calibration was carried out using a dihedral corner reflector. Its characteristics were analyzed in detail and exploited to reach an optimal alignment with the radar, thus allowing the polarimetric calibration through the measurement of only one target and one scattering matrix. The validity of the system and the potential impact of polarimetry on automotive radar applications are verified and presented through several real-radar measurements, both in a controlled environment in the anechoic chamber and outdoors. Different applications are investigated, such as multipath detection and target classification, by applying the Pauli decomposition to the polarimetric data.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"645-660"},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602450","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 : 2024-06-28DOI: 10.1109/TRS.2024.3420551
Nanjun Li;Fulai Wang;Chen Pang;Yongzhen Li
Aimed to enhance the robustness of simultaneously polarimetric radar (SPR) systems against interrupted-sampling repeater jamming (ISRJ) attacks by polarization and waveform diversity techniques, this article focuses on the joint design of unimodular sequences and receiving filters for jamming suppression. Specifically, we first develop a dynamic signal processing framework for target polarization scattering matrix (PSM) estimation based on their statistical properties and orthogonal conditions between receiving filters and ISRJ signals. Then, the weighted sum of integrated sidelobe levels (ISLs) of auto- and cross-ambiguity functions and signal-to-noise ratio losses (SNRLs) is minimized with unimodular and energy constraints to mitigate ISRJ in SPR systems considering both single pulse and multipulse. To handle the resulting NP-hard design problems, an iterative optimization method capitalizing on the alternating direction and majorization-minimization (MM) framework is proposed. The numerical results are provided to show the superiority of the proposed algorithm in comparison with a pair of linear frequency modulation (LFM) waveforms with opposite slopes with respect to the anti-ISRJ performance.
{"title":"Design of Doppler Resilient Sequences and Receiving Filters Against Interrupted-Sampling Repeater Jamming for Simultaneously Polarimetric Radars","authors":"Nanjun Li;Fulai Wang;Chen Pang;Yongzhen Li","doi":"10.1109/TRS.2024.3420551","DOIUrl":"https://doi.org/10.1109/TRS.2024.3420551","url":null,"abstract":"Aimed to enhance the robustness of simultaneously polarimetric radar (SPR) systems against interrupted-sampling repeater jamming (ISRJ) attacks by polarization and waveform diversity techniques, this article focuses on the joint design of unimodular sequences and receiving filters for jamming suppression. Specifically, we first develop a dynamic signal processing framework for target polarization scattering matrix (PSM) estimation based on their statistical properties and orthogonal conditions between receiving filters and ISRJ signals. Then, the weighted sum of integrated sidelobe levels (ISLs) of auto- and cross-ambiguity functions and signal-to-noise ratio losses (SNRLs) is minimized with unimodular and energy constraints to mitigate ISRJ in SPR systems considering both single pulse and multipulse. To handle the resulting NP-hard design problems, an iterative optimization method capitalizing on the alternating direction and majorization-minimization (MM) framework is proposed. The numerical results are provided to show the superiority of the proposed algorithm in comparison with a pair of linear frequency modulation (LFM) waveforms with opposite slopes with respect to the anti-ISRJ performance.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"661-676"},"PeriodicalIF":0.0,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602422","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 : 2024-06-24DOI: 10.1109/TRS.2024.3418461
Guanqun Sun;Fangzheng Zhang;Xiaoyue Yu;Yuewen Zhou;Yuhui He;Xing Wang;Shilong Pan
A photonics-based broadband single-input-multiple-output (SIMO)-orbital angular momentum (OAM) radar is proposed to implement high-resolution radar imaging. In the transmitter, a broadband linear frequency-modulated (LFM) signal is generated by an optically injected semiconductor laser and emitted by a single antenna to illuminate the target. In the receiver, a uniform circular array (UCA) collects the echoes and introduces OAM modulations before photonic frequency mixing is implemented for broadband dechirp processing. The use of microwave photonic techniques enlarges the operation bandwidth and thus improves the radar range resolution, while the SIMO structure mitigates the OAM beam divergence and energy hollow problems. Based on this SIMO-OAM radar, a super-resolution imaging method with random OAM modulation and coincidence processing is proposed to break through the azimuth resolution limitation. A proof-of-concept photonics-based $1times 16$ OAM radar is established with an 8-GHz (18–26 GHz) bandwidth, of which the range resolution reaches 2.1 cm. By using the proposed imaging method, super-resolution imaging with six times higher azimuth resolution than traditional OAM radar is achieved. In the experiment, high-resolution imaging of small-size complex targets is successfully demonstrated, verifying that the proposed system and imaging method can meet the requirement for high-resolution radar detection and high-precision target recognition.
{"title":"Photonics-Based Broadband Single-Input-Multiple- Output-OAM Coincidence Imaging","authors":"Guanqun Sun;Fangzheng Zhang;Xiaoyue Yu;Yuewen Zhou;Yuhui He;Xing Wang;Shilong Pan","doi":"10.1109/TRS.2024.3418461","DOIUrl":"https://doi.org/10.1109/TRS.2024.3418461","url":null,"abstract":"A photonics-based broadband single-input-multiple-output (SIMO)-orbital angular momentum (OAM) radar is proposed to implement high-resolution radar imaging. In the transmitter, a broadband linear frequency-modulated (LFM) signal is generated by an optically injected semiconductor laser and emitted by a single antenna to illuminate the target. In the receiver, a uniform circular array (UCA) collects the echoes and introduces OAM modulations before photonic frequency mixing is implemented for broadband dechirp processing. The use of microwave photonic techniques enlarges the operation bandwidth and thus improves the radar range resolution, while the SIMO structure mitigates the OAM beam divergence and energy hollow problems. Based on this SIMO-OAM radar, a super-resolution imaging method with random OAM modulation and coincidence processing is proposed to break through the azimuth resolution limitation. A proof-of-concept photonics-based \u0000<inline-formula> <tex-math>$1times 16$ </tex-math></inline-formula>\u0000 OAM radar is established with an 8-GHz (18–26 GHz) bandwidth, of which the range resolution reaches 2.1 cm. By using the proposed imaging method, super-resolution imaging with six times higher azimuth resolution than traditional OAM radar is achieved. In the experiment, high-resolution imaging of small-size complex targets is successfully demonstrated, verifying that the proposed system and imaging method can meet the requirement for high-resolution radar detection and high-precision target recognition.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"690-698"},"PeriodicalIF":0.0,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965319","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 : 2024-06-24DOI: 10.1109/TRS.2024.3418689
Adib Y. Nashashibi;Tanner J. Douglas;Mani Kashanianfard;Stephen W. Decker;Kamal Sarabandi
This article presents a fully polarimetric instrumentation radar designed for conducting phenomenological studies in support of autonomous vehicle research at W-band frequencies. The compact radar utilizes a unique single-antenna system with a narrow beamwidth of 1.1° (two-way) and better than 45-dB isolation between the transmit and receive signal paths. It employs the frequency-modulated continuous-wave (FMCW) modulation scheme and operates over a maximum bandwidth of 5.5 GHz centered around 79.25 GHz. The radar benefits from a low phase noise level of −86 dBc/Hz at 10-kHz offset and its receiver channels have an effective noise figure value of 2.7 dB. The calibrated radar can be used to accurately measure the polarimetric response of both point and distributed targets. It can also generate high-resolution range-velocity maps of moving targets in a given traffic scene. The radar was used to characterize the polarimetric response of slow-moving targets, such as pedestrians and bicycles. The statistics of the radar cross sections (RCSs) of these targets were computed, and unique features observed in the range-velocity maps of these targets were revealed.
{"title":"High-Resolution Polarimetric Radar for Autonomous Vehicle Research at W-Band Frequencies","authors":"Adib Y. Nashashibi;Tanner J. Douglas;Mani Kashanianfard;Stephen W. Decker;Kamal Sarabandi","doi":"10.1109/TRS.2024.3418689","DOIUrl":"https://doi.org/10.1109/TRS.2024.3418689","url":null,"abstract":"This article presents a fully polarimetric instrumentation radar designed for conducting phenomenological studies in support of autonomous vehicle research at W-band frequencies. The compact radar utilizes a unique single-antenna system with a narrow beamwidth of 1.1° (two-way) and better than 45-dB isolation between the transmit and receive signal paths. It employs the frequency-modulated continuous-wave (FMCW) modulation scheme and operates over a maximum bandwidth of 5.5 GHz centered around 79.25 GHz. The radar benefits from a low phase noise level of −86 dBc/Hz at 10-kHz offset and its receiver channels have an effective noise figure value of 2.7 dB. The calibrated radar can be used to accurately measure the polarimetric response of both point and distributed targets. It can also generate high-resolution range-velocity maps of moving targets in a given traffic scene. The radar was used to characterize the polarimetric response of slow-moving targets, such as pedestrians and bicycles. The statistics of the radar cross sections (RCSs) of these targets were computed, and unique features observed in the range-velocity maps of these targets were revealed.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"632-644"},"PeriodicalIF":0.0,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141583622","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 : 2024-06-21DOI: 10.1109/TRS.2024.3417519
Rahul Sharma;Okan Yurduseven
Accurately characterizing material properties, particularly the spatial distribution of permittivity, is crucial across diverse domains such as medical imaging, nondestructive testing, and materials science. This work introduces an innovative strategy to tackle the inverse problem of deducing the permittivity distribution within a medium by leveraging time-dependent data of the electric field distribution. The approach utilizes a neural network trained with guidance from the wave equation, embedding the fundamental physics of wave propagation within the network architecture. This integration empowers the network to assimilate domain-specific knowledge during training, combining deep learning capabilities with physics-based constraints. This hybrid framework establishes a robust relationship between the time changing electric field distribution and the underlying permittivity distribution, effectively solving the complex inverse problem. By training on a comprehensive dataset, the neural network discerns intricate variations in spatial permittivity from the intricate temporal evolution of the electric field. Results validate the effectiveness of this approach, showcasing impressive accuracy in the reconstruction of the permittivity distribution.
{"title":"Quantitative Microwave Imaging Using Deep Learning Network Guided by Plane Wave Equation","authors":"Rahul Sharma;Okan Yurduseven","doi":"10.1109/TRS.2024.3417519","DOIUrl":"https://doi.org/10.1109/TRS.2024.3417519","url":null,"abstract":"Accurately characterizing material properties, particularly the spatial distribution of permittivity, is crucial across diverse domains such as medical imaging, nondestructive testing, and materials science. This work introduces an innovative strategy to tackle the inverse problem of deducing the permittivity distribution within a medium by leveraging time-dependent data of the electric field distribution. The approach utilizes a neural network trained with guidance from the wave equation, embedding the fundamental physics of wave propagation within the network architecture. This integration empowers the network to assimilate domain-specific knowledge during training, combining deep learning capabilities with physics-based constraints. This hybrid framework establishes a robust relationship between the time changing electric field distribution and the underlying permittivity distribution, effectively solving the complex inverse problem. By training on a comprehensive dataset, the neural network discerns intricate variations in spatial permittivity from the intricate temporal evolution of the electric field. Results validate the effectiveness of this approach, showcasing impressive accuracy in the reconstruction of the permittivity distribution.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"607-617"},"PeriodicalIF":0.0,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141495026","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}
Effective monitoring of vital signs is a fundamental aspect of healthcare. To measure vital signs, patients often hesitate to wear probes and body-worn sensors for extended periods because these devices can limit their movement and cause discomfort. In this study, we present three radar-based techniques to estimate vital signs and underlying muscle expansion. The first method employs a short-time Fourier transform (STFT), but it has limitations due to its fixed resolution and its performance dependency on the carrier frequency. The second method modifies the Hilbert-Huang transform (HHT) to address the mode-mixing problem. The HHT breaks down the signal into its fundamental components. By subsequently applying Fourier transform and signal filtering, we demonstrate its feasibility of estimating heartbeat and breathing rates. In our latest method, which constitutes the primary contribution of this study, we exploit the repetitive patterns inherent in both heartbeat and breathing signals. This involves representing the spectrum of the received signal as a discrete frequency spectrum and subsequently applying harmonic accumulation. Our simulation results consistently demonstrate that the harmonics accumulation (HA) algorithm outperforms other algorithms in terms of accuracy and effectiveness. To assess the performance of our suggested algorithms, we derive the Cramér-Rao lower bound (CRLB) as a benchmark. Our results show the effectiveness of the proposed methods.
{"title":"Discovering the Unseen: Radar-Based Estimation of Heartbeat, Breathing Rate, and Underlying Muscle Expansion Without Probes","authors":"Sajid Ahmed;Pratiti Paul;Tharmalingam Ratnarajah;Mohamed-Slim Alouini","doi":"10.1109/TRS.2024.3412915","DOIUrl":"https://doi.org/10.1109/TRS.2024.3412915","url":null,"abstract":"Effective monitoring of vital signs is a fundamental aspect of healthcare. To measure vital signs, patients often hesitate to wear probes and body-worn sensors for extended periods because these devices can limit their movement and cause discomfort. In this study, we present three radar-based techniques to estimate vital signs and underlying muscle expansion. The first method employs a short-time Fourier transform (STFT), but it has limitations due to its fixed resolution and its performance dependency on the carrier frequency. The second method modifies the Hilbert-Huang transform (HHT) to address the mode-mixing problem. The HHT breaks down the signal into its fundamental components. By subsequently applying Fourier transform and signal filtering, we demonstrate its feasibility of estimating heartbeat and breathing rates. In our latest method, which constitutes the primary contribution of this study, we exploit the repetitive patterns inherent in both heartbeat and breathing signals. This involves representing the spectrum of the received signal as a discrete frequency spectrum and subsequently applying harmonic accumulation. Our simulation results consistently demonstrate that the harmonics accumulation (HA) algorithm outperforms other algorithms in terms of accuracy and effectiveness. To assess the performance of our suggested algorithms, we derive the Cramér-Rao lower bound (CRLB) as a benchmark. Our results show the effectiveness of the proposed methods.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"594-606"},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141474936","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}
This article describes a method of deriving and verifying hardware specification of a direct digital frequency synthesizer (DDFS) and radio frequency digital-to-analog converter (RFDAC)-based frequency-modulated continuous-wave (FMCW) modulator. The analysis of the concept is conducted by studying the digital nonlinearities, such as amplitude quantization noise, phase quantization noise, and frequency error in the ramp, and analog nonlinearities, such as IQ quadrature error and counter inter modulation-3 (CIM3) of the RFDAC. The impact of the nonlinearities on the detectability of target in the intermediate frequency (IF) spectrum is evaluated with the MATLAB model of the frequency modulator. The outcome of the concept evaluation predicts the low-level hardware specifications needed for the design such as amplitude quantization, phase quantization, expected noise level, spur positions in the target IF spectrum, and frequency error in the ramp. The RFDAC-based FMCW modulator is manufactured in 28-nm technology with the derived parameters and the time-domain data of a frequency ramp from 5 to 9-GHz in 100 $mu $ s is sampled during measurement. The data are postprocessed to confirm the predictions made by the simulation model and to characterize ramp linearity, dynamic phase noise (DPN), and settling time of the ramp. The frequency error for a 4-GHz ramp in 100- $mu $ s duration is ±100kHz, and the settling time in the postprocessed result is in the 20-ns range.
{"title":"Concept Evaluation of a DDFS and RFDAC-Based FMCW Modulator","authors":"Soumya Krishnapuram Sireesh;Niels Christoffers;Christoph Wagner;Andreas Stelzer","doi":"10.1109/TRS.2024.3410137","DOIUrl":"https://doi.org/10.1109/TRS.2024.3410137","url":null,"abstract":"This article describes a method of deriving and verifying hardware specification of a direct digital frequency synthesizer (DDFS) and radio frequency digital-to-analog converter (RFDAC)-based frequency-modulated continuous-wave (FMCW) modulator. The analysis of the concept is conducted by studying the digital nonlinearities, such as amplitude quantization noise, phase quantization noise, and frequency error in the ramp, and analog nonlinearities, such as IQ quadrature error and counter inter modulation-3 (CIM3) of the RFDAC. The impact of the nonlinearities on the detectability of target in the intermediate frequency (IF) spectrum is evaluated with the MATLAB model of the frequency modulator. The outcome of the concept evaluation predicts the low-level hardware specifications needed for the design such as amplitude quantization, phase quantization, expected noise level, spur positions in the target IF spectrum, and frequency error in the ramp. The RFDAC-based FMCW modulator is manufactured in 28-nm technology with the derived parameters and the time-domain data of a frequency ramp from 5 to 9-GHz in 100\u0000<inline-formula> <tex-math>$mu $ </tex-math></inline-formula>\u0000 s is sampled during measurement. The data are postprocessed to confirm the predictions made by the simulation model and to characterize ramp linearity, dynamic phase noise (DPN), and settling time of the ramp. The frequency error for a 4-GHz ramp in 100-\u0000<inline-formula> <tex-math>$mu $ </tex-math></inline-formula>\u0000 s duration is ±100kHz, and the settling time in the postprocessed result is in the 20-ns range.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"618-631"},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539221","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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