Pub Date : 2025-12-10DOI: 10.1109/TRS.2025.3638258
Zachary Sasser;Caleb Fulton;Mark Yeary
Phased array radar systems require precise calibration to ensure accurate beam steering and signal processing. Variations in antenna elements can significantly affect system performance, and traditional calibration methods, which rely on known geometries and specialized equipment, often struggle in real-world settings where data may be incomplete due to factors like amplifier saturation and diverse element configurations. To overcome these limitations, we propose a geometry-agnostic calibration approach that uses mutual coupling measurements for robust calibration, independent of specific antenna configurations. By employing various computational techniques, our method supports both in situ and initial calibration scenarios, offering flexibility for diverse radar systems, including those with nonplanar or independently deployed antennas. The proposed methodology not only generalizes prior calibration techniques but also demonstrates significant improvements in calibration accuracy and operational flexibility, making it a promising solution for applications where traditional methods are impractical.
{"title":"Geometry-Agnostic Mutual Coupling Calibration for Phased Array Radar Systems","authors":"Zachary Sasser;Caleb Fulton;Mark Yeary","doi":"10.1109/TRS.2025.3638258","DOIUrl":"https://doi.org/10.1109/TRS.2025.3638258","url":null,"abstract":"Phased array radar systems require precise calibration to ensure accurate beam steering and signal processing. Variations in antenna elements can significantly affect system performance, and traditional calibration methods, which rely on known geometries and specialized equipment, often struggle in real-world settings where data may be incomplete due to factors like amplifier saturation and diverse element configurations. To overcome these limitations, we propose a geometry-agnostic calibration approach that uses mutual coupling measurements for robust calibration, independent of specific antenna configurations. By employing various computational techniques, our method supports both in situ and initial calibration scenarios, offering flexibility for diverse radar systems, including those with nonplanar or independently deployed antennas. The proposed methodology not only generalizes prior calibration techniques but also demonstrates significant improvements in calibration accuracy and operational flexibility, making it a promising solution for applications where traditional methods are impractical.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"247-260"},"PeriodicalIF":0.0,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11297009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The space-missile bistatic radar system can achieve antisurvey, anti-interference, and payload reduction from a configuration perspective. Meanwhile, the unique conformal array and motion pattern of the missile-borne radar platform lead to a broadened clutter spectrum, which distinguishes the clutter characteristics of missile-borne radars from those of traditional planar array radars, thus causing difficulties in the moving target detection and making the clutter characteristics more irregular and complicating clutter suppression. To address these issues, this article presents a method for clutter signal modeling in a bistatic radar system with satellite transmission and missile-borne conformal array reception. Subsequently, to effectively enhance the capability of clutter suppression, a method for subarray partitioning of the conformal array is provided. Based on this, a design criterion for reducing the main lobe clutter width in the bistatic radar system with satellite transmission and missile reception is presented. Finally, the effectiveness of the proposed design criteria and modeling method, as well as the superiority of the conformal array in suppressing range-ambiguous clutter, are verified through simulations of clutter signals in the bistatic radar system with a low-Earth orbit (LEO) satellite transmitter as well as a missile-borne receiver. This article can serve as an important reference guide for the actual engineering configuration design of space-missile bistatic radar systems.
{"title":"Multichannel Clutter Modeling and Clutter Characteristic Analysis for Space-Missile Bistatic Radar Systems","authors":"Gengze Qin;Xin Lin;Lingyu Wang;Kun Qin;Penghui Huang;Zihao Zou;Jingtao Ma;Xiaoying Gu","doi":"10.1109/TRS.2025.3641937","DOIUrl":"https://doi.org/10.1109/TRS.2025.3641937","url":null,"abstract":"The space-missile bistatic radar system can achieve antisurvey, anti-interference, and payload reduction from a configuration perspective. Meanwhile, the unique conformal array and motion pattern of the missile-borne radar platform lead to a broadened clutter spectrum, which distinguishes the clutter characteristics of missile-borne radars from those of traditional planar array radars, thus causing difficulties in the moving target detection and making the clutter characteristics more irregular and complicating clutter suppression. To address these issues, this article presents a method for clutter signal modeling in a bistatic radar system with satellite transmission and missile-borne conformal array reception. Subsequently, to effectively enhance the capability of clutter suppression, a method for subarray partitioning of the conformal array is provided. Based on this, a design criterion for reducing the main lobe clutter width in the bistatic radar system with satellite transmission and missile reception is presented. Finally, the effectiveness of the proposed design criteria and modeling method, as well as the superiority of the conformal array in suppressing range-ambiguous clutter, are verified through simulations of clutter signals in the bistatic radar system with a low-Earth orbit (LEO) satellite transmitter as well as a missile-borne receiver. This article can serve as an important reference guide for the actual engineering configuration design of space-missile bistatic radar systems.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"135-151"},"PeriodicalIF":0.0,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830782","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 : 2025-12-08DOI: 10.1109/TRS.2025.3638097
{"title":"IEEE Transactions on Radar Systems Publication Information","authors":"","doi":"10.1109/TRS.2025.3638097","DOIUrl":"https://doi.org/10.1109/TRS.2025.3638097","url":null,"abstract":"","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11283130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-04DOI: 10.1109/TRS.2025.3640529
Prasanth Logaraman;Aakash Arora;Prabhu Babu
In this article, we propose a method for designing waveforms for quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM)-based joint radar-communication (JRC) systems that simultaneously minimizes the sidelobes of the ambiguity function and the peak-to-average power ratio (PAPR) of the transmit signal. Modern JRC systems require QAM-based OFDM to support higher data rates. However, the nonunimodular nature of QAM symbols leads to higher sidelobe levels (SLLs) in the ambiguity function, degrading radar sensing performance, and OFDM inherently suffers from the high PAPR. Thus, to achieve effective radar sensing and reliable communication, we propose a waveform design method that simultaneously minimizes SLLs within a specified region of the ambiguity function and the PAPR of the waveform. The resulting problem is nonconvex with a quartic objective function, which we address using an iterative method based on quadratic approximations of the quartic terms. Numerical simulations demonstrate that the proposed technique significantly reduces ambiguity function sidelobes and PAPR, thereby enhancing radar detection performance and maintaining communication reliability compared to recent methods in the literature.
{"title":"Waveform Design for OFDM-Based JRC Systems via Ambiguity Function Sidelobe and PAPR Minimization","authors":"Prasanth Logaraman;Aakash Arora;Prabhu Babu","doi":"10.1109/TRS.2025.3640529","DOIUrl":"https://doi.org/10.1109/TRS.2025.3640529","url":null,"abstract":"In this article, we propose a method for designing waveforms for quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM)-based joint radar-communication (JRC) systems that simultaneously minimizes the sidelobes of the ambiguity function and the peak-to-average power ratio (PAPR) of the transmit signal. Modern JRC systems require QAM-based OFDM to support higher data rates. However, the nonunimodular nature of QAM symbols leads to higher sidelobe levels (SLLs) in the ambiguity function, degrading radar sensing performance, and OFDM inherently suffers from the high PAPR. Thus, to achieve effective radar sensing and reliable communication, we propose a waveform design method that simultaneously minimizes SLLs within a specified region of the ambiguity function and the PAPR of the waveform. The resulting problem is nonconvex with a quartic objective function, which we address using an iterative method based on quadratic approximations of the quartic terms. Numerical simulations demonstrate that the proposed technique significantly reduces ambiguity function sidelobes and PAPR, thereby enhancing radar detection performance and maintaining communication reliability compared to recent methods in the literature.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"129-134"},"PeriodicalIF":0.0,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830785","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 : 2025-12-03DOI: 10.1109/TRS.2025.3640091
Arturo Umeyama;Stephen L. Durden;Robert M. Beauchamp;Simone Tanelli
Since 1997, Earth’s atmosphere has been continuously monitored by a number of spaceborne atmospheric radars. Only the EarthCARE cloud profiling radar has Doppler capability; others measured only reflectivity due to challenges resulting from platform motion. One concept for achieving high-accuracy Doppler measurements uses the displaced phase center antenna (DPCA) method, in which two antennas are appropriately spaced so that platform motion is canceled for pulse pairs. Our previous work initially looked at ideal DPCA performance and, most recently, effects of antenna pointing and position errors for the DPCA case where transmission alternates between the two antennas. This work completes the investigation of plausible antenna configurations’ error sources for the Doppler velocity estimation by considering the effects of antenna beamwidth differences, phase differences, and tilting of the DPCA baseline in the vertical plane. In addition to these new error sources, evaluation of all error sources for transmission on a single antenna is provided.
{"title":"DPCA-Based Doppler Radar Measurements From Space: Additional Error Sources and Single-Antenna Transmission","authors":"Arturo Umeyama;Stephen L. Durden;Robert M. Beauchamp;Simone Tanelli","doi":"10.1109/TRS.2025.3640091","DOIUrl":"https://doi.org/10.1109/TRS.2025.3640091","url":null,"abstract":"Since 1997, Earth’s atmosphere has been continuously monitored by a number of spaceborne atmospheric radars. Only the EarthCARE cloud profiling radar has Doppler capability; others measured only reflectivity due to challenges resulting from platform motion. One concept for achieving high-accuracy Doppler measurements uses the displaced phase center antenna (DPCA) method, in which two antennas are appropriately spaced so that platform motion is canceled for pulse pairs. Our previous work initially looked at ideal DPCA performance and, most recently, effects of antenna pointing and position errors for the DPCA case where transmission alternates between the two antennas. This work completes the investigation of plausible antenna configurations’ error sources for the Doppler velocity estimation by considering the effects of antenna beamwidth differences, phase differences, and tilting of the DPCA baseline in the vertical plane. In addition to these new error sources, evaluation of all error sources for transmission on a single antenna is provided.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"104-112"},"PeriodicalIF":0.0,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778425","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}
Space micromotion target recognition (SMMTR) is a key technology in space defense systems. Unlike monostatic radars, which provide only a single observation dimension, the networked radar systems offer richer information and significantly enhance target recognition performance. Traditional graph neural networks can only model binary relations, whereas hypergraph networks can effectively capture high-order complex interaction relations by allowing multiple nodes to share the same hyperedge, thereby extracting more accurate features in complex systems. In this article, a multiview adaptive hypergraph convolutional network (MVA-HGCN) architecture is proposed. The MVA-HGCN adaptively learns the hypergraph structure from two perspectives: time steps and radar entities. First, the multiscale temporal adaptive hypergraph convolutional network (MSTA-HGCN) treats time steps as hypergraph nodes at different scales. This module captures more comprehensive time-varying micromotion features across multiple temporal resolutions, reflecting the dynamic evolution of the target. Second, the radar entity adaptive hypergraph convolutional network (REA-HGCN) treats each radar as a hypergraph node. This module adaptively captures the potential complex spatial dependencies from the perspective of multisensor collaborative observation. Extensive experiments demonstrate that the proposed MVA-HGCN achieves reliable SMMTR performance even under harsh conditions of low signal-to-noise ratio (SNR) and low pulse repetition frequency (PRF). Specifically, it achieves a recognition accuracy of 93.89% at 5-dB SNR and 100-Hz PRF, representing a 4.78% improvement over the best existing method.
{"title":"Multiview Adaptive Hypergraph for Space Micromotion Target Recognition Based on Networked Radar Systems","authors":"Zhi-Hao Wang;Yuan-Peng Zhang;Kai-Ming Li;Dan Wang;Ying Luo;Qun Zhang","doi":"10.1109/TRS.2025.3639246","DOIUrl":"https://doi.org/10.1109/TRS.2025.3639246","url":null,"abstract":"Space micromotion target recognition (SMMTR) is a key technology in space defense systems. Unlike monostatic radars, which provide only a single observation dimension, the networked radar systems offer richer information and significantly enhance target recognition performance. Traditional graph neural networks can only model binary relations, whereas hypergraph networks can effectively capture high-order complex interaction relations by allowing multiple nodes to share the same hyperedge, thereby extracting more accurate features in complex systems. In this article, a multiview adaptive hypergraph convolutional network (MVA-HGCN) architecture is proposed. The MVA-HGCN adaptively learns the hypergraph structure from two perspectives: time steps and radar entities. First, the multiscale temporal adaptive hypergraph convolutional network (MSTA-HGCN) treats time steps as hypergraph nodes at different scales. This module captures more comprehensive time-varying micromotion features across multiple temporal resolutions, reflecting the dynamic evolution of the target. Second, the radar entity adaptive hypergraph convolutional network (REA-HGCN) treats each radar as a hypergraph node. This module adaptively captures the potential complex spatial dependencies from the perspective of multisensor collaborative observation. Extensive experiments demonstrate that the proposed MVA-HGCN achieves reliable SMMTR performance even under harsh conditions of low signal-to-noise ratio (SNR) and low pulse repetition frequency (PRF). Specifically, it achieves a recognition accuracy of 93.89% at 5-dB SNR and 100-Hz PRF, representing a 4.78% improvement over the best existing method.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"15-34"},"PeriodicalIF":0.0,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145729506","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 : 2025-12-01DOI: 10.1109/TRS.2025.3638995
Da Huang;Hao Zhou;Alei Chen;Yingwei Tian;Weimin Huang
Time-frequency analysis (TFA) serves as an effective technique in improving target-monitoring performance of high-frequency surface-wave radar (HFSWR). However, the potential of this technique has not been fully explored in existing schemes because the extracted time-frequency (TF) signatures are solely used for identifying targets. In addition to missed detection, target nonstationarity may also degrade parameter estimation accuracy. To address this challenge, we propose a TF-based parameter estimation scheme. In particular, we develop range and direction-of-arrival (DOA) methods that directly leverage TF signatures obtained during the detection stage to extract target parameters. These parameters are then processed for subsequent plot association and target localization stages. Statistical results on measured data show that the proposed range and DOA estimation methods outperform their conventional counterparts in accuracy. Next, these methods are integrated into the proposed parameter estimation scheme, which is then compared against existing schemes. Experimental results demonstrate that our scheme achieves better plot association performance compared with other conventional schemes. In addition, using automatic identification system (AIS) records as ground truth, our scheme achieves enhanced localization accuracy. In particular, it reduces the proportion of anomalous coordinate trajectories by 2.05%~4.11%. Moreover, by seamlessly connecting target detection and parameter estimation stages within the TF domain, this scheme streamlines the overall target-monitoring pipeline.
{"title":"Bridging the Domain Gap Between Target Detection and Parameter Estimation: A Time-Frequency Parameter Estimation Scheme for HFSWR","authors":"Da Huang;Hao Zhou;Alei Chen;Yingwei Tian;Weimin Huang","doi":"10.1109/TRS.2025.3638995","DOIUrl":"https://doi.org/10.1109/TRS.2025.3638995","url":null,"abstract":"Time-frequency analysis (TFA) serves as an effective technique in improving target-monitoring performance of high-frequency surface-wave radar (HFSWR). However, the potential of this technique has not been fully explored in existing schemes because the extracted time-frequency (TF) signatures are solely used for identifying targets. In addition to missed detection, target nonstationarity may also degrade parameter estimation accuracy. To address this challenge, we propose a TF-based parameter estimation scheme. In particular, we develop range and direction-of-arrival (DOA) methods that directly leverage TF signatures obtained during the detection stage to extract target parameters. These parameters are then processed for subsequent plot association and target localization stages. Statistical results on measured data show that the proposed range and DOA estimation methods outperform their conventional counterparts in accuracy. Next, these methods are integrated into the proposed parameter estimation scheme, which is then compared against existing schemes. Experimental results demonstrate that our scheme achieves better plot association performance compared with other conventional schemes. In addition, using automatic identification system (AIS) records as ground truth, our scheme achieves enhanced localization accuracy. In particular, it reduces the proportion of anomalous coordinate trajectories by 2.05%~4.11%. Moreover, by seamlessly connecting target detection and parameter estimation stages within the TF domain, this scheme streamlines the overall target-monitoring pipeline.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"50-65"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145729515","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 : 2025-11-27DOI: 10.1109/TRS.2025.3637892
Seyedeh Fatemeh Mirhosseini;Mohammad Alaee-Kerahroodi;Andreas E. Olk;Udo Schroeder;Bhavani Shankar Mysore R
In-car vital signs monitoring using millimeter-wave (mmWave) radar sensors has attracted growing interest due to its nonintrusive, real time, and privacy-preserving nature. Leveraging the high-resolution capabilities of mmWave radar technology, this article proposes noncontact detection of human presence and measurement of vital signs such as respiration and heartbeat within a vehicle cabin. A range of spectral analysis techniques—both parametric and nonparametric—are employed, including fast Fourier transform (FFT), periodogram, correlogram, estimation of signal parameters via rotational invariant techniques (ESPRIT), multiple signal classification (MUSIC), nonlinear least squares (NLS), and the iterative adaptive approach (IAA), to extract the vital sign information with high precision. For real-time measurements, we utilize three radar platforms operating in the 60-GHz band: the BGT60LTR11AIP (pulse Doppler), the BGT60TR13C [single-input–multiple-output (SIMO)], and the IWR6843ISK [multiple-input–multiple-output (MIMO)]. Experiments were conducted in diverse environments, including laboratory settings, on-road scenarios, and a custom test setup using a pump-embedded dummy to simulate infant vital signs. To distinguish living beings from inanimate objects, statistical features, such as variance, entropy, and the Kolmogorov–Smirnov (KS) test, are extracted and used as input to support vector machine (SVM) and $K$ -nearest neighbors (KNNs) classifiers. The proposed solution is low cost, privacy preserving, and robust against environmental interference, making it ideal for integration into next-generation intelligent transportation systems.
{"title":"In-Car Life Detection and Vital Signs Monitoring Using mmWave Radar Sensors","authors":"Seyedeh Fatemeh Mirhosseini;Mohammad Alaee-Kerahroodi;Andreas E. Olk;Udo Schroeder;Bhavani Shankar Mysore R","doi":"10.1109/TRS.2025.3637892","DOIUrl":"https://doi.org/10.1109/TRS.2025.3637892","url":null,"abstract":"In-car vital signs monitoring using millimeter-wave (mmWave) radar sensors has attracted growing interest due to its nonintrusive, real time, and privacy-preserving nature. Leveraging the high-resolution capabilities of mmWave radar technology, this article proposes noncontact detection of human presence and measurement of vital signs such as respiration and heartbeat within a vehicle cabin. A range of spectral analysis techniques—both parametric and nonparametric—are employed, including fast Fourier transform (FFT), periodogram, correlogram, estimation of signal parameters via rotational invariant techniques (ESPRIT), multiple signal classification (MUSIC), nonlinear least squares (NLS), and the iterative adaptive approach (IAA), to extract the vital sign information with high precision. For real-time measurements, we utilize three radar platforms operating in the 60-GHz band: the BGT60LTR11AIP (pulse Doppler), the BGT60TR13C [single-input–multiple-output (SIMO)], and the IWR6843ISK [multiple-input–multiple-output (MIMO)]. Experiments were conducted in diverse environments, including laboratory settings, on-road scenarios, and a custom test setup using a pump-embedded dummy to simulate infant vital signs. To distinguish living beings from inanimate objects, statistical features, such as variance, entropy, and the Kolmogorov–Smirnov (KS) test, are extracted and used as input to support vector machine (SVM) and <inline-formula> <tex-math>$K$ </tex-math></inline-formula>-nearest neighbors (KNNs) classifiers. The proposed solution is low cost, privacy preserving, and robust against environmental interference, making it ideal for integration into next-generation intelligent transportation systems.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"207-231"},"PeriodicalIF":0.0,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11270963","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1109/TRS.2025.3637451
Krishna Mohan Boga;Divyabramham Kandimalla;Arijit De
In this article, the bistatic radar cross section (RCS) of curved plates has been presented using the curved screen uniform theory of diffraction (CSUTD) for a bistatic angle 45°. The reflected field formulations for both convex side and concave side incidences on the cylindrically curved screen are provided for the bistatic case. The incident field and reflected field phase detours (PDs) are obtained for the bistatic case as they are essential in formulating the diffracted field. These PDs play a critical role in providing the continuity of the fields at and around the shadow boundaries due to the straight edges of the curved screen. In addition, the reciprocity condition has been verified with respect to the case of grazing incidence at the edges. The electromagnetic scattering due to plane wave incidence on the concave side of the curved screen is also presented using the CSUTD. The predictions of the CSUTD are compared with the results of the method-of-moments-based electromagnetic simulation tool.
{"title":"Bistatic Radar Cross Section of Curved Plates Using Curved Screen Uniform Theory of Diffraction","authors":"Krishna Mohan Boga;Divyabramham Kandimalla;Arijit De","doi":"10.1109/TRS.2025.3637451","DOIUrl":"https://doi.org/10.1109/TRS.2025.3637451","url":null,"abstract":"In this article, the bistatic radar cross section (RCS) of curved plates has been presented using the curved screen uniform theory of diffraction (CSUTD) for a bistatic angle 45°. The reflected field formulations for both convex side and concave side incidences on the cylindrically curved screen are provided for the bistatic case. The incident field and reflected field phase detours (PDs) are obtained for the bistatic case as they are essential in formulating the diffracted field. These PDs play a critical role in providing the continuity of the fields at and around the shadow boundaries due to the straight edges of the curved screen. In addition, the reciprocity condition has been verified with respect to the case of grazing incidence at the edges. The electromagnetic scattering due to plane wave incidence on the concave side of the curved screen is also presented using the CSUTD. The predictions of the CSUTD are compared with the results of the method-of-moments-based electromagnetic simulation tool.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"66-75"},"PeriodicalIF":0.0,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145729479","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}
Automotive radars are one of the essential enablers of advanced driver assistance systems (ADASs). Continuous monitoring of the functional safety (FuSa) and reliability of automotive radars is a crucial requirement to prevent accidents and increase road safety. One of the most critical aspects to monitor in this context is radar channel imbalances, as they are a key parameter regarding the reliability of the radar. These imbalances may originate from several parameter variations or hardware fatigues, e.g., a solder ball break (SBB), and may affect some radar processing steps, such as the angle of arrival estimation. In this work, a novel method for online estimation of automotive radar channel imbalances is proposed. The proposed method exploits a normalized least mean squares (NLMS) algorithm as a block in the processing chain of the radar to estimate the channel imbalances. The input of this block is the detected targets in the range-Doppler (R-D) map of the radar on the road without any prior knowledge of the angular parameters of the targets. This property, in combination with the low computational complexity (CC) of the NLMS, makes the proposed method suitable for online channel imbalance estimation, in parallel to the normal operation of the radar. Furthermore, it features reduced dependency on specific targets of interest and faster update rates of the channel imbalance estimation compared to the majority of state-of-the-art methods. This improvement is achieved by allowing for multiple targets in the angular spectrum, whereas most other methods are restricted to only a single target in the angular spectrum. The performance of the proposed method is validated using various simulation scenarios and is supported by measurement results.
{"title":"Automotive Radar Online Channel Imbalance Estimation via NLMS","authors":"Esmaeil Kavousi Ghafi;Oliver Lang;Matthias Wagner;Alexander Melzer;Mario Huemer","doi":"10.1109/TRS.2025.3634195","DOIUrl":"https://doi.org/10.1109/TRS.2025.3634195","url":null,"abstract":"Automotive radars are one of the essential enablers of advanced driver assistance systems (ADASs). Continuous monitoring of the functional safety (FuSa) and reliability of automotive radars is a crucial requirement to prevent accidents and increase road safety. One of the most critical aspects to monitor in this context is radar channel imbalances, as they are a key parameter regarding the reliability of the radar. These imbalances may originate from several parameter variations or hardware fatigues, e.g., a solder ball break (SBB), and may affect some radar processing steps, such as the angle of arrival estimation. In this work, a novel method for online estimation of automotive radar channel imbalances is proposed. The proposed method exploits a normalized least mean squares (NLMS) algorithm as a block in the processing chain of the radar to estimate the channel imbalances. The input of this block is the detected targets in the range-Doppler (R-D) map of the radar on the road without any prior knowledge of the angular parameters of the targets. This property, in combination with the low computational complexity (CC) of the NLMS, makes the proposed method suitable for online channel imbalance estimation, in parallel to the normal operation of the radar. Furthermore, it features reduced dependency on specific targets of interest and faster update rates of the channel imbalance estimation compared to the majority of state-of-the-art methods. This improvement is achieved by allowing for multiple targets in the angular spectrum, whereas most other methods are restricted to only a single target in the angular spectrum. The performance of the proposed method is validated using various simulation scenarios and is supported by measurement results.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"86-103"},"PeriodicalIF":0.0,"publicationDate":"2025-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11251361","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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