Pub Date : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149561
Yue Liu, Wenxin Li, Haiyi Mao, Cong Peng, Wei Yi
Target spawning and extended shape estimation are important problems in group target tracking. In this paper, we propose a Gaussian mixture cardinalized probability hypothesis density (GMCPHD) filter for group targets with spawning and irregular shape based on star-convex Random Hypersurface Model (RHM). In order to solve the problem of irregular group shape, we use star-convex RHM to describe the distribution of measurement sources. Besides, we use the distance division method to realize the division of measurement sets and the judgment of group splitting. On this basis, the real-time tracking of the motion state and extended shape is realized under the framework of GMCPHD. The performance of this algorithm is showcased by comparison with the elliptical RHM-based GMCPHD filter, and the results show that the proposed algorithm can improve the estimation accuracy of group shape and motion state effectively.
{"title":"The GMCPHD Filter for Irregular Group Target Spawning Based on Star-Convex RHMs","authors":"Yue Liu, Wenxin Li, Haiyi Mao, Cong Peng, Wei Yi","doi":"10.1109/RadarConf2351548.2023.10149561","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149561","url":null,"abstract":"Target spawning and extended shape estimation are important problems in group target tracking. In this paper, we propose a Gaussian mixture cardinalized probability hypothesis density (GMCPHD) filter for group targets with spawning and irregular shape based on star-convex Random Hypersurface Model (RHM). In order to solve the problem of irregular group shape, we use star-convex RHM to describe the distribution of measurement sources. Besides, we use the distance division method to realize the division of measurement sets and the judgment of group splitting. On this basis, the real-time tracking of the motion state and extended shape is realized under the framework of GMCPHD. The performance of this algorithm is showcased by comparison with the elliptical RHM-based GMCPHD filter, and the results show that the proposed algorithm can improve the estimation accuracy of group shape and motion state effectively.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130775561","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149575
B. Rigling
Many applications of radar signal processing research call for the utilization of measurements or simulations of radar target responses. As measurements are difficult to obtain, simulations are often the approach of choice, but even there, it can be difficult to access high-fidelity scattering simulations, despire a wide variety of faceted models being openly available. This tutorial paper seeks to illustrate what can be accomplished through lower fidelity single-bounce, physical optics RF scattering simulation. We seek to demonstrate the relative ease with which researchers might implement their own scattering models to support the specific needs of their projects. We demonstrate the effectiveness and limitations of this approach through comparisons of single-bounce physical optics results with high-fidelity simulations.
{"title":"Single-Bounce, Physical-Optics Radar Target Modeling","authors":"B. Rigling","doi":"10.1109/RadarConf2351548.2023.10149575","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149575","url":null,"abstract":"Many applications of radar signal processing research call for the utilization of measurements or simulations of radar target responses. As measurements are difficult to obtain, simulations are often the approach of choice, but even there, it can be difficult to access high-fidelity scattering simulations, despire a wide variety of faceted models being openly available. This tutorial paper seeks to illustrate what can be accomplished through lower fidelity single-bounce, physical optics RF scattering simulation. We seek to demonstrate the relative ease with which researchers might implement their own scattering models to support the specific needs of their projects. We demonstrate the effectiveness and limitations of this approach through comparisons of single-bounce physical optics results with high-fidelity simulations.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134290740","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149568
Zichen Kong, J. Tian, Chen Ning, W. Cui
Wideband radar systems have excellent target imaging and recognition performance because of high range resolution. However, range migration occurred in long-time coherent processing and range-Doppler sidelobes may deteriorate the performance of wideband radar systems seriously, especially in multi-target scenarios. To address the two problems above, a fast iterative adaptive approach based on long-time coherent integration outputs is proposed for wideband range-Doppler imaging. The proposed algorithm first correct range migration by Keystone transform and then suppress sidelobes of targets based on the long-time coherent integration outputs within a small processing window around mainlobes. The computational complexity of the proposed method can be further reduced thanks to employing a threshold criterion and exploiting the structure of the covariance matrix. The performance of the proposed algorithm is demonstrated by numerical examples.
{"title":"Iterative Adaptive Approach Based on Long-time Coherent Integration Outputs","authors":"Zichen Kong, J. Tian, Chen Ning, W. Cui","doi":"10.1109/RadarConf2351548.2023.10149568","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149568","url":null,"abstract":"Wideband radar systems have excellent target imaging and recognition performance because of high range resolution. However, range migration occurred in long-time coherent processing and range-Doppler sidelobes may deteriorate the performance of wideband radar systems seriously, especially in multi-target scenarios. To address the two problems above, a fast iterative adaptive approach based on long-time coherent integration outputs is proposed for wideband range-Doppler imaging. The proposed algorithm first correct range migration by Keystone transform and then suppress sidelobes of targets based on the long-time coherent integration outputs within a small processing window around mainlobes. The computational complexity of the proposed method can be further reduced thanks to employing a threshold criterion and exploiting the structure of the covariance matrix. The performance of the proposed algorithm is demonstrated by numerical examples.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133347409","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149630
R. Riddolls
An Arctic over-the-horizon radar system should be located so that the boundary of the aurora borealis lies at one-half its maximum range. At this location, the ionosphere reflection point is generally outside the aurora and auroral backscatter clutter arrives from close to the horizon. The optimal depth of an AOTHR two-dimensional receive array for clutter mitigation is given by the spread of the clutter spatial autocorrelation. Endfire element spacing is limited by the appearance of grating lobes at the horizon.
{"title":"Arctic Over-the-Horizon Radar Receive Array Design Considerations","authors":"R. Riddolls","doi":"10.1109/RadarConf2351548.2023.10149630","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149630","url":null,"abstract":"An Arctic over-the-horizon radar system should be located so that the boundary of the aurora borealis lies at one-half its maximum range. At this location, the ionosphere reflection point is generally outside the aurora and auroral backscatter clutter arrives from close to the horizon. The optimal depth of an AOTHR two-dimensional receive array for clutter mitigation is given by the spread of the clutter spatial autocorrelation. Endfire element spacing is limited by the appearance of grating lobes at the horizon.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133498858","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149617
Nasser Ojaroudi, Mostafa H Elsayed, J. Le Kernec, Ahmed S. I. Amar
This study aims to discuss the characteristics of a dual-port/dual-polarized MIMO slot antenna system with dual-band filtering for ultra-wideband (UWB) wireless communications. The proposed design configuration consists of a pair of modified arc-shaped radiation stubs with a shared ground plane in a planar form. The stubs also contain open-ended rectangular slots and W-shaped. The suggested design ground plane contains an open-ended circular slot. The results indicate that the antenna operates at frequencies 3-10.7 GHz, fully covering the UWB spectrum. Additionally, two notched-band filtering characteristics have been achieved at 5.5 and 7.5 GHz to fully suppress the interfaces from other wireless systems such as the WLAN, and X-band satellite communication downlink. Fundamental characteristics of the proposed design are evaluated. It has been determined that sufficient scattering parameters, 3D radiations, efficiency, and gain levels are all achievable with the presented UWB antenna design. The introduced antenna system meets the requirements well for MIMO and diversity applications.
{"title":"Dual-Polarized Microstrip-Fed Slot Antenna Design with Dual-Notch Filtering for Ultra-Wideband Communications","authors":"Nasser Ojaroudi, Mostafa H Elsayed, J. Le Kernec, Ahmed S. I. Amar","doi":"10.1109/RadarConf2351548.2023.10149617","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149617","url":null,"abstract":"This study aims to discuss the characteristics of a dual-port/dual-polarized MIMO slot antenna system with dual-band filtering for ultra-wideband (UWB) wireless communications. The proposed design configuration consists of a pair of modified arc-shaped radiation stubs with a shared ground plane in a planar form. The stubs also contain open-ended rectangular slots and W-shaped. The suggested design ground plane contains an open-ended circular slot. The results indicate that the antenna operates at frequencies 3-10.7 GHz, fully covering the UWB spectrum. Additionally, two notched-band filtering characteristics have been achieved at 5.5 and 7.5 GHz to fully suppress the interfaces from other wireless systems such as the WLAN, and X-band satellite communication downlink. Fundamental characteristics of the proposed design are evaluated. It has been determined that sufficient scattering parameters, 3D radiations, efficiency, and gain levels are all achievable with the presented UWB antenna design. The introduced antenna system meets the requirements well for MIMO and diversity applications.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133392922","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149708
Jing Feng, Shuang Jin, Jinajing Zhang, H. Bi
Synthetic aperture radar tomography (TomoSAR) enables three-dimensional (3-D) reconstruction of urban buildings with a high level of details. However, traditional spectrum estimation algorithms for TomoSAR inversion are usually based on large data stacks and high-resolution synthetic aperture radar (SAR) images. For the Gaofen-3 (GF-3) dataset with few available images, due to the low image resolution and large baseline intervals, traditional methods fail to achieve accurate 3-D reconstruction of the interested area. Compressed sensing (CS) method has super-resolution imaging capability in TomoSAR, which can significantly reduce the number of samples required for 3-D imaging. With the help of multi-signal compressed sensing (MCS) theory, this paper introduces a novel processing workflow to achieve 3-D reconstruction of Chinese GF-3 Satellite dataset. This workflow firstly uses two-dimensional (2-D) building footprint geographic information system (GIS) data to extract features of target building. Then, these features are introduced into the estimation as prior knowledge to improve the accuracy of TomoSAR inversion. Finally, to ensure that scatterers on the same contour line of a building are regularly arranged, we exploit total variation (TV) to constrain the distribution of these scatterers. This paper uses the GF-3 dataset to generate high-resolution 3-D point cloud of Beijing, demonstrating the potential of GF-3 satellite for 3-D imaging.
{"title":"Three-dimensional Initial Imaging Result of Chinese Gaofen-3 Satellite Based on CS-TomoSAR","authors":"Jing Feng, Shuang Jin, Jinajing Zhang, H. Bi","doi":"10.1109/RadarConf2351548.2023.10149708","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149708","url":null,"abstract":"Synthetic aperture radar tomography (TomoSAR) enables three-dimensional (3-D) reconstruction of urban buildings with a high level of details. However, traditional spectrum estimation algorithms for TomoSAR inversion are usually based on large data stacks and high-resolution synthetic aperture radar (SAR) images. For the Gaofen-3 (GF-3) dataset with few available images, due to the low image resolution and large baseline intervals, traditional methods fail to achieve accurate 3-D reconstruction of the interested area. Compressed sensing (CS) method has super-resolution imaging capability in TomoSAR, which can significantly reduce the number of samples required for 3-D imaging. With the help of multi-signal compressed sensing (MCS) theory, this paper introduces a novel processing workflow to achieve 3-D reconstruction of Chinese GF-3 Satellite dataset. This workflow firstly uses two-dimensional (2-D) building footprint geographic information system (GIS) data to extract features of target building. Then, these features are introduced into the estimation as prior knowledge to improve the accuracy of TomoSAR inversion. Finally, to ensure that scatterers on the same contour line of a building are regularly arranged, we exploit total variation (TV) to constrain the distribution of these scatterers. This paper uses the GF-3 dataset to generate high-resolution 3-D point cloud of Beijing, demonstrating the potential of GF-3 satellite for 3-D imaging.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132950989","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149718
Bosung Kana, Vikram Krishnamnurthy, Kunal Pattanayak, S. Gogineni, M. Rangaswamy
This paper addresses an adversarial inference problem involving cognitive radars. The game theoretic framework described in this paper comprises “us” and an “adversary”. Our goal is to design an external interference signal that confuses the adversary radar with given information of the signals of the radar. The optimization problem is formulated such that the signal power of the designed interference is minimized while enforcing the probability that the signal-to-clutter-plus-noise ratio (SCNR) of the radar exceeds a certain SCNR level to be less than a specified threshold. The resulting problem is a challenging optimization problem since the constraint is based on a probability density function (PDF), which is non-differentiable. By taking an expected value of the SCNR, the problem is relaxed to a convex problem using the semidefinite relaxation. The simulation results verify the performance of the designed interference using the high-fidelity modeling and simulation tool, RFView.
{"title":"Smart Interference Signal Design to a Cognitive Radar","authors":"Bosung Kana, Vikram Krishnamnurthy, Kunal Pattanayak, S. Gogineni, M. Rangaswamy","doi":"10.1109/RadarConf2351548.2023.10149718","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149718","url":null,"abstract":"This paper addresses an adversarial inference problem involving cognitive radars. The game theoretic framework described in this paper comprises “us” and an “adversary”. Our goal is to design an external interference signal that confuses the adversary radar with given information of the signals of the radar. The optimization problem is formulated such that the signal power of the designed interference is minimized while enforcing the probability that the signal-to-clutter-plus-noise ratio (SCNR) of the radar exceeds a certain SCNR level to be less than a specified threshold. The resulting problem is a challenging optimization problem since the constraint is based on a probability density function (PDF), which is non-differentiable. By taking an expected value of the SCNR, the problem is relaxed to a convex problem using the semidefinite relaxation. The simulation results verify the performance of the designed interference using the high-fidelity modeling and simulation tool, RFView.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114347968","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149583
Fangzhou Wang, Hongbin Li, A. L. Swindlehurst
Reconfigurable intelligent surface (RIS) technology is a promising approach being considered for future wireless communications due to its ability to control signal propagation with low-cost elements. This paper explores the use of an RIS for clutter mitigation and target detection in radar systems. Unlike conventional reflect-only RIS, which can only adjust the phase of the reflected signal, or active RIS, which can also amplify the reflected signal at the cost of significantly higher complexity, noise, and power consumption, we exploit hybrid RIS that can configure both the phase and modulus of the impinging signal by absorbing part of the signal energy. Such RIS can be considered as a compromise solution between conventional reflect-only and active RIS in terms of complexity, power consumption, and degrees of freedoms (DoFs). We consider two clutter suppression scenarios: with and without knowledge of the target range cell. The RIS design is formulated by minimizing the received clutter echo energy when there is no information regarding the potential target range cell. This turns out to be a convex problem and can be efficiently solved. On the other hand, when target range cell information is available, we maximize the received signal-to-noise-plus-interference ratio (SINR). The resulting non-convex optimization problem is solved through fractional programming algorithms. Numerical results are presented to demonstrate the performance of the proposed hybrid RIS in comparison with conventional RIS in clutter suppression for target detection.
{"title":"Clutter Suppression for Target Detection Using Hybrid Reconfigurable Intelligent Surfaces","authors":"Fangzhou Wang, Hongbin Li, A. L. Swindlehurst","doi":"10.1109/RadarConf2351548.2023.10149583","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149583","url":null,"abstract":"Reconfigurable intelligent surface (RIS) technology is a promising approach being considered for future wireless communications due to its ability to control signal propagation with low-cost elements. This paper explores the use of an RIS for clutter mitigation and target detection in radar systems. Unlike conventional reflect-only RIS, which can only adjust the phase of the reflected signal, or active RIS, which can also amplify the reflected signal at the cost of significantly higher complexity, noise, and power consumption, we exploit hybrid RIS that can configure both the phase and modulus of the impinging signal by absorbing part of the signal energy. Such RIS can be considered as a compromise solution between conventional reflect-only and active RIS in terms of complexity, power consumption, and degrees of freedoms (DoFs). We consider two clutter suppression scenarios: with and without knowledge of the target range cell. The RIS design is formulated by minimizing the received clutter echo energy when there is no information regarding the potential target range cell. This turns out to be a convex problem and can be efficiently solved. On the other hand, when target range cell information is available, we maximize the received signal-to-noise-plus-interference ratio (SINR). The resulting non-convex optimization problem is solved through fractional programming algorithms. Numerical results are presented to demonstrate the performance of the proposed hybrid RIS in comparison with conventional RIS in clutter suppression for target detection.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114423524","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149627
A. Oveis, E. Giusti, S. Ghio, Giulio Meucci, M. Martorella
In real-time real-world scenarios, an automatic target recognition (ATR) system may encounter new samples from unseen classes continually. Retraining a neural network by using the new and all the previous samples, whenever new data is received, imposes a considerable computational cost. Instead, incremental learning aims at learning new knowledge while preserving previous knowledge with an emphasis on computational time and storage resources. In this paper, we employ the Openmax method, which has been initially introduced for open set recognition in optical images, to assist a convolutional neural network (CNN) in incremental learning scenarios with SAR images. The new set for fine-tuning the network is constituted of the unknown samples recognized by the Openmax method together with exemplars from the old classes. Our real data analysis to validate the proposed method is performed on radar images of man-made targets from the well-known Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset.
{"title":"Incremental Learning in Synthetic Aperture Radar Images Using Openmax Algorithm","authors":"A. Oveis, E. Giusti, S. Ghio, Giulio Meucci, M. Martorella","doi":"10.1109/RadarConf2351548.2023.10149627","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149627","url":null,"abstract":"In real-time real-world scenarios, an automatic target recognition (ATR) system may encounter new samples from unseen classes continually. Retraining a neural network by using the new and all the previous samples, whenever new data is received, imposes a considerable computational cost. Instead, incremental learning aims at learning new knowledge while preserving previous knowledge with an emphasis on computational time and storage resources. In this paper, we employ the Openmax method, which has been initially introduced for open set recognition in optical images, to assist a convolutional neural network (CNN) in incremental learning scenarios with SAR images. The new set for fine-tuning the network is constituted of the unknown samples recognized by the Openmax method together with exemplars from the old classes. Our real data analysis to validate the proposed method is performed on radar images of man-made targets from the well-known Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"402 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114437311","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 : 2023-05-01DOI: 10.1109/RadarConf2351548.2023.10149789
Vinzenz Janoudi, Pirmin Schoeder, Timo Grebner, D. Schwarz, C. Waldschmidt, J. Dickmann, N. Appenrodt
High angular resolution provides improved environmental perception and increases the detection quality of extended targets. It is therefore a key requirement towards future radar systems for autonomous driving. The angular resolution of a radar system fundamentally depends on its antenna array aperture size. It is technically difficult and economically challenging to realize a large aperture radar system as a single sensor. Radar networks, consisting of multiple individual radar sensors, mitigate the challenges caused by creating a large aperture radar system. This paper presents a radar network consisting of two individual MIMO radar sensors equipped with L-shaped physical antenna arrays. L-shaped arrays for the individual sensors are chosen to achieve a rectangular equally spaced radar network vir-tual aperture. Furthermore, the paper discusses the performance of the resulting virtual aperture in the context of DoA estimation. Measurements of a bicycle, conducted with a coherently coupled radar network consisting of 768 virtual channels, demonstrate the performance of a high angular resolution radar system.
{"title":"Antenna Array Design for Coherent MIMO Radar Networks","authors":"Vinzenz Janoudi, Pirmin Schoeder, Timo Grebner, D. Schwarz, C. Waldschmidt, J. Dickmann, N. Appenrodt","doi":"10.1109/RadarConf2351548.2023.10149789","DOIUrl":"https://doi.org/10.1109/RadarConf2351548.2023.10149789","url":null,"abstract":"High angular resolution provides improved environmental perception and increases the detection quality of extended targets. It is therefore a key requirement towards future radar systems for autonomous driving. The angular resolution of a radar system fundamentally depends on its antenna array aperture size. It is technically difficult and economically challenging to realize a large aperture radar system as a single sensor. Radar networks, consisting of multiple individual radar sensors, mitigate the challenges caused by creating a large aperture radar system. This paper presents a radar network consisting of two individual MIMO radar sensors equipped with L-shaped physical antenna arrays. L-shaped arrays for the individual sensors are chosen to achieve a rectangular equally spaced radar network vir-tual aperture. Furthermore, the paper discusses the performance of the resulting virtual aperture in the context of DoA estimation. Measurements of a bicycle, conducted with a coherently coupled radar network consisting of 768 virtual channels, demonstrate the performance of a high angular resolution radar system.","PeriodicalId":168311,"journal":{"name":"2023 IEEE Radar Conference (RadarConf23)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134408409","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：