Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104390
Tianyu Cao, Wenqiang Pu, Pengyu Zhang, Z. Luo
Conformal array is attractive due to its flexibility to attach to different shape of surface. However, beam pattern synthesis for conformal array to control power side lobes and different polarization components for two dimensional angle space is a challenge, especially the degree of freedom is limited. In this work, we propose a robust beam pattern synthesis formulation for conformal array based on constrained convex optimization. By penalizing the maximum gain of cross-polarization component levels, power side lobes and different polarization components are controlled in a manner that the number of constraints is no longer limited by the array DoF. The proposed formulation is a convex second-order cone programming, a computationally efficient algorithm based on the alternating directions of multipliers method is designed to solve it. Simulations demonstrate the effectiveness of the proposed formulation to synthesize a desired pattern with robustness.
{"title":"Beam Pattern Synthesis for Conformal Array with Sidelobe and Polarization Control: A Penalized Inequality Approach","authors":"Tianyu Cao, Wenqiang Pu, Pengyu Zhang, Z. Luo","doi":"10.1109/SAM48682.2020.9104390","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104390","url":null,"abstract":"Conformal array is attractive due to its flexibility to attach to different shape of surface. However, beam pattern synthesis for conformal array to control power side lobes and different polarization components for two dimensional angle space is a challenge, especially the degree of freedom is limited. In this work, we propose a robust beam pattern synthesis formulation for conformal array based on constrained convex optimization. By penalizing the maximum gain of cross-polarization component levels, power side lobes and different polarization components are controlled in a manner that the number of constraints is no longer limited by the array DoF. The proposed formulation is a convex second-order cone programming, a computationally efficient algorithm based on the alternating directions of multipliers method is designed to solve it. Simulations demonstrate the effectiveness of the proposed formulation to synthesize a desired pattern with robustness.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"17 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78459035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104384
Chaoqun Yang, Xiaofeng Wang, Heng Zhang, Yu Zheng
Detect-before-track-based cognitive radars in which threshold detections are taken as the input of tracking, irreversibly result in high false alarm under the case of low signal-to-noise ratio (SNR). To solve this problem, in this paper, we propose a framework of cognitive radars based on track-beforedetect (TBD) technique. This framework includes the TBD measurement model consisting of received ambiguity function without threshold detection, cubature Kalman filter to estimate target state, and the feedback mechanism and optimization criterion for the next transmitted waveform. In particular, waveform design problem in the TBD-based cognitive radars is emphasized. This work opens the door to the cognitive radars based on TBD technique, and reveals their potential in target tracking under the case of low SNR. Numerical results demonstrate that better target tracking performance can be achieved by the TBD-based cognitive radars, as compared with conventional radars.
{"title":"Waveform Design For Track-Before-Detect-Based Cognitive Radars","authors":"Chaoqun Yang, Xiaofeng Wang, Heng Zhang, Yu Zheng","doi":"10.1109/SAM48682.2020.9104384","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104384","url":null,"abstract":"Detect-before-track-based cognitive radars in which threshold detections are taken as the input of tracking, irreversibly result in high false alarm under the case of low signal-to-noise ratio (SNR). To solve this problem, in this paper, we propose a framework of cognitive radars based on track-beforedetect (TBD) technique. This framework includes the TBD measurement model consisting of received ambiguity function without threshold detection, cubature Kalman filter to estimate target state, and the feedback mechanism and optimization criterion for the next transmitted waveform. In particular, waveform design problem in the TBD-based cognitive radars is emphasized. This work opens the door to the cognitive radars based on TBD technique, and reveals their potential in target tracking under the case of low SNR. Numerical results demonstrate that better target tracking performance can be achieved by the TBD-based cognitive radars, as compared with conventional radars.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83050909","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}
Intelligent reflecting surface (IRS) has drawn a lot of attention recently as a promising new solution to achieve high spectral and energy efficiency for future wireless networks. Prior works on IRS mainly rely on the instantaneous channel state information (I-CSI), which, however, is practically difficult to obtain for IRS-associated links due to its passive operation and large number of elements. To overcome this difficulty, we propose in this paper a new two-timescale (TTS) transmission protocol to maximize the achievable average sum-rate for an IRS-aided multiuser system. Specifically, the passive IRS phase-shifts are first optimized based on the statistical CSI (S-CSI) of all links, which varies much slowly as compared to their I-CSI, while the transmit beamforming/precoding vectors at the access point (AP) are then designed to cater to the I-CSI of the users' effective channels with the optimized IRS phase-shifts, thus significantly reducing the channel training overhead and passive beamforming complexity over the existing schemes based on the I-CSI of all channels. Simulation results are presented to validate the effectiveness of our proposed algorithm.
{"title":"Two-timescale Beamforming Optimization for Intelligent Reflecting Surface Enhanced Wireless Network","authors":"Ming-Min Zhao, Qingqing Wu, Min-Jian Zhao, Rui Zhang","doi":"10.1109/SAM48682.2020.9104346","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104346","url":null,"abstract":"Intelligent reflecting surface (IRS) has drawn a lot of attention recently as a promising new solution to achieve high spectral and energy efficiency for future wireless networks. Prior works on IRS mainly rely on the instantaneous channel state information (I-CSI), which, however, is practically difficult to obtain for IRS-associated links due to its passive operation and large number of elements. To overcome this difficulty, we propose in this paper a new two-timescale (TTS) transmission protocol to maximize the achievable average sum-rate for an IRS-aided multiuser system. Specifically, the passive IRS phase-shifts are first optimized based on the statistical CSI (S-CSI) of all links, which varies much slowly as compared to their I-CSI, while the transmit beamforming/precoding vectors at the access point (AP) are then designed to cater to the I-CSI of the users' effective channels with the optimized IRS phase-shifts, thus significantly reducing the channel training overhead and passive beamforming complexity over the existing schemes based on the I-CSI of all channels. Simulation results are presented to validate the effectiveness of our proposed algorithm.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"229 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83679774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104379
Yulei Qian, Daiyin Zhu
An algorithm is presented in this paper to focus the azimuth periodically gapped SAR (Synthetic Aperture Radar) raw data. The proposed algorithm mainly contains phase multiplication in range frequency domain and sparse reconstruction in range Doppler domain. The phase multiplication in range frequency domain aims to acquire sparser data in range Doppler domain. Then, the complex iterative thresholding algorithm is utilized to reconstruct the complete SAR data in range Doppler domain. The iterative thresholding algorithm is extended to cope with the complex SAR data. Afterwards, the traditional SAR focusing methods are capable of obtaining image from the recovered data. The proposed method performs well on suppressing ghost targets induced by gapping. Point target simulation is implemented to assess the validity of the proposed method. In addition, real SAR data experiment is also utilized to demonstrate the effectiveness of the proposed method.
{"title":"Suppression of Ghost Targets in Focusing Azimuth Periodically Gapped SAR Raw Data with Complex Iterative Thresholding Algorithm","authors":"Yulei Qian, Daiyin Zhu","doi":"10.1109/SAM48682.2020.9104379","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104379","url":null,"abstract":"An algorithm is presented in this paper to focus the azimuth periodically gapped SAR (Synthetic Aperture Radar) raw data. The proposed algorithm mainly contains phase multiplication in range frequency domain and sparse reconstruction in range Doppler domain. The phase multiplication in range frequency domain aims to acquire sparser data in range Doppler domain. Then, the complex iterative thresholding algorithm is utilized to reconstruct the complete SAR data in range Doppler domain. The iterative thresholding algorithm is extended to cope with the complex SAR data. Afterwards, the traditional SAR focusing methods are capable of obtaining image from the recovered data. The proposed method performs well on suppressing ghost targets induced by gapping. Point target simulation is implemented to assess the validity of the proposed method. In addition, real SAR data experiment is also utilized to demonstrate the effectiveness of the proposed method.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"12 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89913268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104295
Payal Gupta, M. Agrawal
Increasing the number of sources to be processed from a given array of sensors is an important problem in sensor array signal processing and of interest to many researchers. This problem has also been tackled with the virtual array based approach where the covariance and cumulant lags provide a virtual sensor. Here, an important parameter which affects the parameter estimation accuracy and latency is weight function. The weight function is defined as the frequency of occurrence of each virtual sensor in the virtual array. We provide the close-form expression of virtual array corresponding to linear array. We have also analytically evaluated the weight function of virtual array and have also studied the effect of the weight function on parameter estimation. Simulation results show the parameter estimation accuracy is significantly improve with high weight function.
{"title":"Computation of Weight Function of 2qth Order Virtual Array to Analyse the Estimation Performance","authors":"Payal Gupta, M. Agrawal","doi":"10.1109/SAM48682.2020.9104295","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104295","url":null,"abstract":"Increasing the number of sources to be processed from a given array of sensors is an important problem in sensor array signal processing and of interest to many researchers. This problem has also been tackled with the virtual array based approach where the covariance and cumulant lags provide a virtual sensor. Here, an important parameter which affects the parameter estimation accuracy and latency is weight function. The weight function is defined as the frequency of occurrence of each virtual sensor in the virtual array. We provide the close-form expression of virtual array corresponding to linear array. We have also analytically evaluated the weight function of virtual array and have also studied the effect of the weight function on parameter estimation. Simulation results show the parameter estimation accuracy is significantly improve with high weight function.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89206101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104381
Mohammad Mohammad, G. Cui, Xianxiang Yu, M. Ahmed, Ashenafi Yadessa Gemechu
At present, the integrated radar and communication (RadCom) system has attracted much attention. It has several advantages such as power consumption, reducing system size, weight,...etc. This paper proposes a power allocation strategy for the RadCom system in signal-dependent clutter, where both systems use the Orthogonal Frequency Division Multiplexing (OFDM) waveform. The convex optimization problem is formulated and solved analytically by using the Karush-Kuhn-Tuckers (KKT) optimality conditions. The proposed strategy minimizes the total transmitted power while fulfilling the two systems requirements i.e., Signal-to-Clutter-plus-Noise Ratio (SCNR) for the target detection performance and Data Information Rate (DIR) for the communication system performance. Finally, the simulation results are presented to verify the effectiveness of the proposed power allocation strategy.
{"title":"Power Allocation Strategy for OFDM Waveform in RadCom Systems","authors":"Mohammad Mohammad, G. Cui, Xianxiang Yu, M. Ahmed, Ashenafi Yadessa Gemechu","doi":"10.1109/SAM48682.2020.9104381","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104381","url":null,"abstract":"At present, the integrated radar and communication (RadCom) system has attracted much attention. It has several advantages such as power consumption, reducing system size, weight,...etc. This paper proposes a power allocation strategy for the RadCom system in signal-dependent clutter, where both systems use the Orthogonal Frequency Division Multiplexing (OFDM) waveform. The convex optimization problem is formulated and solved analytically by using the Karush-Kuhn-Tuckers (KKT) optimality conditions. The proposed strategy minimizes the total transmitted power while fulfilling the two systems requirements i.e., Signal-to-Clutter-plus-Noise Ratio (SCNR) for the target detection performance and Data Information Rate (DIR) for the communication system performance. Finally, the simulation results are presented to verify the effectiveness of the proposed power allocation strategy.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"51 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76545547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104288
Chih-Chung Hsu, Kuan Huang
Generative adversarial nets (GAN) have been widely used in several image restoration tasks such as image denoise, enhancement, and super-resolution. The objective functions of an image super-resolution problem based on GANs usually are reconstruction error, semantic feature distance, and GAN loss. In general, semantic feature distance was used to measure the feature similarity between the super-resolved and ground-truth images, to ensure they have similar feature representations. However, the feature is usually extracted by the pre-trained model, in which the feature representation is not designed for distinguishing the extracted features from low-resolution and high-resolution images. In this study, a coupled adversarial net (CAN) based on Siamese Network Structure is proposed, to improve the effectiveness of the feature extraction. In the proposed CAN, we offer GAN loss and semantic feature distances simultaneously, reducing the training complexity as well as improving the performance. Extensive experiments conducted that the proposed CAN is effective and efficient, compared to state-of-the-art image super-resolution schemes.
{"title":"Coupled Adversarial Learning for Single Image Super-Resolution","authors":"Chih-Chung Hsu, Kuan Huang","doi":"10.1109/SAM48682.2020.9104288","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104288","url":null,"abstract":"Generative adversarial nets (GAN) have been widely used in several image restoration tasks such as image denoise, enhancement, and super-resolution. The objective functions of an image super-resolution problem based on GANs usually are reconstruction error, semantic feature distance, and GAN loss. In general, semantic feature distance was used to measure the feature similarity between the super-resolved and ground-truth images, to ensure they have similar feature representations. However, the feature is usually extracted by the pre-trained model, in which the feature representation is not designed for distinguishing the extracted features from low-resolution and high-resolution images. In this study, a coupled adversarial net (CAN) based on Siamese Network Structure is proposed, to improve the effectiveness of the feature extraction. In the proposed CAN, we offer GAN loss and semantic feature distances simultaneously, reducing the training complexity as well as improving the performance. Extensive experiments conducted that the proposed CAN is effective and efficient, compared to state-of-the-art image super-resolution schemes.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"35 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78189836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104265
Chenwei Liu, Xudong Wang, Daiyin Zhu
As a novel SAR imaging mode, the ideal state of VideoSAR system is to perform real-time processing of radar echoes with high frame rate on airborne platform. Compared with previous studies on hardware acceleration processing of individual module, this paper makes a further attempt on the implementation of VideoSAR system. An FPGA-based high-resolution ground playback system for airborne VideoSAR including data transmission, imaging, autofocus, geometric distortion correction and display interface is designed in this study. Through the frame-by-frame extraction of radar raw data, which is collected to FLASH during the flight, the process of high-resolution, high frame rate video SAR playback imaging is completed on the ground. It can be verified that the system can convert a frame of 16K×2K raw data into 4K×2K SAR image within 1 second, and is expected to support onboard real-time processing in the future, which provides a valuable reference for the further development of VideoSAR system.
{"title":"An Airborne VideoSAR High-resolution Ground Playback System Based on FPGA","authors":"Chenwei Liu, Xudong Wang, Daiyin Zhu","doi":"10.1109/SAM48682.2020.9104265","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104265","url":null,"abstract":"As a novel SAR imaging mode, the ideal state of VideoSAR system is to perform real-time processing of radar echoes with high frame rate on airborne platform. Compared with previous studies on hardware acceleration processing of individual module, this paper makes a further attempt on the implementation of VideoSAR system. An FPGA-based high-resolution ground playback system for airborne VideoSAR including data transmission, imaging, autofocus, geometric distortion correction and display interface is designed in this study. Through the frame-by-frame extraction of radar raw data, which is collected to FLASH during the flight, the process of high-resolution, high frame rate video SAR playback imaging is completed on the ground. It can be verified that the system can convert a frame of 16K×2K raw data into 4K×2K SAR image within 1 second, and is expected to support onboard real-time processing in the future, which provides a valuable reference for the further development of VideoSAR system.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"40 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74724273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104366
Shohei Hamada, K. Ichige
This paper discusses the maximum number of sources when their direction of arrivals (DOAs) are estimated by the method of direction estimation (MODE), and presents a modified version of MODE that can estimate more number of sources than that by the original MODE. It is well-known that M-element array can basically estimate up to (M – 1) DOAs, however the application of MODE may reduce up to M/2 DOAs because of its computation procedure . We propose a novel DOA estimation method by modifying MODE to employ peak-search of the primary eigenvector beam patterns instead of the null-search in the original MODE. Performance of the proposed method is evaluated through computer simulation.
{"title":"A Note on The Maximum Number of Sources in DOA Estimation by MODE","authors":"Shohei Hamada, K. Ichige","doi":"10.1109/SAM48682.2020.9104366","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104366","url":null,"abstract":"This paper discusses the maximum number of sources when their direction of arrivals (DOAs) are estimated by the method of direction estimation (MODE), and presents a modified version of MODE that can estimate more number of sources than that by the original MODE. It is well-known that M-element array can basically estimate up to (M – 1) DOAs, however the application of MODE may reduce up to M/2 DOAs because of its computation procedure . We propose a novel DOA estimation method by modifying MODE to employ peak-search of the primary eigenvector beam patterns instead of the null-search in the original MODE. Performance of the proposed method is evaluated through computer simulation.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"206 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75488041","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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