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Cramèr-Rao lower bounds for radar parameter estimation in noise plus structured interference 噪声加结构干扰下雷达参数估计的cram<s:1> r- rao下界
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485105
M. Masarik, N. Subotic
{"title":"Cramèr-Rao lower bounds for radar parameter estimation in noise plus structured interference","authors":"M. Masarik, N. Subotic","doi":"10.1109/RADAR.2016.7485105","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485105","url":null,"abstract":"This document derives approximate expressions for the Cramèr-Rao lower bounds on the variance of unbiased estimates of the parameters of a narrow-band radar model in the presence of additive white Gaussian noise as well as interference with known structure. We show that the Cramèr-Rao lower bounds with interference are comprised of the bound when the interference is not present and a term that is proportional to the squared normalized-correlation between the radar signal and the interfering signal. Numerical simulations demonstrating these bounds are shown and the threshold effect is observed. The bounds are then used to define an objective function to be used for waveform co-design, and a simple example of this is shown.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114172946","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}
引用次数: 8
Radar fall motion detection using deep learning 使用深度学习的雷达坠落运动检测
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485147
B. Jokanović, M. Amin, F. Ahmad
{"title":"Radar fall motion detection using deep learning","authors":"B. Jokanović, M. Amin, F. Ahmad","doi":"10.1109/RADAR.2016.7485147","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485147","url":null,"abstract":"Radar has a great potential to be one of the leading technologies to perform in-home monitoring of elderly. Radar signal returns corresponding to human gross-motor activities are nonstationary in nature. As such, time-frequency (TF) analysis plays a fundamental role in revealing constant and higher order velocity components of various parts of the human body under motion which are important for motion discrimination. In this paper, we consider radar for fall detection using TF-based deep learning approach. The proposed approach learns and captures the intricate properties of the TF signatures without human intervention and feeds the underlying features to the classifier. Experimental data is used to demonstrate the effectiveness of the proposed fall detection deep learning approach in comparison with the principal component analysis method and techniques incorporating manual selections of a few dominant features.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114373981","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}
引用次数: 133
An azimuth-variant autofocus scheme of bistatic forward-looking synthetic aperture radar 双基地前视合成孔径雷达变方位角自动对焦方案
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485170
Yulin Huang, Wei Pu, Junjie Wu, Jianyu Yang, Youxin Lv
{"title":"An azimuth-variant autofocus scheme of bistatic forward-looking synthetic aperture radar","authors":"Yulin Huang, Wei Pu, Junjie Wu, Jianyu Yang, Youxin Lv","doi":"10.1109/RADAR.2016.7485170","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485170","url":null,"abstract":"In bistatic forward-looking synthetic aperture radar (BFSAR), conventional autofocus algorithms cannot estimate the phase errors accurately when the range walk is compensated in the azimuthal time domain. This problem stems form the influence of the azimuth-variant Doppler coefficients after linear range cell migration correction (LRCMC) in azimuthal time domain. To cope with such a problem, an estimation equalization-estimation (EEE) autofocus scheme for BFSAR is proposed. Different from the conventional autofocus method, the azimuth-variant Doppler coefficients are additionally estimated and equalized. As the influence of azimuth-variant Doppler coefficients has been greatly reduced, conventional autofocus method is subsequently applied for accurate phase error retrieval. Simulation results demonstrate the validity of the proposed method on the improvement of autofocus in BFSAR.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127556486","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}
引用次数: 5
Radio frequency interference suppression in ultra-wideband synthetic aperture radar using range-azimuth sparse and low-rank model 利用距离-方位稀疏低秩模型抑制超宽带合成孔径雷达射频干扰
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485144
S. Joy, L. Nguyen, T. Tran
{"title":"Radio frequency interference suppression in ultra-wideband synthetic aperture radar using range-azimuth sparse and low-rank model","authors":"S. Joy, L. Nguyen, T. Tran","doi":"10.1109/RADAR.2016.7485144","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485144","url":null,"abstract":"Ultra-wideband (UWB) Synthetic Aperture Radars (SAR) operate over a large bandwidth ranging from under 100 MHz to over a few Ghz. They often share spectrum with other systems such as radio, TV and cellular networks. The mitigation of radio frequency interference(RFI) from these sources is an important problem for UWB SAR systems. Traditional RFI suppression techniques such as notch filtering introduce side effects such as large sidelobes or poor peak-to-sidelobe ratio. More recently, methods based on sparsity and compressive sensing that do not have these side effects have been proposed. In particular, a sparse and low-rank method that models SAR data as a linear combination shifted SAR pulses and RFI to be of low-rank has been found to be effective. This model however uses the structure of SAR data in down-range direction only and ignores the structure in azimuth direction. In this paper, we propose to replace the data model with a new sparse model that incorporates structure in azimuth direction as well. We demonstrate that the new model has significantly better performance than the previously proposed model. It performs robustly even in the presence of high level of noise(-20 dB SNR) and does not suppress small targets like the previously proposed model did.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126943944","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}
引用次数: 20
Chirp diversity waveform design and detection by stretch processing 啁啾分集波形设计及拉伸处理检测
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485174
Amro Lulu, B. Mobasseri
{"title":"Chirp diversity waveform design and detection by stretch processing","authors":"Amro Lulu, B. Mobasseri","doi":"10.1109/RADAR.2016.7485174","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485174","url":null,"abstract":"Pulse trains are among the most commonly used waveforms in radar. Examples are pulse-Doppler radar, stepped-frequency, up-down chirps, stepped-chirps and frequency-coded waveforms, among others. In this work, we propose a pulse train modeled after chirplet chains where the basic elements of the waveform are contiguous linear chirps of arbitrary chirp rates and offset frequencies without using frequency coding. The receiver structure employs a bank of stretch processors each tuned to different chirps. The beat frequencies are separated from the cross term spectra by tuning the slopes and offsets of the individual chirps. The waveform can also be tuned to remove the range-Doppler coupling common to linear chirps. The detector can handle delays in the fraction of the pulse width, Doppler, as well as clutter suppression by isolating secondary target returns.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128089241","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}
引用次数: 6
Automotive MIMO radar for urban environments 用于城市环境的汽车MIMO雷达
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485215
I. Bilik, Oded Bialer, S. Villeval, H. Sharifi, K. Kona, Marcus Pan, D. Persechini, Marcel Musni, K. Geary
{"title":"Automotive MIMO radar for urban environments","authors":"I. Bilik, Oded Bialer, S. Villeval, H. Sharifi, K. Kona, Marcus Pan, D. Persechini, Marcel Musni, K. Geary","doi":"10.1109/RADAR.2016.7485215","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485215","url":null,"abstract":"A high azimuth and elevation resolution multiple-input-multiple-output(MIMO) radar prototype with 16 Tx and 16 Rx antenna elements was developed in this work to address the autonomous driving vehicle challenges in complex urban environments. This article describes the technological scope of the developed prototype, details the performance challenges and discusses the system design considerations. The main goal of the developed automotive radar prototype is to achieve a high 2D angular resolution in the presence of a large number of radar echoes while maintaining an industry acceptable antenna aperture size and reasonable cost.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128108652","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}
引用次数: 63
Multi-carrier MIMO radar: A concept of sparse array for improved DOA estimation 多载波MIMO雷达:改进DOA估计的稀疏阵列概念
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485156
Michael Ulrich, Bin Yang
{"title":"Multi-carrier MIMO radar: A concept of sparse array for improved DOA estimation","authors":"Michael Ulrich, Bin Yang","doi":"10.1109/RADAR.2016.7485156","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485156","url":null,"abstract":"In this paper we propose a multi-carrier (MC) based sparse array for improved direction-of-arrival (DOA) estimation. We use a spatial (physical or virtual) array of a small number of antennas, but with a large aperture to achieve a high DOA estimation accuracy. The resulting problem of grating lobes (spatial aliasing) is addressed by using multiple carrier frequencies. In contrast to the single-carrier case, by a suitable choice of multiple carrier frequencies the resulting antenna position-to-wavelength ratios can be used to satisfy the spatial anti-aliasing condition. We present such design rules in this paper. A new problem, however, is that a target range results in different phase changes for different carriers. This is the MC range-DOA coupling. We both discuss the joint range-DOA deterministic maximum likelihood estimation and a simplified DOA estimation algorithm with range elimination. Their performance in simulations are compared to the Cramer-Rao bound.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"90 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126860410","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}
引用次数: 11
Fast iterative interpolated beamforming for high fidelity single snapshot DOA estimation 用于高保真单快照DOA估计的快速迭代插值波束形成
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485275
E. Aboutanios, A. Hassanien, M. Amin, A. Zoubir
{"title":"Fast iterative interpolated beamforming for high fidelity single snapshot DOA estimation","authors":"E. Aboutanios, A. Hassanien, M. Amin, A. Zoubir","doi":"10.1109/RADAR.2016.7485275","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485275","url":null,"abstract":"We propose fast direction-of-arrival (DOA) estimation of multiple sources using a single snapshot. This problem arises in many practical applications and is pertinent to automotive radar. Existing beamforming algorithms incur a high computational cost as they usually require significant zero-padding or fail to fully remove the bias that results from the spectral leakage, especially at high signal to noise ratios (SNRs). We demonstrate superior performance of an iterative interpolated beamforming algorithm which is based on a recently introduced fast and accurate frequency estimation method. This algorithm has a computational complexity of the same order as the fast Fourier transform (FFT), yet is capable of delivering high-fidelity multi-source DOA estimates that can achieve the CRB. Two modifications are proposed to further enhance the algorithm threshold performance and reduce its computational cost. DOA estimation accuracy and computational simplicity of the proposed technique are demonstrated using simulations involving relevant automotive scenarios.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127105836","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}
引用次数: 11
Cramer-Rao Lower Bound assessment when using bistatic clutter mitigation techniques 使用双基地杂波减缓技术时的Cramer-Rao下限评估
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485093
Marsal A. Bruna, K. Bing, M. Minges
{"title":"Cramer-Rao Lower Bound assessment when using bistatic clutter mitigation techniques","authors":"Marsal A. Bruna, K. Bing, M. Minges","doi":"10.1109/RADAR.2016.7485093","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485093","url":null,"abstract":"This paper describes a new method to compare the effectiveness of bistatic clutter mitigation techniques. A combination of a high-fidelity simulation and Cramer-Rao Lower Bounds (CRLBs) is used to determine angle, velocity, and range estimation accuracies. This approach allows the assessment of bistatic clutter mitigation techniques over a wide area in a computationally efficient manner, rather than at a restricted number of specific locations. It enables the development of a trade space analysis; i.e., parameters of the bistatic configuration are varied and the effectiveness of the techniques compared. Estimation accuracies are evaluated herein for a specific configuration in which bistatic and conventional space time adaptive processing (STAP) is applied. Then, the bistatic angle of the configuration is varied and the effectiveness of the STAP techniques compared.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124313954","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}
引用次数: 1
Cramer-Rao type bounds for sparsity-aware multi-target tracking in multi-static passive radar 多静态无源雷达稀疏感知多目标跟踪的Cramer-Rao型边界
2016 IEEE Radar Conference (RadarConf) Pub Date : 2016-05-02 DOI: 10.1109/RADAR.2016.7485162
Saurav Subedi, Yimin D. Zhang, M. Amin, B. Himed
{"title":"Cramer-Rao type bounds for sparsity-aware multi-target tracking in multi-static passive radar","authors":"Saurav Subedi, Yimin D. Zhang, M. Amin, B. Himed","doi":"10.1109/RADAR.2016.7485162","DOIUrl":"https://doi.org/10.1109/RADAR.2016.7485162","url":null,"abstract":"Sparsity-aware multi-sensor multi-target tracking (MTT) algorithms comprise a two-step sequential architecture that cascades a group sparse reconstruction scheme and a multi-target tracker. The former exploits the a priori knowledge that the measurements across multiple sensors share a common sparse support in a discretized target state space and provides a computationally efficient approach for centralized fusion of the multi-sensor information. In the succeeding step, the multi-target tracker performs data association, compensates for the missed detections, and removes the clutter components, so as to improve the accuracy of multi-target state estimates. In many practical applications, the observation suffers from a high proportion of missing samples, rendering it difficult to accurately estimate the multi-target states using the group sparse reconstruction methods. Therefore, it is of significant interest to analyze the performance loss due to missing samples. In this paper, we analytically evaluate the Cramer-Rao type performance bounds for the sparsity-aware multi-sensor MTT algorithms in a multi-static passive radar system and evaluate the performance loss due to missing samples in the measurement vectors.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123780057","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}
引用次数: 2
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