Pub Date : 2014-05-19DOI: 10.1109/RADAR.2014.6875729
Hui Chen, Yongjun Zhao, Chengcheng Liu, Yongchao Ding, Ting Wang
A simplified wideband beamforming structure is proposed. Based on this structure, an improved robust Capon algorithm can be used to against look direction errors by employing an estimated array steering vector (ASV). The proposed algorithm is obtained by projecting the nominal ASV onto the signal-plus-interferences subspace, and achieves a higher output signal-to-interference-plus-noise ratio (SINR) compared with the conventional robust Capon beamforming (RCB). Simulation results show the effectiveness of the proposed method.
{"title":"A novel robust Capon algorithm for wideband beamforming","authors":"Hui Chen, Yongjun Zhao, Chengcheng Liu, Yongchao Ding, Ting Wang","doi":"10.1109/RADAR.2014.6875729","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875729","url":null,"abstract":"A simplified wideband beamforming structure is proposed. Based on this structure, an improved robust Capon algorithm can be used to against look direction errors by employing an estimated array steering vector (ASV). The proposed algorithm is obtained by projecting the nominal ASV onto the signal-plus-interferences subspace, and achieves a higher output signal-to-interference-plus-noise ratio (SINR) compared with the conventional robust Capon beamforming (RCB). Simulation results show the effectiveness of the proposed method.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126990552","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875732
P. Roszkowski, M. Malanowski
In the paper bistatic noise radar is considered. The concept of such a radar is verified with a demonstrator. The demonstrator consists of physically separated transmitter and receiver, therefore a bistatic geometry is created. Reference signal used for correlation processing is generated locally in the receiver. Coarse synchronization in time and frequency between the transmitter and receiver is provided by GPS (Global Positioning System) satellite navigation. Fine time synchronization is carried out using the direct path interference signal. Apart from range and velocity measurements, bearing is also estimated using phase-interferometry technique. The demonstrator has been tested and verified during a field measurement campaign. In the paper the results of synchronization, detection, localization and tracking of a moving target are presented.
{"title":"Bistatic noise radar demonstrator with phase-interferometry for bearing determination","authors":"P. Roszkowski, M. Malanowski","doi":"10.1109/RADAR.2014.6875732","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875732","url":null,"abstract":"In the paper bistatic noise radar is considered. The concept of such a radar is verified with a demonstrator. The demonstrator consists of physically separated transmitter and receiver, therefore a bistatic geometry is created. Reference signal used for correlation processing is generated locally in the receiver. Coarse synchronization in time and frequency between the transmitter and receiver is provided by GPS (Global Positioning System) satellite navigation. Fine time synchronization is carried out using the direct path interference signal. Apart from range and velocity measurements, bearing is also estimated using phase-interferometry technique. The demonstrator has been tested and verified during a field measurement campaign. In the paper the results of synchronization, detection, localization and tracking of a moving target are presented.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127018069","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875792
Suqi Li, Bailu Wang, Wei Yi, G. Cui, L. Kong, Haiguang Yang
In this paper, we deal with the problem of simultaneously detecting and tracking multiple targets using polarimetric multiple input multiple output (MIMO) radars. The problem is formulated in a Bayesian framework by modeling the collection of states as a random finite set. First, we propose a multiple sensor Multi-Bernoulli (MS-MeMber) filter based track-before-detect (TBD) algorithm suitable for both MIMO radars and polarimetric MIMO radars. Then the sequential Monte Carlo (SMC) implementations are performed to prove the effectiveness of the proposed algorithm. Simulation results show that the polarization diversity can be exploited to enhance the detecting and tracking performance of MIMO radars.
{"title":"Multiple sensor Multi-Bernoulli filter based track-before-detect for polarimetric MIMO radars","authors":"Suqi Li, Bailu Wang, Wei Yi, G. Cui, L. Kong, Haiguang Yang","doi":"10.1109/RADAR.2014.6875792","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875792","url":null,"abstract":"In this paper, we deal with the problem of simultaneously detecting and tracking multiple targets using polarimetric multiple input multiple output (MIMO) radars. The problem is formulated in a Bayesian framework by modeling the collection of states as a random finite set. First, we propose a multiple sensor Multi-Bernoulli (MS-MeMber) filter based track-before-detect (TBD) algorithm suitable for both MIMO radars and polarimetric MIMO radars. Then the sequential Monte Carlo (SMC) implementations are performed to prove the effectiveness of the proposed algorithm. Simulation results show that the polarization diversity can be exploited to enhance the detecting and tracking performance of MIMO radars.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"48 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129177318","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875727
R. Suryaprakash, R. Nadakuditi
The Multiple Signal Classification (MUSIC) algorithm is widely used to estimate the direction of arrival (DOA) of signals impinging on a sensor array. In this work, we analyze the performance of the MUSIC algorithm in the presence of white noise, and when only a random, sample independent subset of the entries in the data matrix are observed, in both the sample rich and deficient regimes. We derive a simple, closed form expression for the mean-squared-error (MSE) performance of MUSIC for a single source system, in the asymptotic regime and validate our analysis with simulations.
{"title":"The performance of MUSIC in white noise with limited samples and missing data","authors":"R. Suryaprakash, R. Nadakuditi","doi":"10.1109/RADAR.2014.6875727","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875727","url":null,"abstract":"The Multiple Signal Classification (MUSIC) algorithm is widely used to estimate the direction of arrival (DOA) of signals impinging on a sensor array. In this work, we analyze the performance of the MUSIC algorithm in the presence of white noise, and when only a random, sample independent subset of the entries in the data matrix are observed, in both the sample rich and deficient regimes. We derive a simple, closed form expression for the mean-squared-error (MSE) performance of MUSIC for a single source system, in the asymptotic regime and validate our analysis with simulations.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123680025","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875777
M. Ikram, Murtaza Ali
We present a new method for data association in 3-D object tracking for automotive applications. The method is a variant of the nearest-neighbor data association and is based on comparing the location of an existing track with that of each incoming object and associating to the one which is closest in 3-D space. As a pair is associated, it is removed from the search space and the association process continues until all assignments are made. Our experiments show that the proposed method significantly reduces the processing cost as compared to the existing full-search nearest-neighbor method and maintains similar performance at the signal to noise ratios that are typically encountered in automotive object tracking. We will provide guidelines on selecting the operating parameters and suggestions on handling the case when the number of incoming objects is not equal to the number of existing tracks.
{"title":"A new data association method for 3-D object tracking in automotive applications","authors":"M. Ikram, Murtaza Ali","doi":"10.1109/RADAR.2014.6875777","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875777","url":null,"abstract":"We present a new method for data association in 3-D object tracking for automotive applications. The method is a variant of the nearest-neighbor data association and is based on comparing the location of an existing track with that of each incoming object and associating to the one which is closest in 3-D space. As a pair is associated, it is removed from the search space and the association process continues until all assignments are made. Our experiments show that the proposed method significantly reduces the processing cost as compared to the existing full-search nearest-neighbor method and maintains similar performance at the signal to noise ratios that are typically encountered in automotive object tracking. We will provide guidelines on selecting the operating parameters and suggestions on handling the case when the number of incoming objects is not equal to the number of existing tracks.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121567813","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875577
M. Dawood, A. V. Alejos
This paper discusses the Brillouin precursor formation pertaining to LFM and random noise waveforms propagating through the dispersive media of Triply distilled water represented by the Rocard-Powles-Debye (RPD) dielectric model and the experimental data for the wet loamy soil.
{"title":"Brillouin precursor waveforms pertaining to UWB random noise and LFM waveforms propagating through dispersive media","authors":"M. Dawood, A. V. Alejos","doi":"10.1109/RADAR.2014.6875577","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875577","url":null,"abstract":"This paper discusses the Brillouin precursor formation pertaining to LFM and random noise waveforms propagating through the dispersive media of Triply distilled water represented by the Rocard-Powles-Debye (RPD) dielectric model and the experimental data for the wet loamy soil.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"244 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114808960","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875583
D. Crouse
High-order deterministic Runge-Kutta methods are often used to predict forward continuous-time nonlinear differential equations describing physical systems. However, the stochastic nature of dynamic models in practical systems necessitates other methods for propagating forward the uncertain probability density function of a target state over time. This paper presents a variant of the cubature Kalman filter for nonlinear continuous-time dynamic models that uses a moment matching technique to predict forward the target state and covariance matrix. In this formulation, deterministic Runge-Kutta algorithms can be used for state prediction. Unlike previous work, the formulation presented is derived to handle non-additive process noise.
{"title":"Cubature Kalman filters for continuous-time dynamic models Part II: A solution based on moment matching","authors":"D. Crouse","doi":"10.1109/RADAR.2014.6875583","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875583","url":null,"abstract":"High-order deterministic Runge-Kutta methods are often used to predict forward continuous-time nonlinear differential equations describing physical systems. However, the stochastic nature of dynamic models in practical systems necessitates other methods for propagating forward the uncertain probability density function of a target state over time. This paper presents a variant of the cubature Kalman filter for nonlinear continuous-time dynamic models that uses a moment matching technique to predict forward the target state and covariance matrix. In this formulation, deterministic Runge-Kutta algorithms can be used for state prediction. Unlike previous work, the formulation presented is derived to handle non-additive process noise.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"154 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131371546","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875765
J. Guerci, R. Guerci
A new method is described that allows for the non-interfering spectrum coexistence of radar and a wireless communication system employing multiuser subscriber waveforms. To simultaneously achieve compatibility and requisite radar performance, the radar “subscribes” to the network and utilizes K independent subscriptions. In the case of a cellular network, this would correspond to K independent cell subscriptions operating simultaneously. To achieve requisite radar performance, the onboard radar controller performs an adaptive linear combiner optimization of the K simultaneous waveforms to obtain a transmitted composite waveform with far superior useful radar properties (greater power, Doppler tolerance, etc.) than would be achieved by simply using the indigenous unaltered communications network waveforms. The linearity of the superposition ensures that the composite radar waveform behaves as K ordinary users, and thus does not require any special handling by the communications network nor will result in any undue interference. While utilizing communication waveforms for radar is not new, using a plurality of simultaneous waveforms to form a new composite waveform with better radar properties yet preserving network compatibility is entirely new.
{"title":"RAST: Radar as a subscriber technology for wireless spectrum cohabitation","authors":"J. Guerci, R. Guerci","doi":"10.1109/RADAR.2014.6875765","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875765","url":null,"abstract":"A new method is described that allows for the non-interfering spectrum coexistence of radar and a wireless communication system employing multiuser subscriber waveforms. To simultaneously achieve compatibility and requisite radar performance, the radar “subscribes” to the network and utilizes K independent subscriptions. In the case of a cellular network, this would correspond to K independent cell subscriptions operating simultaneously. To achieve requisite radar performance, the onboard radar controller performs an adaptive linear combiner optimization of the K simultaneous waveforms to obtain a transmitted composite waveform with far superior useful radar properties (greater power, Doppler tolerance, etc.) than would be achieved by simply using the indigenous unaltered communications network waveforms. The linearity of the superposition ensures that the composite radar waveform behaves as K ordinary users, and thus does not require any special handling by the communications network nor will result in any undue interference. While utilizing communication waveforms for radar is not new, using a plurality of simultaneous waveforms to form a new composite waveform with better radar properties yet preserving network compatibility is entirely new.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132043026","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875718
A. Massa, P. Rocca, E. Giaccari, A. Farina
The analysis of the effects on the radiation pattern of the manufacturing tolerances of the control points (i.e., amplitude and phase weights) of antenna arrays is addressed. A strategy based on Interval Analysis (IA) is exploited to analytically compute upper and lower bounds of the power pattern as a function of the maximum deviations of the control point values from the nominal/reference ones. A set of representative results is reported to show the behavior of the IA-based tool as well as to assess its effectiveness.
{"title":"Tolerance analysis of antenna arrays through Interval Analysis","authors":"A. Massa, P. Rocca, E. Giaccari, A. Farina","doi":"10.1109/RADAR.2014.6875718","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875718","url":null,"abstract":"The analysis of the effects on the radiation pattern of the manufacturing tolerances of the control points (i.e., amplitude and phase weights) of antenna arrays is addressed. A strategy based on Interval Analysis (IA) is exploited to analytically compute upper and lower bounds of the power pattern as a function of the maximum deviations of the control point values from the nominal/reference ones. A set of representative results is reported to show the behavior of the IA-based tool as well as to assess its effectiveness.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132084417","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875753
S. Wacks, B. Yazıcı
This paper presents a theory for moving target imaging using two channel Doppler synthetic aperture radar (SAR). Doppler-SAR is a novel SAR modality that transmits ultra-narrowband waveforms. It reconstructs high resolution images by backprojecting data onto the high resolution iso-Doppler contours provided by ultra-narrowband waveforms. We present a novel method to detect/image moving targets by combining the displaced phase center antenna technique with Doppler-SAR. The displaced phase center antenna technique has the distinct advantages of removing the response from stationary targets (clutter) by subtracting images formed by each channel. We present numerical results to demonstrate our theory. This novel method can be used for passive imaging of moving targets embedded in clutter using sources of opportunity transmitting ultra-narrowband waveforms, such as TV and radio stations.
{"title":"Bistatic Doppler-SAR DPCA imaging of ground moving targets","authors":"S. Wacks, B. Yazıcı","doi":"10.1109/RADAR.2014.6875753","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875753","url":null,"abstract":"This paper presents a theory for moving target imaging using two channel Doppler synthetic aperture radar (SAR). Doppler-SAR is a novel SAR modality that transmits ultra-narrowband waveforms. It reconstructs high resolution images by backprojecting data onto the high resolution iso-Doppler contours provided by ultra-narrowband waveforms. We present a novel method to detect/image moving targets by combining the displaced phase center antenna technique with Doppler-SAR. The displaced phase center antenna technique has the distinct advantages of removing the response from stationary targets (clutter) by subtracting images formed by each channel. We present numerical results to demonstrate our theory. This novel method can be used for passive imaging of moving targets embedded in clutter using sources of opportunity transmitting ultra-narrowband waveforms, such as TV and radio stations.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132114620","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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