Pub Date : 2014-08-14DOI: 10.1109/RADAR.2014.6875618
M. Hussain
Ultrawideband (UWB) waveform diversity (WD) has the potentials for improving the overall radar-system performance in terms of all-weather capability, target resolution, detection of stealthy targets, effective propagation through foliage and lossy media, suppression of interference and jamming, clutter suppression, and non-cooperative target classification and recognition. Analogous to the linear-frequency modulated (LFM) waveform, commonly known as “chirp” signal, a bipolar UWB-throb signal has been designed for the applications of highresolution impulse radar, and through-the-wall imaging radar. In this paper, we present the characteristics of the bipolar UWB-throb signal and derive its ambiguity function, which is an essential design tool for radar performance analysis. A parametric analysis of the ambiguity function is carried out to demonstrate the capabilities of the UWB-throb signal in terms of range and Doppler resolution and clutter suppression.
{"title":"Ambiguity function of bipolar ultrawideband-throb signal","authors":"M. Hussain","doi":"10.1109/RADAR.2014.6875618","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875618","url":null,"abstract":"Ultrawideband (UWB) waveform diversity (WD) has the potentials for improving the overall radar-system performance in terms of all-weather capability, target resolution, detection of stealthy targets, effective propagation through foliage and lossy media, suppression of interference and jamming, clutter suppression, and non-cooperative target classification and recognition. Analogous to the linear-frequency modulated (LFM) waveform, commonly known as “chirp” signal, a bipolar UWB-throb signal has been designed for the applications of highresolution impulse radar, and through-the-wall imaging radar. In this paper, we present the characteristics of the bipolar UWB-throb signal and derive its ambiguity function, which is an essential design tool for radar performance analysis. A parametric analysis of the ambiguity function is carried out to demonstrate the capabilities of the UWB-throb signal in terms of range and Doppler resolution and clutter suppression.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127071054","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 : 2014-08-14DOI: 10.1109/RADAR.2014.6875791
Suqi Li, Wei Yi, L. Kong, Bailu Wang
This paper deals with the problem of simultaneously detecting and tracking multiple maneuvering targets. The multitarget, multi-Bernoulli (MeMber) filter based track-before-detect (TBD) is an attractive approach to detect and track targets at low signal-to-noise (SNR). However, MeMber-TBD with a fixed motion model is not general enough to accommodate maneuvering targets. In this paper, a new MeMber filter in the TBD context is proposed to cope with unknown and time-varying number of maneuvering targets. We extend the basic MeMber-TBD with Jump Markov System (JMS) multi-target models to accommodate target birth, death and switching dynamics. The recursive prediction and update equations of the proposed JMS-MeMber-TBD are derived and implemented using the sequential Monte Carlo (SMC) approximations. Simulation results for a challenging tracking scenario prove the effectiveness of the proposed algorithm.
{"title":"Multi-Bernoulli filter based track-before-detect for Jump Markov models","authors":"Suqi Li, Wei Yi, L. Kong, Bailu Wang","doi":"10.1109/RADAR.2014.6875791","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875791","url":null,"abstract":"This paper deals with the problem of simultaneously detecting and tracking multiple maneuvering targets. The multitarget, multi-Bernoulli (MeMber) filter based track-before-detect (TBD) is an attractive approach to detect and track targets at low signal-to-noise (SNR). However, MeMber-TBD with a fixed motion model is not general enough to accommodate maneuvering targets. In this paper, a new MeMber filter in the TBD context is proposed to cope with unknown and time-varying number of maneuvering targets. We extend the basic MeMber-TBD with Jump Markov System (JMS) multi-target models to accommodate target birth, death and switching dynamics. The recursive prediction and update equations of the proposed JMS-MeMber-TBD are derived and implemented using the sequential Monte Carlo (SMC) approximations. Simulation results for a challenging tracking scenario prove the effectiveness of the proposed algorithm.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132609089","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 : 2014-08-14DOI: 10.1109/RADAR.2014.6875615
Jilan Feng, Z. Cao, Y. Pi
This paper presents an SAR image classification approach that takes advantage of both amplitude and texture features. The proposed approach is based on superpixels obtained with some over-segmentation methods, and consists of two stages. In the first stage, the SAR image is classified with amplitude and texture feature used separately. Specifically, we use statistical model based maximum-likelihood method for amplitude based classification. Meanwhile, we classify the SAR image with the support vector machine (SVM) method by taking histograms generated with sparse coded morphological profiles as feature. To combine classification results produced with amplitude and texture features, a second refine stage is proposed based on the conditional random field (CRF) method. We define the CRF based on region adjacent graph (RAG) of superpixels. The unary term of the CRF is based on fusing classification scores produced by two classifiers in the first stage. Therefore, both of amplitude and texture information are used for the final classification. The graph cut (GC) algorithm is used to optimize the CRF model. We show experimental results on real SAR data, which verify the effectiveness of the proposed approach.
{"title":"Amplitude and texture feature based SAR image classification with a two-stage approach","authors":"Jilan Feng, Z. Cao, Y. Pi","doi":"10.1109/RADAR.2014.6875615","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875615","url":null,"abstract":"This paper presents an SAR image classification approach that takes advantage of both amplitude and texture features. The proposed approach is based on superpixels obtained with some over-segmentation methods, and consists of two stages. In the first stage, the SAR image is classified with amplitude and texture feature used separately. Specifically, we use statistical model based maximum-likelihood method for amplitude based classification. Meanwhile, we classify the SAR image with the support vector machine (SVM) method by taking histograms generated with sparse coded morphological profiles as feature. To combine classification results produced with amplitude and texture features, a second refine stage is proposed based on the conditional random field (CRF) method. We define the CRF based on region adjacent graph (RAG) of superpixels. The unary term of the CRF is based on fusing classification scores produced by two classifiers in the first stage. Therefore, both of amplitude and texture information are used for the final classification. The graph cut (GC) algorithm is used to optimize the CRF model. We show experimental results on real SAR data, which verify the effectiveness of the proposed approach.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127991502","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 : 2014-08-14DOI: 10.1109/RADAR.2014.6875580
Omer Bar-Ilan, Yonina C. Elda
We investigate the problem of a monostatic pulse-Doppler radar transceiver trying to detect targets, sparsely populated in the radar's unambiguous time-frequency region. Several past works employ compressed sensing (CS) algorithms to this type of problem, but either do not address sample rate reduction, impose constraints on the radar transmitter, propose CS recovery methods with prohibitive dictionary size, or perform poorly in noisy conditions. Here we describe a sub-Nyquist sampling and recovery approach called Doppler focusing which performs low rate sampling and digital processing, imposes no restrictions on the transmitter, and uses a CS dictionary with size which does not increase with number of pulses P. Furthermore, in the presence of noise, Doppler focusing enjoys a signal-to-noise ratio (SNR) improvement which scales linearly with P, obtaining good detection performance even at SNR as low as - 25dB. It can easily incorporate clutter rejection capabilities, and handle targets with large dynamic range. The recovery is based on the Xampling framework, which allows sub-Nyquist analog-to-digital conversion. The entire digital recovery process is also performed at the low rate. Finally, our approach is implemented in hardware using a Xampling radar prototype.
{"title":"Compressed radar via Doppler focusing","authors":"Omer Bar-Ilan, Yonina C. Elda","doi":"10.1109/RADAR.2014.6875580","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875580","url":null,"abstract":"We investigate the problem of a monostatic pulse-Doppler radar transceiver trying to detect targets, sparsely populated in the radar's unambiguous time-frequency region. Several past works employ compressed sensing (CS) algorithms to this type of problem, but either do not address sample rate reduction, impose constraints on the radar transmitter, propose CS recovery methods with prohibitive dictionary size, or perform poorly in noisy conditions. Here we describe a sub-Nyquist sampling and recovery approach called Doppler focusing which performs low rate sampling and digital processing, imposes no restrictions on the transmitter, and uses a CS dictionary with size which does not increase with number of pulses P. Furthermore, in the presence of noise, Doppler focusing enjoys a signal-to-noise ratio (SNR) improvement which scales linearly with P, obtaining good detection performance even at SNR as low as - 25dB. It can easily incorporate clutter rejection capabilities, and handle targets with large dynamic range. The recovery is based on the Xampling framework, which allows sub-Nyquist analog-to-digital conversion. The entire digital recovery process is also performed at the low rate. Finally, our approach is implemented in hardware using a Xampling radar prototype.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127034745","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 : 2014-08-14DOI: 10.1109/RADAR.2014.6875563
Jiazhou Liu, Zhiqin Zhao, Jinguo Wang, Q. Liu
The performance of synthesis pattern with sparse arrays is known to degrade in the presence of errors in the array manifolds. This paper introduces a beampattern synthesis approach with uncertain manifold vectors perturbation for linear array. In order to match the desired pattern and minimize the elements simultaneously, the convex optimization of minimizing a reweighted l1-norm objective based on the weights of elements is proposed. The superposition sampling is used for select the elements. The excitation weights and sensor positions of an array radiating pencil beampatterns are obtained. This method is demonstrated through numerical simulations. The results show the maximally sparse array in beampattern synthesis with manifold vectors perturbation is obtained and the method is effective.
{"title":"A robust sparse optimization for pattern synthesis with unknown manifold error","authors":"Jiazhou Liu, Zhiqin Zhao, Jinguo Wang, Q. Liu","doi":"10.1109/RADAR.2014.6875563","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875563","url":null,"abstract":"The performance of synthesis pattern with sparse arrays is known to degrade in the presence of errors in the array manifolds. This paper introduces a beampattern synthesis approach with uncertain manifold vectors perturbation for linear array. In order to match the desired pattern and minimize the elements simultaneously, the convex optimization of minimizing a reweighted l1-norm objective based on the weights of elements is proposed. The superposition sampling is used for select the elements. The excitation weights and sensor positions of an array radiating pencil beampatterns are obtained. This method is demonstrated through numerical simulations. The results show the maximally sparse array in beampattern synthesis with manifold vectors perturbation is obtained and the method is effective.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116612624","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 : 2014-08-14DOI: 10.1109/RADAR.2014.6875567
H. Kayano, N. Shiokawa, K. Nakayama, T. Kawaguchi, T. Kumamoto, Mitsuyoshi Shinonaga
We have developed a low-profile high-sensitivity sub-array module for an active phased array antenna. By using this sub-array module, a low noise receiving antenna can be easily available for wireless applications such as radar systems, communication systems, and so on. In this paper, we describe the new 16 elements S-band multichannel receiving sub-array module using high-temperature superconducting (HTS) filters as a key component for an active phased array antenna. Each receiving channel correspond to an antenna element consists of a HTS filter, a low noise amplifier (LNA), and interface circuits. In the sub-array module, 16 channel circuits are contained within a 200 mm×240 mm×30 mm vacuum chamber and cooled by a small cooler to 77 K. By using HTS filters and the cooler, feed-line loss and internal noise can be substantially reduced. Therefore, high sensitivity for an active phased array antenna can be realized. Additionally, radio wave interferences can be suppressed effectively by sharp frequency selectivity of the HTS filter with high-Q factor.
{"title":"Low-profile high-sensitivity sub-array module with HTS filters for an active phased array antenna","authors":"H. Kayano, N. Shiokawa, K. Nakayama, T. Kawaguchi, T. Kumamoto, Mitsuyoshi Shinonaga","doi":"10.1109/RADAR.2014.6875567","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875567","url":null,"abstract":"We have developed a low-profile high-sensitivity sub-array module for an active phased array antenna. By using this sub-array module, a low noise receiving antenna can be easily available for wireless applications such as radar systems, communication systems, and so on. In this paper, we describe the new 16 elements S-band multichannel receiving sub-array module using high-temperature superconducting (HTS) filters as a key component for an active phased array antenna. Each receiving channel correspond to an antenna element consists of a HTS filter, a low noise amplifier (LNA), and interface circuits. In the sub-array module, 16 channel circuits are contained within a 200 mm×240 mm×30 mm vacuum chamber and cooled by a small cooler to 77 K. By using HTS filters and the cooler, feed-line loss and internal noise can be substantially reduced. Therefore, high sensitivity for an active phased array antenna can be realized. Additionally, radio wave interferences can be suppressed effectively by sharp frequency selectivity of the HTS filter with high-Q factor.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123971825","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 : 2014-08-14DOI: 10.1109/RADAR.2014.6875657
R. Takahashi, K. Hirata, A. Okamura
In this paper, cross-correlation processing with interference mitigating ability is proposed for passive bistatic radar. Direct signal interference from an illuminator-of-opportunity and stationary clutter are simultaneously cancelled in frequency domain during FFT (Fast Fourier Transform)-based cross-correlation processing. Due to the frequency domain processing, the proposed method can extend to subband-based interference mitigation to combat with channel mismatch between the surveillance and reference channels. Computer simulation results are included to highlight performance of the proposed method under channel mismatch condition.
{"title":"Subband cross-correlation processing with interference mitigation for passive bistatic radar","authors":"R. Takahashi, K. Hirata, A. Okamura","doi":"10.1109/RADAR.2014.6875657","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875657","url":null,"abstract":"In this paper, cross-correlation processing with interference mitigating ability is proposed for passive bistatic radar. Direct signal interference from an illuminator-of-opportunity and stationary clutter are simultaneously cancelled in frequency domain during FFT (Fast Fourier Transform)-based cross-correlation processing. Due to the frequency domain processing, the proposed method can extend to subband-based interference mitigation to combat with channel mismatch between the surveillance and reference channels. Computer simulation results are included to highlight performance of the proposed method under channel mismatch condition.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128441575","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 : 2014-08-14DOI: 10.1109/RADAR.2014.6875673
Yu Zhang, Wen Hu, Ling Wang, Lu Zhang
In this paper, we propose a chaotic-based random stepped frequency radar (CRSFR) applicable to wideband imaging. CRSFR provides faster matched processing via sequence rearrangement of AD sampling as compared with conventional random stepped frequency radar (RSFR). Our analysis shows that the presented radar system not only achieves a rapid matched filtering for range profiles without random noise floor, but also has good performance of immunity from single-frequency interference. We conducted simulations to demonstrate the performance of CRSFR and verify our analysis.
{"title":"A novel random stepped frequency radar using chaos","authors":"Yu Zhang, Wen Hu, Ling Wang, Lu Zhang","doi":"10.1109/RADAR.2014.6875673","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875673","url":null,"abstract":"In this paper, we propose a chaotic-based random stepped frequency radar (CRSFR) applicable to wideband imaging. CRSFR provides faster matched processing via sequence rearrangement of AD sampling as compared with conventional random stepped frequency radar (RSFR). Our analysis shows that the presented radar system not only achieves a rapid matched filtering for range profiles without random noise floor, but also has good performance of immunity from single-frequency interference. We conducted simulations to demonstrate the performance of CRSFR and verify our analysis.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115996966","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 : 2014-06-24DOI: 10.1109/NAECON.2014.7045783
Siyang Cao, Yuan F. Zheng, R. Ewing
Transform sensing is proposed for the phased array radar to form certain beam patterns for sensing the space more efficiently. Using the transform sensing, the received signals will be the result of transformation of individual echo signals instead of the original raw data. Therefore signal processing can perform in an online fashion to render attractive advantages. First, the volume of the raw data can be compressed before downloading since the transform will generate many null coefficients. Secondly, adaptive sensing will be possible since multi-resolution analysis enables selective sampling for better efficiency while obtaining higher resolution. The proposed new scheme is supported by an innovative phase and amplitude modulation mechanism, and is verified by theory and simulation.
{"title":"Transform sensing of phased array radar","authors":"Siyang Cao, Yuan F. Zheng, R. Ewing","doi":"10.1109/NAECON.2014.7045783","DOIUrl":"https://doi.org/10.1109/NAECON.2014.7045783","url":null,"abstract":"Transform sensing is proposed for the phased array radar to form certain beam patterns for sensing the space more efficiently. Using the transform sensing, the received signals will be the result of transformation of individual echo signals instead of the original raw data. Therefore signal processing can perform in an online fashion to render attractive advantages. First, the volume of the raw data can be compressed before downloading since the transform will generate many null coefficients. Secondly, adaptive sensing will be possible since multi-resolution analysis enables selective sampling for better efficiency while obtaining higher resolution. The proposed new scheme is supported by an innovative phase and amplitude modulation mechanism, and is verified by theory and simulation.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122389715","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 : 2014-06-03DOI: 10.1109/RADAR.2014.6875767
K. Morrison, J. Bennett
The goal of carrying out sub-surface imaging from space or aircraft has so far remained elusive. In response, a description is offered here of a novel new imaging technique. Virtual-bandwidth SAR (VB-SAR) promises to deliver a previously unachievable high-resolution sub-surface imaging capability from large stand-off distances applicable to airborne and spaceborne platforms. This is in sharp contrast to current techniques, where discrimination relies on close-proximity measurement of the scene, usually with a ground-based system using large bandwidths. The scheme for separation of surface and sub-surface features is based on their differing DInSAR phase histories. Whereas, the latter experience phase delays in sympathy to variations in soil moisture, these are absent from the phase history of surface features. Because the technique works on phase it is essentially independent of distance, and so applicable to large stand-off distances relevant to aircraft and satellite platforms.
{"title":"Virtual-bandwidth SAR (VB-SAR) for sub-surface imaging","authors":"K. Morrison, J. Bennett","doi":"10.1109/RADAR.2014.6875767","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875767","url":null,"abstract":"The goal of carrying out sub-surface imaging from space or aircraft has so far remained elusive. In response, a description is offered here of a novel new imaging technique. Virtual-bandwidth SAR (VB-SAR) promises to deliver a previously unachievable high-resolution sub-surface imaging capability from large stand-off distances applicable to airborne and spaceborne platforms. This is in sharp contrast to current techniques, where discrimination relies on close-proximity measurement of the scene, usually with a ground-based system using large bandwidths. The scheme for separation of surface and sub-surface features is based on their differing DInSAR phase histories. Whereas, the latter experience phase delays in sympathy to variations in soil moisture, these are absent from the phase history of surface features. Because the technique works on phase it is essentially independent of distance, and so applicable to large stand-off distances relevant to aircraft and satellite platforms.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130784916","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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