Pub Date : 2014-05-19DOI: 10.1109/RADAR.2014.6875636
Yu Zhang, A. Venkatachalam, T. Xia, Yuanchang Xie, Guoan Wang
Fouled ballast is a typical problem faced by many freight and passenger rail agencies. Due to the underground nature of this problem, we have developed a high-speed air coupled ultra wideband (UWB) ground penetrating radar (GPR) that is applicable for ballast inspection. Implemented with the GPR hardware, new GPR signal processing algorithms including Bicubic interpolation, gain compensation, and reflection signal envelope extraction in conjunction with background removal are developed to remove noise and interference while preserve and enhance the subsurface features under inspection. The entire system is tested extensively on a customer-built structure emulating a segment of railroad track. The results show that the system can effectively detect subsurface objects and characterize ballast fouling conditions.
{"title":"Data analysis technique to leverage ground penetrating radar ballast inspection performance","authors":"Yu Zhang, A. Venkatachalam, T. Xia, Yuanchang Xie, Guoan Wang","doi":"10.1109/RADAR.2014.6875636","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875636","url":null,"abstract":"Fouled ballast is a typical problem faced by many freight and passenger rail agencies. Due to the underground nature of this problem, we have developed a high-speed air coupled ultra wideband (UWB) ground penetrating radar (GPR) that is applicable for ballast inspection. Implemented with the GPR hardware, new GPR signal processing algorithms including Bicubic interpolation, gain compensation, and reflection signal envelope extraction in conjunction with background removal are developed to remove noise and interference while preserve and enhance the subsurface features under inspection. The entire system is tested extensively on a customer-built structure emulating a segment of railroad track. The results show that the system can effectively detect subsurface objects and characterize ballast fouling conditions.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132493336","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.2014.6875797
M. Greenspan
Cognitive radar architectures offer the community many potential benefits including the potential of improving sensor system performance while simultaneously reducing the cost of future radar systems. However, as with many new technologies, it is important that, in addition to understanding its benefits, the developers of such advanced cognitive radar systems also be fully aware of its potential risks. The objective of this paper is to identify and highlight some of these potential risks so that they can be addressed and resolved as early as possible in the development cycle.
{"title":"Potential pitfalls of cognitive radars","authors":"M. Greenspan","doi":"10.1109/RADAR.2014.6875797","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875797","url":null,"abstract":"Cognitive radar architectures offer the community many potential benefits including the potential of improving sensor system performance while simultaneously reducing the cost of future radar systems. However, as with many new technologies, it is important that, in addition to understanding its benefits, the developers of such advanced cognitive radar systems also be fully aware of its potential risks. The objective of this paper is to identify and highlight some of these potential risks so that they can be addressed and resolved as early as possible in the development cycle.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130038395","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.2014.6875617
Victor Iglesias, J. Grajal, Omar A. Yeste Ojeda, M. Garrido, M. A. Sánchez, M. López-Vallejo
The estimation of pulsed radar signal parameters is a key task of an electronic intelligence (ELINT) equipment. All these signal parameters are compiled in a pulse description word (PDW). The post-processing of various PDWs from different receivers can provide valuable information about emitters. This paper presents a real-time FPGA implementation of a radar pulse parameter extractor (PPE) which provides the PDW of four simultaneous pulsed radar signals. Experimental results are presented in order to validate the FPGA implementation.
{"title":"Real-time radar pulse parameter extractor","authors":"Victor Iglesias, J. Grajal, Omar A. Yeste Ojeda, M. Garrido, M. A. Sánchez, M. López-Vallejo","doi":"10.1109/RADAR.2014.6875617","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875617","url":null,"abstract":"The estimation of pulsed radar signal parameters is a key task of an electronic intelligence (ELINT) equipment. All these signal parameters are compiled in a pulse description word (PDW). The post-processing of various PDWs from different receivers can provide valuable information about emitters. This paper presents a real-time FPGA implementation of a radar pulse parameter extractor (PPE) which provides the PDW of four simultaneous pulsed radar signals. Experimental results are presented in order to validate the FPGA implementation.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134594477","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.2014.6875723
Yimin D. Zhang, B. Himed
In this paper, we develop a new space-time adaptive processing (STAP) technique for bistatic passive radar by exploiting clutter sparsity so as to enable effective clutter suppression with a small set of data samples. The Bayesian compressive sensing (BCS) technique is utilized for sparse clutter reconstruction, and the persymmetry property of the STAP processor is used to cast the complex sparse signal recovery problem into a group sparsity formulation. This approach provides improved recovery of the clutter and, thereby, yields better STAP performance.
{"title":"Space-time adaptive processing in bistatic passive radar exploiting complex Bayesian learning","authors":"Yimin D. Zhang, B. Himed","doi":"10.1109/RADAR.2014.6875723","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875723","url":null,"abstract":"In this paper, we develop a new space-time adaptive processing (STAP) technique for bistatic passive radar by exploiting clutter sparsity so as to enable effective clutter suppression with a small set of data samples. The Bayesian compressive sensing (BCS) technique is utilized for sparse clutter reconstruction, and the persymmetry property of the STAP processor is used to cast the complex sparse signal recovery problem into a group sparsity formulation. This approach provides improved recovery of the clutter and, thereby, yields better STAP performance.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130793095","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.2014.6875731
Bulent Sen, Mehmet Kayhan
This paper presents an experimental investigation on transmit pulse to pulse stability and receiver protection capability of a 1.4 kw s band transmit receive module (t/r module). Most modern radar transmitters require very stable inter and intra-pulse amplitude and phase performance. This is indeed a very challenging task due to maintaining electrical and thermal requirements in a very limited space. A compact high power t/r module is produced with a dedicated in-house waveform stability and surviving peak power test and measurement system. Lower than -60db of inter-pulse amplitude and phase stability figure is achieved at the transmitter. A peak power survivability test is also conducted at the receiver with 1.5kw and 500w peak power at duty cycles of %3 and %10, respectively. The module is exposed to operational burn in test in the lab for 12 hours and operational endurance test on the radar for 100 hours to validate its reliability.
{"title":"Pulse To pulse stability and receiver protection considerations of S band transmit receive module","authors":"Bulent Sen, Mehmet Kayhan","doi":"10.1109/RADAR.2014.6875731","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875731","url":null,"abstract":"This paper presents an experimental investigation on transmit pulse to pulse stability and receiver protection capability of a 1.4 kw s band transmit receive module (t/r module). Most modern radar transmitters require very stable inter and intra-pulse amplitude and phase performance. This is indeed a very challenging task due to maintaining electrical and thermal requirements in a very limited space. A compact high power t/r module is produced with a dedicated in-house waveform stability and surviving peak power test and measurement system. Lower than -60db of inter-pulse amplitude and phase stability figure is achieved at the transmitter. A peak power survivability test is also conducted at the receiver with 1.5kw and 500w peak power at duty cycles of %3 and %10, respectively. The module is exposed to operational burn in test in the lab for 12 hours and operational endurance test on the radar for 100 hours to validate its reliability.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130795669","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.2014.6875825
Tarek S. Abdelrahman, Emre Ertin
We study the problem of tracking low radar cross section (RCS) objects using a range doppler sensor. Previously proposed track-before-detect (TBD) algorithms for this problem do not scale to large scenes, as their computational complexity grows rapidly with increasing grid size. In this paper we present a novel tracking algorithm that controls the complexity of the tracking algorithm using an adaptive multi-resolution grid to represent state of the objects in the scene, with finer cells at regions with higher probability of presence of active targets. We present extensive simulation results to illustrate the superior scaling performance of our technique.
{"title":"Multi-resolution track-before-detect tracking using dyadic trees","authors":"Tarek S. Abdelrahman, Emre Ertin","doi":"10.1109/RADAR.2014.6875825","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875825","url":null,"abstract":"We study the problem of tracking low radar cross section (RCS) objects using a range doppler sensor. Previously proposed track-before-detect (TBD) algorithms for this problem do not scale to large scenes, as their computational complexity grows rapidly with increasing grid size. In this paper we present a novel tracking algorithm that controls the complexity of the tracking algorithm using an adaptive multi-resolution grid to represent state of the objects in the scene, with finer cells at regions with higher probability of presence of active targets. We present extensive simulation results to illustrate the superior scaling performance of our technique.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130946237","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.2014.6875712
B. Erol, C. Karabacak, S. Gurbuz, A. Gurbuz
The availability and access to real radar data collected for targets with a desired characteristic is often limited by monetary and practical resources, especially in the case of airborne radar. In such cases, the generation of accurate simulated radar data is critical to the successful design and testing of radar signal processing algorithms. In the case of human micro-Doppler research, simulations of the expected target signature are required for a wide parameter space, including height, weight, gender, range, angle and waveform. The applicability of kinematic models is limited to just walking, while the use of motion capture databases is restricted to the test subjects and scenarios recorded by a third-party. To enable the simulation of human micro-Doppler signatures at will, this work exploits the inexpensive Kinect sensor to generate human spectrograms of any motion and for any subject from skeleton tracking data. The simulated spectrograms generated are statistically compared with those generated from high quality motion capture data. It is shown that the Kinect spectrograms are of sufficient quality to be used in simulation and classification of human micro-Doppler.
{"title":"Simulation of human micro-Doppler signatures with Kinect sensor","authors":"B. Erol, C. Karabacak, S. Gurbuz, A. Gurbuz","doi":"10.1109/RADAR.2014.6875712","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875712","url":null,"abstract":"The availability and access to real radar data collected for targets with a desired characteristic is often limited by monetary and practical resources, especially in the case of airborne radar. In such cases, the generation of accurate simulated radar data is critical to the successful design and testing of radar signal processing algorithms. In the case of human micro-Doppler research, simulations of the expected target signature are required for a wide parameter space, including height, weight, gender, range, angle and waveform. The applicability of kinematic models is limited to just walking, while the use of motion capture databases is restricted to the test subjects and scenarios recorded by a third-party. To enable the simulation of human micro-Doppler signatures at will, this work exploits the inexpensive Kinect sensor to generate human spectrograms of any motion and for any subject from skeleton tracking data. The simulated spectrograms generated are statistically compared with those generated from high quality motion capture data. It is shown that the Kinect spectrograms are of sufficient quality to be used in simulation and classification of human micro-Doppler.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133045789","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.2014.6875764
A. Charlish, F. Govaers, W. Koch
The distributed Kalman filter requires the measurement covariances of remote radar nodes to be known at all radar nodes. This is not possible for a radar network, as the true measurement covariances depend on the radar-target geometry and the fluctuating signal-to-noise ratio. This paper tackles this problem using the double debiased distributed Kalman filter (D3KF) which utilizes a radar model to form a hypothesis on the global covariance. The scheme also transmits debiasing matrices, that account for the mismatch between the assumed and encountered measurement covariance. The scheme is evaluated in a radar network scenario, where it is demonstrated to achieve close to the optimal performance of a centralized Kalman filter (CKF). In contrast to a CKF, the D3KF does not transmit the complete measurement data and is not dependent on the transmission rate of the communication channels to the fusion center.
{"title":"Distributed radar tracking using the double debiased distributed Kalman filter","authors":"A. Charlish, F. Govaers, W. Koch","doi":"10.1109/RADAR.2014.6875764","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875764","url":null,"abstract":"The distributed Kalman filter requires the measurement covariances of remote radar nodes to be known at all radar nodes. This is not possible for a radar network, as the true measurement covariances depend on the radar-target geometry and the fluctuating signal-to-noise ratio. This paper tackles this problem using the double debiased distributed Kalman filter (D3KF) which utilizes a radar model to form a hypothesis on the global covariance. The scheme also transmits debiasing matrices, that account for the mismatch between the assumed and encountered measurement covariance. The scheme is evaluated in a radar network scenario, where it is demonstrated to achieve close to the optimal performance of a centralized Kalman filter (CKF). In contrast to a CKF, the D3KF does not transmit the complete measurement data and is not dependent on the transmission rate of the communication channels to the fusion center.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133531071","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.2014.6875532
M. Lesturgie
MIMO (multiple-input multiple-output) radar refers to the use of multiple transmitters and receivers, for sensing the environment and the targets present in this environment. Basically MIMO radar uses multiple antennas that transmit correlated or uncorrelated waveforms. For the last ten years MIMO has led to extensive research and publications, both in communications and Radar domains. Why such interest for MIMO in radar? Beside the prolific amount of publications, how to assess the interest of MIMO to overcome the current limitations of conventional radar? The tutorial attempts to answer these questions, as well as to provide the tools to understand the link between theoretical considerations and radar system design. After a summary of the state of art - we may notice that MIMO was invented more than 25 years ago - the course will provide the fundamentals of MIMO radar, how to define a MIMO radar configuration, introduce the signal model, waveform design, signal processing, detection, and localization. A particular emphasis will be put on the coherent MIMO in conjunction with the unique properties of the MIMO steering vector. A large part of the course will be focused on applications, including MIMO-STAP for GMTI, low frequency radar for coastal maritime surveillance.
{"title":"T06 — MIMO radar","authors":"M. Lesturgie","doi":"10.1109/RADAR.2014.6875532","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875532","url":null,"abstract":"MIMO (multiple-input multiple-output) radar refers to the use of multiple transmitters and receivers, for sensing the environment and the targets present in this environment. Basically MIMO radar uses multiple antennas that transmit correlated or uncorrelated waveforms. For the last ten years MIMO has led to extensive research and publications, both in communications and Radar domains. Why such interest for MIMO in radar? Beside the prolific amount of publications, how to assess the interest of MIMO to overcome the current limitations of conventional radar? The tutorial attempts to answer these questions, as well as to provide the tools to understand the link between theoretical considerations and radar system design. After a summary of the state of art - we may notice that MIMO was invented more than 25 years ago - the course will provide the fundamentals of MIMO radar, how to define a MIMO radar configuration, introduce the signal model, waveform design, signal processing, detection, and localization. A particular emphasis will be put on the coherent MIMO in conjunction with the unique properties of the MIMO steering vector. A large part of the course will be focused on applications, including MIMO-STAP for GMTI, low frequency radar for coastal maritime surveillance.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133229089","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.2014.6875725
G. Harding, R. Penno
With the goal of developing a dynamic, time-domain, simulation tool, different techniques for predicting the complex scattered electromagnetic fields are examined. Emphasis is placed upon evaluating the ability of certain RCS prediction methods to produce a high fidelity model of the static phase relationships of scattering mechanisms of a complex scattering body. Future exploration will focus on the phase effects of dynamic movement of these mechanisms within a radar measurement.
{"title":"Simulation of the electromagnetic scattering from complex scattering targets","authors":"G. Harding, R. Penno","doi":"10.1109/RADAR.2014.6875725","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875725","url":null,"abstract":"With the goal of developing a dynamic, time-domain, simulation tool, different techniques for predicting the complex scattered electromagnetic fields are examined. Emphasis is placed upon evaluating the ability of certain RCS prediction methods to produce a high fidelity model of the static phase relationships of scattering mechanisms of a complex scattering body. Future exploration will focus on the phase effects of dynamic movement of these mechanisms within a radar measurement.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117327473","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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