The Experts below are selected from a list of 31677 Experts worldwide ranked by ideXlab platform
Atr Lab - One of the best experts on this subject based on the ideXlab platform.
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Reserch of 3D Radar Target Imaging Based on ICA
Signal Processing, 2005Co-Authors: Atr LabAbstract:A method based on ICA for imaging 3-D structure of Radar Target is suggest, by using the position information of scattering centre of a Radar Target range frofile in different directions. Computer simulations with simple Radar Target profile show that the method is useful for Radar Target recognition.
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The Research On Automatic Data Acquisition Of Radar Target
Signal Processing, 2002Co-Authors: Atr LabAbstract:In this paper, a kind of automatic Radar Target data acquisition system used in the automatic Radar Target recognition system is mentioned, the hardware of the system is introduced including a data acquisition unite and a Target detected, tracked unite. Controlled by the system software, according to the Target space position offered by the detected, tracked unite, the data acquisition unite may pick the data of a Target which is need to be sampled through the fenestration in space. The data acquisition system may sample multiple Target data automatically, then we may built the Target characteristic data-base and do some analysis and recognition work.
Hyo-tae Kim - One of the best experts on this subject based on the ideXlab platform.
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Radar Target discrimination using neural networks
Proceedings of the IEEE 2010 National Aerospace & Electronics Conference, 2010Co-Authors: Joon-ho Lee, Hyo-tae KimAbstract:Time domain response based neural network and frequency domain response based neural network have been proposed for Radar Target recognition. In this paper, we propose a natural frequency based neural network for Radar Target recognition. Our scheme makes advantage of an aspect angle independence of a natural frequency. In the results, we show that, for the multiple aspect angles, natural frequency based neural network is superior to time domain response based neural network.
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Radar Target recognition based on late time representation closed form expression for criterion
IEEE Transactions on Antennas and Propagation, 2006Co-Authors: Joon-ho Lee, Hyo-tae KimAbstract:In the previous paper, we have defined the normalized estimation error and presented the Radar Target recognition scheme in frequency domain. A time-domain version of the previous paper is considered and a closed-form expression for the defined normalized estimation error in terms of Z-plane natural frequencies and transient response is derived. Evaluation of the closed-form expression of the normalized estimation error is shown in the numerical results, where it is shown that the performance of the Radar Target recognition scheme improves with an increase of the number of the natural frequencies and with an increase of signal-to-noise ratio. Furthermore, the mean and the variance of the square of the numerator of the normalized estimation error are obtained, and the validity of the statistics is shown using the numerical results
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Radar Target recognition using least squares estimate
Microwave and Optical Technology Letters, 2001Co-Authors: Joon-ho Lee, Hyo-tae KimAbstract:A new scheme for Radar Target discrimination which is independent of an aspect angle is proposed in the frequency domain. A system of linear equations is constructed using the frequency response of an unknown Target and stored natural frequencies of a particular Target. Whether an unknown Target is a particular Target or not is determined using the defined least squares estimate or the normalized estimation error. The validity of the method is shown using the method-of-moments (MM) frequency response. © 2001 John Wiley & Sons, Inc. Microwave Opt Technol Lett 30: 427–434, 2001.
Andrey Baev - One of the best experts on this subject based on the ideXlab platform.
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Ultra wideband Radar Target discrimination using the signatures algorithm
33rd European Microwave Conference 2003, 2003Co-Authors: Andrey Baev, Y. Kuznetsova, A. AleksandrovAbstract:An aspect independent Radar Target discrimination method based on the natural frequencies of ultra wideband Radar Targets is introduced. The sets of points in multi-dimension space corresponding to the poles on a complex plane (natural resonances) were offered as signatures of Radar Targets. This approach allows performing an automated discrimination algorithm of Radar Targets. The results of experimental research of the signals scattered by the scaled aircraft models by using the signatures algorithm are presented.
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Technique of ultra wideband Radar Target discrimination using natural frequencies
15th International Conference on Microwaves Radar and Wireless Communications (IEEE Cat. No.04EX824), 1Co-Authors: Andrey Baev, Y. KuznetsovAbstract:An aspect independent Radar Target discrimination method based on the natural frequencies of ultra wideband Radar Targets is introduced. The sets of points in a multi-dimensional space corresponding to the poles on a complex plane (natural resonances) were offered as signatures of Radar Targets. This approach allows performing the automated discrimination algorithm of Radar Targets. The results of experimental research of the signals scattered by scaled aircraft models using the signatures algorithm and cumulant preprocessing are presented.
Joon-ho Lee - One of the best experts on this subject based on the ideXlab platform.
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Radar Target discrimination using neural networks
Proceedings of the IEEE 2010 National Aerospace & Electronics Conference, 2010Co-Authors: Joon-ho Lee, Hyo-tae KimAbstract:Time domain response based neural network and frequency domain response based neural network have been proposed for Radar Target recognition. In this paper, we propose a natural frequency based neural network for Radar Target recognition. Our scheme makes advantage of an aspect angle independence of a natural frequency. In the results, we show that, for the multiple aspect angles, natural frequency based neural network is superior to time domain response based neural network.
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Radar Target recognition based on late time representation closed form expression for criterion
IEEE Transactions on Antennas and Propagation, 2006Co-Authors: Joon-ho Lee, Hyo-tae KimAbstract:In the previous paper, we have defined the normalized estimation error and presented the Radar Target recognition scheme in frequency domain. A time-domain version of the previous paper is considered and a closed-form expression for the defined normalized estimation error in terms of Z-plane natural frequencies and transient response is derived. Evaluation of the closed-form expression of the normalized estimation error is shown in the numerical results, where it is shown that the performance of the Radar Target recognition scheme improves with an increase of the number of the natural frequencies and with an increase of signal-to-noise ratio. Furthermore, the mean and the variance of the square of the numerator of the normalized estimation error are obtained, and the validity of the statistics is shown using the numerical results
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Radar Target recognition using least squares estimate
Microwave and Optical Technology Letters, 2001Co-Authors: Joon-ho Lee, Hyo-tae KimAbstract:A new scheme for Radar Target discrimination which is independent of an aspect angle is proposed in the frequency domain. A system of linear equations is constructed using the frequency response of an unknown Target and stored natural frequencies of a particular Target. Whether an unknown Target is a particular Target or not is determined using the defined least squares estimate or the normalized estimation error. The validity of the method is shown using the method-of-moments (MM) frequency response. © 2001 John Wiley & Sons, Inc. Microwave Opt Technol Lett 30: 427–434, 2001.
A. Aleksandrov - One of the best experts on this subject based on the ideXlab platform.
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Ultra wideband Radar Target discrimination using the signatures algorithm
33rd European Microwave Conference 2003, 2003Co-Authors: Andrey Baev, Y. Kuznetsova, A. AleksandrovAbstract:An aspect independent Radar Target discrimination method based on the natural frequencies of ultra wideband Radar Targets is introduced. The sets of points in multi-dimension space corresponding to the poles on a complex plane (natural resonances) were offered as signatures of Radar Targets. This approach allows performing an automated discrimination algorithm of Radar Targets. The results of experimental research of the signals scattered by the scaled aircraft models by using the signatures algorithm are presented.