The Experts below are selected from a list of 47988 Experts worldwide ranked by ideXlab platform
Leon H Sibul - One of the best experts on this subject based on the ideXlab platform.
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cascaded scattering Functions for sonar signal processing
European Signal Processing Conference, 1998Co-Authors: Lora G Weiss, Leon H SibulAbstract:This paper derives the total scattering Function of a channel as a cascaded convolution of propagation and other scattering Functions in a general structure with the narrowband (time-frequency) and wideband (time-scale) details presented as special cases. To do this requires the assumption that the probing signal is sufficiently rich so that the total Spreading Function can be represented by an inverse transform of the received signal. The derivation of this cascade of scattering Functions then exploits properties of reproducing kernel Hilbert spaces (RKHS). Since scattering Functions behave similarly to ambiguity Functions (there is an increase in ambiguity as the signal propagates through the medium), a convolution of scattering Functions can be viewed as propagation of ambiguities through a time-varying multipath medium. The incorporation of cascaded scattering Functions into a detection processor then yields an improved technique for detecting signals in more complex time-varying environments.
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EUSIPCO - Cascaded scattering Functions for sonar signal processing
1998Co-Authors: Lora G Weiss, Leon H SibulAbstract:This paper derives the total scattering Function of a channel as a cascaded convolution of propagation and other scattering Functions in a general structure with the narrowband (time-frequency) and wideband (time-scale) details presented as special cases. To do this requires the assumption that the probing signal is sufficiently rich so that the total Spreading Function can be represented by an inverse transform of the received signal. The derivation of this cascade of scattering Functions then exploits properties of reproducing kernel Hilbert spaces (RKHS). Since scattering Functions behave similarly to ambiguity Functions (there is an increase in ambiguity as the signal propagates through the medium), a convolution of scattering Functions can be viewed as propagation of ambiguities through a time-varying multipath medium. The incorporation of cascaded scattering Functions into a detection processor then yields an improved technique for detecting signals in more complex time-varying environments.
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a parameterized hough transform approach for estimating the support of the wideband Spreading Function of a distributed object
Multidimensional Systems and Signal Processing, 1996Co-Authors: Teresa L Dixon, Leon H SibulAbstract:A multidimensional Hough transform is used in conjunction with continuous wavelet transforms to aid in solving a parameterized inverse problem. The inverse problem under consideration is the characterization of distributed scatterers by means of active wideband remote sensing. Wavelet transforms are used to obtain estimates of distributed scatterers in the delay/scale plane. From a noisy wavelet transform estimate, the Hough transform is used to estimate a support region which is directly related to the physical parameters describing the distributed object.
Antonia Papandreou-suppappola - One of the best experts on this subject based on the ideXlab platform.
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Time Scale and Dispersive Processing for Wideband Time-Varying Channels
2011Co-Authors: Antonia Papandreou-suppappola, Cornel Ioana, Jun Jason ZhangAbstract:This chapter presents wideband time-varying channel models and their application towards improving wireless communication performance. It investigates two types of wideband channels: the wideband delay-scale channel that causes multipath and Doppler scaling on the transmitted signal and the wideband dispersive channel that causes nonlinear dispersive changes on the transmitted signal. For the wideband delay-scale channel, the conditions under which Doppler changes in the signal cannot be approximated as Doppler shifts are provided. The corresponding channel representation is based on the wideband Spreading Function. It is demonstrated that the Doppler scale parameter of this representation can be sampled geometrically using the Mellin transform, and for each discrete scale, the multipath parameter can be uniformly sampled. It is furthermore demonstrated that the delay-scale framework can be used to improve wideband channel communication performance due to its inherent multipath-scale diversity, which is captured by the discrete time-scale model. This is achieved by using a wavelet signaling scheme to dyadically decompose the channel into independent subchannels. The adoption of wavelet signaling also facilitates the efficient implementation of a wideband time-scale rake receiver using wavelet transform techniques. The wideband dispersive channel generalizes the narrowband channel characterization. This generalization framework provides an important foundation to exploit dispersive characteristics and improve system performance.
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ICASSP (4) - Time-scale canonical model for wideband system characterization
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics Speech and Signal Processing 2005., 2005Co-Authors: Ying Jiang, Antonia Papandreou-suppappolaAbstract:In this paper, we propose a time-scale canonical model as a discrete characterization of wideband linear time-varying systems. This representation decomposes a system output into discrete time shifts and Doppler scalings on the input, weighted by a smoothed discrete version of the wideband Spreading Function. We base this formulation on the Mellin transform that is matched to scalings. We also demonstrate that our proposed model inherently affords a joint multipath-scale diversity in wideband communication channels. By properly designing the signaling and reception schemes using wavelet techniques, we can achieve this diversity over a dyadic time-scale framework.
Lora G Weiss - One of the best experts on this subject based on the ideXlab platform.
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Wavelet processing for wideband Spreading Function estimation
The Journal of the Acoustical Society of America, 1999Co-Authors: Lora G WeissAbstract:The statistic used to quantify the amount of environmental Spreading a signal undergoes as it traverses through a channel is called a Spreading Function, and it includes the effects of moving, distributed scattering objects, multipath, boundary effects, etc., on the signal. Traditionally, narrow‐band signals have been transmitted, and the Spreading Functions were estimated by calculating the outputs of narrow‐band‐matched filters. Now that wideband processing has become more accessible, we need a solid concept of estimating wideband Spreading Functions. This paper shows that a wideband Spreading Function can be estimated by computing the wavelet transform of the received signal while using the transmitted signal as the mother wavelet. The paper then computes the second‐order statistic, called the wideband scattering Function, associated with the wideband Spreading Function. To assess the total scattering, several scattering Functions are convolved to yield an overall representation of the environment. This representation can then be incorporated into a detection processor. The payoff is that if any portion of the scattering environment is known a priori, this information can be exploited in the detector. As knowledge of the scattering process is acquired, it is combined via the cascaded scattering Function formulation.
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cascaded scattering Functions for sonar signal processing
European Signal Processing Conference, 1998Co-Authors: Lora G Weiss, Leon H SibulAbstract:This paper derives the total scattering Function of a channel as a cascaded convolution of propagation and other scattering Functions in a general structure with the narrowband (time-frequency) and wideband (time-scale) details presented as special cases. To do this requires the assumption that the probing signal is sufficiently rich so that the total Spreading Function can be represented by an inverse transform of the received signal. The derivation of this cascade of scattering Functions then exploits properties of reproducing kernel Hilbert spaces (RKHS). Since scattering Functions behave similarly to ambiguity Functions (there is an increase in ambiguity as the signal propagates through the medium), a convolution of scattering Functions can be viewed as propagation of ambiguities through a time-varying multipath medium. The incorporation of cascaded scattering Functions into a detection processor then yields an improved technique for detecting signals in more complex time-varying environments.
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EUSIPCO - Cascaded scattering Functions for sonar signal processing
1998Co-Authors: Lora G Weiss, Leon H SibulAbstract:This paper derives the total scattering Function of a channel as a cascaded convolution of propagation and other scattering Functions in a general structure with the narrowband (time-frequency) and wideband (time-scale) details presented as special cases. To do this requires the assumption that the probing signal is sufficiently rich so that the total Spreading Function can be represented by an inverse transform of the received signal. The derivation of this cascade of scattering Functions then exploits properties of reproducing kernel Hilbert spaces (RKHS). Since scattering Functions behave similarly to ambiguity Functions (there is an increase in ambiguity as the signal propagates through the medium), a convolution of scattering Functions can be viewed as propagation of ambiguities through a time-varying multipath medium. The incorporation of cascaded scattering Functions into a detection processor then yields an improved technique for detecting signals in more complex time-varying environments.
Biyang Wen - One of the best experts on this subject based on the ideXlab platform.
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wind direction mapping with a modified wind Spreading Function by broad beam high frequency radar
IEEE Geoscience and Remote Sensing Letters, 2018Co-Authors: Yuming Zeng, Hao Zhou, Yeping Lai, Biyang WenAbstract:Wind Spreading Functions (WSF) are crucial for high-frequency radar (HFR) wind-direction inversion. The popular half-angle cosine WSF always fails to describe observed HFR Doppler spectra and tends to provide almost fixed relative angle estimations. In this letter, analysis of the data from a broad-beam HFR radar, deployed on the Taiwan Strait’s west coast, shows that a modified WSF (based on the cosine WSF) has a better wind-direction estimation performance. The modified WSF fits average Bragg ratios of 15-day data well with the aid of data from buoys. The data of the next 13 days are used to test the modified WSF. The wind direction estimated by the modified WSF has an advantage when Bragg ratios have adequate average processing, and directions of arrival are around the upwind or downwind direction. The root mean square error of the modified WSF wind-direction estimate is 32.59° for the entire observation, decreasing to 14.18° when a significant wave height is between 1 and 2 m.
Volker Pohl - One of the best experts on this subject based on the ideXlab platform.
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permissible support patterns for identifying the Spreading Function of time varying channels
International Conference on Acoustics Speech and Signal Processing, 2018Co-Authors: Dae Gwan Lee, Alihan Kaplan, Volker PohlAbstract:We study support patterns for covariance matrices that appear in the problem of stochastic time-varying channel identification. The problem reduces to solving a linear system that is associated with a matrix in the form of a Kronecker product of a Gabor system matrix with itself, and therefore solvability of the linear system depends on the choice of generating window for the Gabor system and the support pattern of the object vector. In this paper, we investigate support patterns that allows the linear system to be solvable with some window. We present several classes of permissible patterns and also provide how the corresponding windows need to be chosen.