Relevant bibliographies by topics / Decorrelating

Academic literature on the topic 'Decorrelating'

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Published: 4 June 2021
Last updated: 28 January 2023

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Journal articles on the topic "Decorrelating"

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Lombardini, Fabrizio, and Francesco Cai. "Generalized-Capon Method for Diff-Tomo SAR Analyses of Decorrelating Scatterers." Remote Sensing 11, no. 4 (February 18, 2019): 412. http://dx.doi.org/10.3390/rs11040412.

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In synthetic aperture radar (SAR) remote sensing, Differential Tomography (Diff-Tomo) is developing as a powerful crossing of the mature Differential SAR Interferometry and the emerged 3D SAR Tomography. Diff-Tomo produces advanced 4D (3D+Time) SAR imaging capabilities, extensively applied to urban deformation monitoring. More recently, it has been shown that, through Diff-Tomo, identifying temporal spectra of multiple height-distributed decorrelating scatterers, the important decorrelation-robust forest Tomography functionality is possible. To loosen application constraints of the related main experimented full model-based processing, and develop other functionalities, this work presents an adaptive, just semi-parametric, generalized-Capon Diff-Tomo method, first conceived at University of Pisa in 2013, for joint extraction of height and dynamical information of natural distributed (volumetric) scatterers, with its formalization and a series of insights. Particular reference is given to the important functionality of the separation of different decorrelation mechanisms in forest layers. Representative simulated and P-band forest data sample results are also shown. The new Diff-Tomo method is getting a flexible and rich decorrelation-robust Tomography functionality, and is able to profile height-varying temporal decorrelation, for significantly distributed scatterers.
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Lippert, Th, B. Allés, G. Bali, M. D'Elia, A. Di Giacomo, N. Eicker, S. Güsken, et al. "Decorrelating topology with HMC." Nuclear Physics B - Proceedings Supplements 73, no. 1-3 (March 1999): 521–23. http://dx.doi.org/10.1016/s0920-5632(99)85124-x.

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Canfield-Dafilou, Elliot K., and Jonathan S. Abel. "Allpass decorrelating filter design and evaluation." Journal of the Acoustical Society of America 143, no. 3 (March 2018): 1933. http://dx.doi.org/10.1121/1.5036319.

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Hamilton, A. J. S., and M. Tegmark. "Decorrelating the power spectrum of galaxies." Monthly Notices of the Royal Astronomical Society 312, no. 2 (February 21, 2000): 285–94. http://dx.doi.org/10.1046/j.1365-8711.2000.03074.x.

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Novikov, L. V. "Decorrelating scaling functions for wavelet transformations." Journal of Communications Technology and Electronics 51, no. 6 (June 2006): 663–69. http://dx.doi.org/10.1134/s1064226906060076.

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Baykas, Tuncer, Mohamed Siala, and Abbas Yongacoglu. "Generalized decorrelating discrete-time rake receiver." IEEE Transactions on Wireless Communications 6, no. 12 (December 2007): 4268–74. http://dx.doi.org/10.1109/twc.2007.060392.

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Van Heeswyk, Frank, D. D. Falconer, and A. U. H. Sheikh. "Decorrelating detectors for quasi-synchronous CDMA." Wireless Personal Communications 3, no. 1-2 (March 1996): 129–47. http://dx.doi.org/10.1007/bf00333927.

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Boyd, G., B. Allés, M. D'Elia, A. Di Giacomo, and E. Vicari. "Decorrelating the topology in full QCD." Nuclear Physics B - Proceedings Supplements 53, no. 1-3 (February 1997): 544–46. http://dx.doi.org/10.1016/s0920-5632(96)00713-x.

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Sollich, Peter. "Trap models with slowly decorrelating observables." Journal of Physics A: Mathematical and General 39, no. 11 (March 1, 2006): 2573–97. http://dx.doi.org/10.1088/0305-4470/39/11/004.

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Mitra, U., and H. V. Poor. "Adaptive decorrelating detectors for CDMA systems." Wireless Personal Communications 2, no. 4 (1996): 415–40. http://dx.doi.org/10.1007/bf01099344.

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Dissertations / Theses on the topic "Decorrelating"

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XU, BIN. "A Blind Space-Time Decorrelating RAKE Receiver in a DS-CDMA System in Multipath Channels." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1078193785.

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Wang, Yongjian, and Tingxian Zhou. "THE RESEARCH OF A NEW MULTIUSER DETECTION SCHEME COMBINING DECORRELATING DETECTOR AND PARTIAL PARALLEL INTERFERENCE CANCELLER." International Foundation for Telemetering, 2004. http://hdl.handle.net/10150/604934.

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International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California
The decorrelating detector can afford good data estimates because it does not need to know many parameters of the received signal. However, it shows great performance deprivation when the background noise is high. On the other hand, partial parallel interference canceller(PPIC) has the potential to combat the near-far problem and have much lower computation complexity. But its performance depends on the initial data estimate. An improved PPIC scheme is proposed in this paper to combat the near-far problem. It utilizes the advantages of the two detectors by combining them. The focus of this paper is on the BER performance and the near-far resistance capability of the proposed scheme. Computer simulations demonstrate that the proposed detector has good BER performance and near-far resistance capability.
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LI, XIANGTAO. "PERFORMANCE ANALYSIS OF DECORRELATING DETECTORS FOR DUAL-RATE SYNCHRONOUS DS/CDMA SYSTEMS OVER FREQUENCY-SELECTIVE RAYLEIGH FADING CHANNELS." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1028644891.

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Jones, Haley M., and Haley Jones@anu edu au. "On multipath spatial diversity in wireless multiuser communications." The Australian National University. Research School of Information Sciences and Engineering, 2001. http://thesis.anu.edu.au./public/adt-ANU20050202.152811.

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The study of the spatial aspects of multipath in wireless communications environments is an increasingly important addition to the study of the temporal aspects in the search for ways to increase the utilization of the available wireless channel capacity. Traditionally, multipath has been viewed as an encumbrance in wireless communications, two of the major impairments being signal fading and intersymbol interference. However, recently the potential advantages of the diversity offered by multipath rich environments in multiuser communications have been recognised. Space time coding, for example, is a recent technique which relies on a rich scattering environment to create many practically uncorrelated signal transmission channels. Most often, statistical models have been used to describe the multipath environments in such applications. This approach has met with reasonable success but is limited when the statistical nature of a field is not easily determined or is not readily described by a known distribution.¶ Our primary aim in this thesis is to probe further into the nature of multipath environments in order to gain a greater understanding of their characteristics and diversity potential. We highlight the shortcomings of beamforming in a multipath multiuser access environment. We show that the ability of a beamformer to resolve two or more signals in angle directly limits its achievable capacity.¶ We test the probity of multipath as a source of spatial diversity, the limiting case of which is co-located users. We introduce the concept of separability to define the fundamental limits of a receiver to extract the signal of a desired user from interfering users’ signals and noise. We consider the separability performances of the minimum mean square error (MMSE), decorrelating (DEC) and matched filter (MF) detectors as we bring the positions of a desired and an interfering user closer together. We show that both the MMSE and DEC detectors are able to achieve acceptable levels of separability with the users as close as λ/10.¶ In seeking a better understanding of the nature of multipath fields themselves, we take two approaches. In the first we take a path oriented approach. The effects on the variation of the field power of the relative values of parameters such as amplitude and propagation direction are considered for a two path field. The results are applied to a theoretical analysis of the behaviour of linear detectors in multipath fields. This approach is insightful for fields with small numbers of multipaths, but quickly becomes mathematically complex.¶ In a more general approach, we take a field oriented view, seeking to quantify the complexity of arbitrary fields. We find that a multipath field has an intrinsic dimensionality of (πe)R/λ≈8.54R/λ, for a field in a two dimensional circular region, increasing only linearly with the radius R of the region. This result implies that there is no such thing as an arbitrarily complicated multipath field. That is, a field generated by any number of nearfield and farfield, specular and diffuse multipath reflections is no more complicated than a field generated by a limited number of plane waves. As such, there are limits on how rich multipath can be. This result has significant implications including means: i) to determine a parsimonious parameterization for arbitrary multipath fields and ii) of synthesizing arbitrary multipath fields with arbitrarily located nearfield or farfield, spatially discrete or continuous sources. The theoretical results are corroborated by examples of multipath field analysis and synthesis.
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Möhringer, Sandra [Verfasser]. "Decorrelation of Gravimetric Data / Sandra Möhringer." München : Verlag Dr. Hut, 2014. http://d-nb.info/1052375421/34.

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Amrani, Naoufal. "Spectral decorrelation for coding remote sensing data." Doctoral thesis, Universitat Autònoma de Barcelona, 2017. http://hdl.handle.net/10803/402237.

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Hoy en día, los datos de teledetección son esenciales para muchas aplicaciones dirigidas a la observación de la tierra. El potencial de los datos de teledetección en ofrecer información valiosa permite entender mejor las características de la tierra y las actividades humanas. Los desarrollos recientes en los sensores de satélites permiten cubrir amplias áreas geográficas, produciendo imágenes con resoluciones espaciales, espectrales y temporales sin precedentes. Esta cantidad de datos producidos implica una necesidad requiere técnicas de compresión eficientes para mejorar la transmisión y la capacidad de almacenamiento. La mayoría de estas técnicas se basan en las transformadas o en los métodos de predicción. Con el fin de entender la independencia no lineal y la compactación de datos para las imágenes hiperespectrales, empezaos por investigar la mejora de la transformada “Principa Component Analysis” (PCA) que proporciona una decorrelación optima para fuentes Gausianas. Analizamos la eficiencia en compresión sin perdida de “Principal Polynomial Analysis” (PPA) que generaliza PCA con la eliminación de las dependencias non lineales a través de regresión polinomial. Mostramos que las componentes principales no son capaces de predecirse con la regresión polinomial y por tanto no se mejora la independencia del PCA. Este análisis nos permite entender mejor el concepto de la predicción en el dominio de la transformada para fines de compresión. Por tanto, en lugar de utilizar transformadas sofisticadas y costosas como PCA, centramos nuestro interés en transformadas más simples como “CDiscrete Wavelet Transform”(DWT). Mientras tanto, adoptamos técnicas de predicción para explotar cualquier dependencia restante entre las componentes transformadas. Así, introducimos un nuevo esquema llamado “Regression Wavelet Analysis” (RWA) para aumentar la independencia entre los coeficientes de las imágenes hiperespectrales. El algoritmo utiliza la regresión multivariante para explotar las relaciones entre los coeficientes de las transformada DWT. El algoritmo RWA ofrece muchas ventajas, como el bajo coste computacional y la no expansión del rango dinámico. Sin embargo, la propiedad más importante es la eficiencia en compresión sin perdida. Experimentaos extensivos sobre un conjunto amplio de imanes indican que RWA supera las técnicas mas competitivas en el estado del arte com. PCA o el estándar CCSDS-123. Extendemos los beneficios de RWA para la compresión progresiva “ Lossy-to-lossless “. Mostramos que RWA puede alcanzar una relación rate-distorsión mejor que las obtenidas por otras técnicas del estado del arte como PCA. Para este fin, proponemos un esquema de pesos que captura la significancia predictiva de las componentes. Para un análisis más profundo, también analizamos el sesgo en los parámetros de regresión cuando se aplica una compresión con perdida. Mostramos que los parámetros de RWA no son sesgados cuando los modelos de regresión se aplican con los datos recuperados que carecen información. Finalmente, introducimos una versión del algoritmo RWA de muy bajo coste computacional. Con este nuevo enfoque, la predicción solo se basa en muy pocas componentes, mientras que el rendimiento se mantiene. Mientras que la complejidad de RWA se lleva a su bajo extremo, un método de selección eficiente es necesario. A diferencia de otros métodos de selección costosos, proponemos una estrategia simple pero eficiente llamada “ neighbor selection” para seleccionar modelos con pocas componentes predictivas. Sobre un amplio conjunto de imágenes hiperespectrales, estos modelos mantienen el excelente rendimiento de RWA con el modelo máximo, mientras que el coste computacional es reducido al
Today remote sensing is essential for many applications addressed to Earth Observation. The potential capability of remote sensing in providing valuable information enables a better understanding of Earth characteristics and human activities. Recent advances in satellite sensors allow recovering large areas, producing images with unprecedented spatial, spectral and temporal resolution. This amount of data implies a need for efficient compression techniques to improve the capabilities of storage and transmissions. Most of these techniques are dominated by transforms or prediction methods. This thesis aims at deeply analyzing the state-of-the-art techniques and at providing efficient solutions that improve the compression of remote sensing data. In order to understand the non-linear independence and data compaction of hyperspectral images, we investigate the improvement of Principal Component Analysis (PCA) that provides optimal independence for Gaussian sources. We analyse the lossless coding efficiency of Principal Polynomial Analysis (PPA), which generalizes PCA by removing non-linear relations among components using polynomial regression. We show that principal components are not able to predict each other through polynomial regression, resulting in no improvement of PCA at the cost of higher complexity and larger amount of side information. This analysis allows us to understand better the concept of prediction in the transform domain for compression purposes. Therefore, rather than using expensive sophisticated transforms like PCA, we focus on theoretically suboptimal but simpler transforms like Discrete Wavelet Transform (DWT). Meanwhile, we adopt predictive techniques to exploit any remaining statistical dependence. Thus, we introduce a novel scheme, called Regression Wavelet Analysis (RWA), to increase the coefficient independence in remote sensing images. The algorithm employs multivariate regression to exploit the relationships among wavelet-transformed components. The proposed RWA has many important advantages, like the low complexity and no dynamic range expansion. Nevertheless, the most important advantage consists of its performance for lossless coding. Extensive experimental results over a wide range of sensors, such as AVIRIS, IASI and Hyperion, indicate that RWA outperforms the most prominent transforms like PCA and wavelets, and also the best recent coding standard, CCSDS-123. We extend the benefits of RWA to progressive lossy-to-lossless. We show that RWA can attain a rate-distortion performance superior to those obtained with the state-of-the-art techniques. To this end, we propose a Prediction Weighting Scheme that captures the prediction significance of each transformed components. The reason of using a weighting strategy is that coefficients with similar magnitude can have extremely different impact on the reconstruction quality. For a deeper analysis, we also investigate the bias in the least squares parameters, when coding with low bitrates. We show that the RWA parameters are unbiased for lossy coding, where the regression models are used not with the original transformed components, but with the recovered ones, which lack some information due to the lossy reconstruction. We show that hyperspectral images with large size in the spectral dimension can be coded via RWA without side information and at a lower computational cost. Finally, we introduce a very low-complexity version of RWA algorithm. Here, the prediction is based on only some few components, while the performance is maintained. When the complexity of RWA is taken to an extremely low level, a careful model selection is necessary. Contrary to expensive selection procedures, we propose a simple and efficient strategy called \textit{neighbor selection} for using small regression models. On a set of well-known and representative hyperspectral images, these small models maintain the excellent coding performance of RWA, while reducing the computational cost by about 90\%.
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Subramanian, Swetha. "Thermal Ablation Monitoring Using Ultrasound Echo Decorrelation Imaging." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1428068754.

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Tullis, Iain David Charles. "The laser torquemeter and implications of speckle decorrelation on torque measurement." Thesis, Loughborough University, 2000. https://dspace.lboro.ac.uk/2134/12168.

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Torque measurement of a rotating shaft is a method of monitoring machine performance. Steady transmission of mechanical power from the prime mover to the load is vital to avoid gear and bearing wear, shaft fatigue failure, bearing and coupling failure and noise. Mean and fluctuating torque are fundamental quantities of interest. The laser torquemeter is capable of providing a non-contact measurement of time-resolved torque through a driven system. The laser torquemeter depends upon laser speckle produced from coherent light illuminating a diffuse object and the speckle pattern may be used in determining the angular position of a rotating object. When the object rotates the backscattered speckle pattern, which changes continuously but repeats exactly with every revolution, is sampled by a suitably positioned photo detector. The photo detector output signal is periodic and one period is recorded in memory as a reference and the angular position of a shaft can then be determined by a comparison of this recorded reference signal with the current photo detector output signal. The speckle pattern from two axially separated points on the shaft are monitored and under low or, ideally, zero torque the photo detector outputs are recorded into the laser torquemeter electronics. The laser torquemeter then tracks the live photo detector output and determines the angle at the two points on the shaft. Relative angular displacement in the two angle outputs appears when torque is applied and the shaft twists. When the shaft is displaced, for example by vibration, the backscattered speckle pattern changes on the photo detector and the similarity between the recorded, reference signal and the live, current signal is reduced. In this thesis, the cross-correlation of the real-time photodetector output signal and the recorded reference signal as a function of shaft position is examined. The effects of various shaft motions - rotation, axial translation, pitch and yaw, and radial translation are theoretically and experimentally examined and the results can then be used in the design of an optical head for the laser torquemeter. A review of the current torquemeter technology allows for discussion of the broad spectrum of typical torquemeter operating conditions. The optical head of the laser torquemeter may vary significantly for various torque measurement scenarios. A design procedure for the optical head of the laser torquemeter is summarised. The holy grail of torquemeter manufacturers is to produce a cheap, easy to use, robust, accurate, reliable and non-contacting torquemeter. The laser torque meter has great potential to meet these requirements.
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Wells, Susan K. "Temporal and spatial decorrelation scales of the Yellow Sea thermal fields." Thesis, Monterey, California. Naval Postgraduate School, 1994. http://hdl.handle.net/10945/28595.

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Historically, studies on decorrelation scales have been conducted in the deep ocean waters. As the Navy shifts its interest toward the less understood shallow water regions, decorrelation scales need to be computed in order to use formerly deep water models such as the Optimum Thermal Interpolation System (OTIS) for shallow water regions such as the Yellow Sea. A data set containing over 35,000 temperature profiles from 1929 to 1991 was obtained from the Naval Oceanographic Office's MOODS data set. The winter and summer seasons provide realistic results. Winter has the smallest decorrelation scales of all the seasons, approximately 15 days and 165 km. Summer shows that there are different decorrelation scales between the surface and at depth. The surface has scales of 12.3 days and 251 km while at depth the scales are approximately 16.5 days and 163 km. An observational sampling network design is suggested for future sampling of the region. Spring and fall provide mixed results which may be due to the irregularities in time and space of the data set or to the very complex forcing mechanisms found in the region. Overall, this study gives a ground work for better refinement of decorrelation scales and thus, the ability to assess the conversion of deep water models to shallow water regions
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Fosnight, Tyler R. "Echo Decorrelation Imaging of In Vivo HIFU and Bulk Ultrasound Ablation." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447691239.

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Books on the topic "Decorrelating"

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Freeden, Willi. Decorrelative Mollifier Gravimetry. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69909-3.

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Wells, Susan K. Temporal and spatial decorrelation scales of the Yellow Sea thermal field[s]. Monterey, Calif: Naval Postgraduate School, 1994.

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Feeney, Michael Stephen. Time-windowed multiuser decorrelating receivers for asynchronous code division multiple access communication channels. 1994.

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Decorrelative Mollifier Gravimetry: Basics, Ideas, Concepts, and Examples. Springer International Publishing AG, 2022.

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Decorrelative Mollifier Gravimetry: Basics, Ideas, Concepts, and Examples. Springer International Publishing AG, 2021.

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Book chapters on the topic "Decorrelating"

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Djendi, Mohamed, Feriel Khemies, and Amina Morsli. "A Frequency Domain Adaptive Decorrelating Algorithm for Speech Enhancement." In Speech and Computer, 51–54. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23132-7_6.

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Tapiador, Juan E., Mudhakar Srivatsa, John A. Clark, and John A. McDermid. "Decorrelating WSN Traffic Patterns with Maximally Uninformative Constrained Routing." In NETWORKING 2011 Workshops, 207–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23041-7_20.

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Roy, S., D. S. Chen, and S. C. Mau. "An Adaptive Multi-user Decorrelating Receiver for CDMA Systems." In Wireless and Mobile Communications, 67–81. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2716-9_5.

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van Hemmen, J. L., and N. Klemmer. "Unlearning and Its Relevance to REM Sleep: Decorrelating Correlated Data." In Neural Network Dynamics, 30–43. London: Springer London, 1992. http://dx.doi.org/10.1007/978-1-4471-2001-8_3.

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Bar-Ness, Y. "The Bootstrap Decorrelating Algorithm: A Promising Tool for Adaptive Separation of Multi-User CDMA Signals." In Information Technology: Transmission, Processing and Storage, 68–81. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1013-2_6.

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Freeden, Willi. "Concluding Remarks." In Decorrelative Mollifier Gravimetry, 451–52. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69909-3_16.

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Freeden, Willi. "Decorrelative Acoustic Potential-Based Exploration." In Decorrelative Mollifier Gravimetry, 419–36. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69909-3_14.

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Freeden, Willi. "Volume Methodology." In Decorrelative Mollifier Gravimetry, 237–301. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69909-3_10.

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Freeden, Willi. "Decorrelative Elastic Potential-Based Exploration." In Decorrelative Mollifier Gravimetry, 437–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69909-3_15.

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Freeden, Willi. "Decorrelative Monopole Potential-Based Gravimetry." In Decorrelative Mollifier Gravimetry, 363–69. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69909-3_12.

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Conference papers on the topic "Decorrelating"

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D'Aria, Davide, Antonio Leanza, Andrea Monti-Guarnieri, and Andrea Recchia. "Decorrelating targets: Models and measures." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7729826.

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Abuhilal, Hasan, Aykut Hocanin, and Huseyin Bilgekul. "Robust MIMO-CDMA Decorrelating Detector." In 2007 IEEE International Conference on Signal Processing and Communications. IEEE, 2007. http://dx.doi.org/10.1109/icspc.2007.4728423.

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Ramirez, Miguel Arjona. "Decorrelating transforms for spectral vector quantization." In 2013 18th International Conference on Digital Signal Processing (DSP). IEEE, 2013. http://dx.doi.org/10.1109/icdsp.2013.6622682.

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Zhang, Huanjiong. "A New Decorrelating Method of MUD." In 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2009. http://dx.doi.org/10.1109/wicom.2009.5301888.

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Usui, Shiro, Shigeki Nakauchi, and Yasuo Miyamoto. "A decorrelating neural network for color constancy." In 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.5761236.

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Usui, Nakauchi, and Miyamoto. "A Decorrelating Neural Network For Color Constancy." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.594701.

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FitzGerald, Des, Rod Paterson, and Asbjorn Christensen. "Decorrelating measured airborne gravity gradiometry data with topography." In 12th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 15-18 August 2011. Society of Exploration Geophysicists and Brazilian Geophysical Society, 2011. http://dx.doi.org/10.1190/sbgf2011-147.

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Ramprasad, Sumant, Naresh R. Shanbhag, and Ibrahim N. Hajj. "Decorrelating (DECOR) transformations for low-power adaptive filters." In the 1998 international symposium. New York, New York, USA: ACM Press, 1998. http://dx.doi.org/10.1145/280756.280923.

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Peng, M. "A modified linear decorrelating detector for asynchronous CDMA." In IEE Colloquium on CDMA Techniques and Applications for Third Generation Mobile Systems. IEE, 1997. http://dx.doi.org/10.1049/ic:19970714.

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Le, Bingbing, Duo Long Wu, and Yan Jie Wu. "A new DOA method on decorrelating strong correlation signal." In 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE). IEEE, 2012. http://dx.doi.org/10.1109/csae.2012.6272639.

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Reports on the topic "Decorrelating"

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T.S. Hahm, P.H. Diamond, and E.-J. Kim. Trapped Electron Precession Shear Induced Fluctuation Decorrelation. Office of Scientific and Technical Information (OSTI), July 2002. http://dx.doi.org/10.2172/808377.

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2

Hahm, T. S. Rotation shear induced fluctuation decorrelation in a toroidal plasma. Office of Scientific and Technical Information (OSTI), June 1994. http://dx.doi.org/10.2172/10160733.

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3

Jun, Soon Yung. The Azimuthal decorrelation of jets widely separated in rapidity. Office of Scientific and Technical Information (OSTI), January 1997. http://dx.doi.org/10.2172/1421731.

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4

Kim, Chang Lyong. A Study of the Azimuthal Decorrelation between Jets with Large Rapidity Separation. Office of Scientific and Technical Information (OSTI), January 1996. http://dx.doi.org/10.2172/1421748.

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5

Budkewitsch, P., M. A. D'Iorio, P. W. Vachon, D. T. Andersen, and W H Pollard. Sources of phase decorrelation in SAR scene coherence images from Arctic environments. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1999. http://dx.doi.org/10.4095/219537.

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6

Chakravarthula, Kiran. Study of Jet Transverse Momentum and Jet Rapidity Dependence on Dijet Azimuthal Decorrelations. Office of Scientific and Technical Information (OSTI), January 2012. http://dx.doi.org/10.2172/1128085.

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7

R. Nazikian, K. Shinohara, G.J. Kramer, E. Valeo, K. Hill, T.S. Hahm, G. Rewoldt, et al. Measurement of Turbulence Decorrelation during Transport Barrier Evolution in a High Temperature Fusion Plasma. Office of Scientific and Technical Information (OSTI), March 2005. http://dx.doi.org/10.2172/840434.

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8

Dudley, J. P., and S. V. Samsonov. SAR interferometry with the RADARSAT Constellation Mission. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329396.

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Abstract:
The RADARSAT Constellation Mission (RCM) is Canada's latest system of C-band Synthetic Aperture Radar (SAR) Earth observation satellites. The system of three satellites, spaced equally in a common orbit, allows for a rapid four-day repeat interval. The RCM has been designed with a selection of stripmap, spotlight, and ScanSAR beam modes which offer varied combinations of spatial resolution and coverage. Using Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques, the growing archive of SAR data gathered by RCM can be used for change detection and ground deformation monitoring for diverse applications in Canada and around the world. In partnership with the Canadian Space Agency (CSA), the Canada Centre for Mapping and Earth Observation (CCMEO) has developed an automated system for generating standard and advanced deformation products and change detection from SAR data acquired by RCM and RADARSAT-2 satellites using DInSAR processing methodology. Using this system, this paper investigates four key interferometric properties of the RCM system which were not available on the RADARSAT-1 or RADARSAT-2 missions: The impact of the high temporal resolution of the four-day repeat cycle of the RCM on temporal decorrelation trends is tested and fitted against simple temporal decay models. The effect of the normalization and the precision of the radiometric calibration on interferometric spatial coherence is investigated. The performance of the RCM ScanSAR mode for wide area interferometric analysis is tested. The performance of the novel RCM Compact-polarization (CP) mode for interferometric analysis is also investigated.
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