1,550 research outputs found

    Doppler Radar for USA Weather Surveillance

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    Beyond the spatio-temporal limits of atmospheric radars: inverse problem techniques and MIMO systems

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    The Earth’s upper atmosphere (UA) is a highly dynamic region dominated by atmospheric waves and stratified turbulence covering a wide range of spatio-temporal scales. A comprehensive study of the UA requires measurements over a broad range of frequencies and spatial wavelengths, which are prohibitively costly. To improve the understanding of the UA, an investment in efficient and large observational infrastructures is required. This work investigates remote sensing techniques based on MIMO and inverse problems techniques to improve the capabilities of current atmospheric radars

    Novel Methods in Computational Imaging with Applications in Remote Sensing

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    This dissertation is devoted to novel computational imaging methods with applications in remote sensing. Computational imaging methods are applied to three distinct applications including imaging and detection of buried explosive hazards utilizing array radar, high resolution imaging of satellites in geosynchronous orbit utilizing optical hypertelescope arrays, and characterization of atmospheric turbulence through multi-frame blind deconvolution utilizing conventional optical digital sensors. The first application considered utilizes a radar array employed as a forward looking ground penetrating radar system with applications in explosive hazard detection. A penalized least squares technique with sparsity-inducing regularization is applied to produce imagery, which is consistent with the expectation that objects are sparsely populated but extended with respect to the pixel grid. Additionally, a series of pre-processing steps is demonstrated which result in a greatly reduced data size and computational cost. Demonstrations of the approach are provided using experimental data and results are given in terms of signal to background ratio, image resolution, and relative computation time. The second application involves a sparse-aperture telescope array configured as a hypertelescope with applications in long range imaging. The penalized least squares technique with sparsity-inducing regularization is adapted and applied to this very different imaging modality. A comprehensive study of the algorithm tuning parameters is performed and performance is characterized using the Structure Similarity Metric (SSIM) to maximize image quality. Simulated measurements are used to show that imaging performance achieved using the pro- posed algorithm compares favorably in comparison to conventional Richardson-Lucy deconvolution. The third application involves a multi-frame collection from a conventional digital sensor with the primary objective of characterizing the atmospheric turbulence in the medium of propagation. In this application a joint estimate of the image is obtained along with the Zernike coefficients associated with the atmospheric PSF at each frame, and the Fried parameter r0 of the atmosphere. A pair of constraints are applied to a penalized least squares objective function to enforce the theoretical statistics of the set of PSF estimates as a function of r0. Results of the approach are shown with both simulated and experimental data and demonstrate excellent agreement between the estimated r0 values and the known or measured r0 values respectively

    An adaptive moments estimation technique applied to MST radar echoes

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    An adaptive spectral moments estimation technique has been developed for analyzing the Doppler spectra of the mesosphere-stratosphere-troposphere (MST) radar signals. The technique, implemented with the MST radar at Gadanki (13.5°N, 79°E), is based on certain criteria, set up for the Doppler window, signal-to-noise ratio (SNR), and wind shear parameters, which are used to adaptively track the signal in the range-Doppler spectral frame. Two cases of radar data, one for low and the other for high SNR conditions, have been analyzed and the results are compared with those from the conventional method based on the strongest peak detection in each range gate. The results clearly demonstrate that by using the adaptive method the height coverage can be considerably enhanced compared to the conventional method. For the low SNR case, the height coverage for the adaptive and conventional methods is about 22 and 11 km, respectively; the corresponding heights for the high SNR case are 24 and 13 km. To validate the results obtained through the adaptive method, the velocity profile is compared with global positioning system balloon sounding (GPS sonde) observations. The results of the adaptive method show excellent agreement with the GPS sonde measured wind speeds and directions throughout the height profile. To check the robustness and reliability of the adaptive algorithm, data taken over a diurnal cycle at 1-h intervals were analyzed. The results demonstrate the reliability of the algorithm in extracting wind profiles that are self-consistent in time. The adaptive method is thus found to be of considerable advantage over the conventional method in extracting information from the MST radar signal spectrum, particularly under low SNR conditions that are free from interference and ground clutter

    A satellite-based radar wind sensor

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    The objective is to investigate the application of Doppler radar systems for global wind measurement. A model of the satellite-based radar wind sounder (RAWS) is discussed, and many critical problems in the designing process, such as the antenna scan pattern, tracking the Doppler shift caused by satellite motion, and backscattering of radar signals from different types of clouds, are discussed along with their computer simulations. In addition, algorithms for measuring mean frequency of radar echoes, such as the Fast Fourier Transform (FFT) estimator, the covariance estimator, and the estimators based on autoregressive models, are discussed. Monte Carlo computer simulations were used to compare the performance of these algorithms. Anti-alias methods are discussed for the FFT and the autoregressive methods. Several algorithms for reducing radar ambiguity were studied, such as random phase coding methods and staggered pulse repitition frequncy (PRF) methods. Computer simulations showed that these methods are not applicable to the RAWS because of the broad spectral widths of the radar echoes from clouds. A waveform modulation method using the concept of spread spectrum and correlation detection was developed to solve the radar ambiguity. Radar ambiguity functions were used to analyze the effective signal-to-noise ratios for the waveform modulation method. The results showed that, with suitable bandwidth product and modulation of the waveform, this method can achieve the desired maximum range and maximum frequency of the radar system

    Spectral and correlation analysis with applications to middle-atmosphere radars

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    The correlation and spectral analysis methods for uniformly sampled stationary random signals, estimation of their spectral moments, and problems arising due to nonstationary are reviewed. Some of these methods are already in routine use in atmospheric radar experiments. Other methods based on the maximum entropy principle and time series models have been used in analyzing data, but are just beginning to receive attention in the analysis of radar signals. These methods are also briefly discussed

    Auto-regressive model based polarimetric adaptive detection scheme part I: Theoretical derivation and performance analysis

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    This paper deals with the problem of target detection in coherent radar systems exploiting polarimetric diversity. We resort to a parametric approach and we model the disturbance affecting the data as a multi-channel autoregressive (AR) process. Following this model, a new polarimetric adaptive detector is derived, which aims at improving the target detection capability while relaxing the requirements on the training data size and the computational burden with respect to existing solutions. A complete theoretical characterization of the asymptotic performance of the derived detector is provided, using two different target fluctuation models. The effectiveness of the proposed approach is shown against simulated data, in comparison with alternative existing solutions

    Orbital Effects in Spaceborne Synthetic Aperture Radar Interferometry

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    This book reviews and investigates orbit-related effects in synthetic aperture Radar interferometry (InSAR). The translation of orbit inaccuracies to error signals in the interferometric phase is concisely described; estimation and correction approaches are discussed and evaluated with special focus on network adjustment of redundantly estimated baseline errors. Moreover, the effect of relative motion of the orbit reference frame is addressed

    Publications of the Jet Propulsion Laboratory 1989

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    This bibliography describes and indexes by primary author the externally distributed technical reporting, released during 1989, that resulted from scientific and engineering work performed, or managed, by JPL. Three classes of publications are included: JPL publications in which the information is complete for a specific accomplishment; articles from the quarterly Telecommunications and Data Acquisition (TDA) Progress Report; and articles published in the open literature
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