![]() Though one would normally conclude that the wind direction is somehow the opposite of the rest of the surrounding area and moving very fast, this is not correct. In some cases when very high wind speeds are present, such as when the radar samples strong jets or tropical cyclones, a radial velocity maximum or minimum will contain colors from the opposite wind direction in its center. Use radar imagery to identify instances of anomalous propagation, velocity and range folding, non-meteorological targets, and other radar artifacts.Use radar imagery to identify common features of precipitating phenomena, such as winter storms, convection, and tropical cyclones.Use radar imagery to identify phenomena that commonly occur during otherwise fair weather including dust storms, smoke, horizontal convective rolls, fronts, and other boundaries.Interpret precipitation intensity and movement using radar reflectivity imagery.Interpret wind speed and direction using Doppler radial velocity imagery.Describe the primary uses and limitations of radar data as well as factors that affect data quality and interpretation.Explain the basic principles of weather radar operation.Although intended as an accelerated introduction to understanding and using basic Doppler weather radar products, the module is also an excellent refresher for more experienced users.īy the end of this module, users will be able to: Compare the performance of the proposed algorithm to standard time-frequency estimators applied to the same data sets.This 2-hour module discusses the fundamental principles of Doppler weather radar operation and how to interpret common weather phenomena using radar imagery. Apply the complex RPEM algorithm to synthesized ISAR data using the above simulator. Develop and extend a complex, recursive-in-time, time- frequency parameter estimator based on the recursive prediction error method (RPEM) using the underlying Gauss- Newton algorithms. Our goals for the continued effort are to: 1. This algorithm is easily extended to recursive solution and will probably become part of the overall recursive processing approach to solve the ISAR imaging problem. It should also be noted that we developed a batch minimum variance translational motion compensation (TMC) algorithm to estimate the radial components of target motion (see Section IV). We have achieved all of these goals during the Phase I of the project and plan to complete the overall development, application and comparison of the parametric approach to other time-frequency estimators (STFT, etc.) on our synthesized vehicular data sets during the next phase of funding. Initiate the development of the recursive algorithm. Apply the standard time-frequency short-term Fourier transform (STFT) estimator, initially to a synthesized data set and 4. Develop a parametric, recursive-in-time approach to the ISAR target imaging more » problem 3. Develop an ISAR stepped-frequency waveform (SFWF) radar simulator based on a point scatterer vehicular target model incorporating both translational and rotational motion 2. Our short term (Phase I) goals were to: 1. The primary objective of this research was aimed at developing an alternative time-frequency approach which is recursive-in-time to be applied to the Inverse Synthethic Aperture Radar (ISAR) imaging problem discussed subsequently. This report summarizes the work performed for the Office of the Chief of Naval Research (ONR) during the period of 1 September 1997 through 31 December 1997. (GA-ASI), an affiliate of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and related mission systems, including the Predator/Gray Eagle-series and Lynx Multi-mode Radar. General Atomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Research and Development Agreement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. Acknowledgements This report was funded by General Atomics Aeronautical Systems, Inc. While the information herein is not new to more » the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall MWAS radar system. This report identifies and explores those characteristics and limits, and how they depend on hardware system parameters and environmental conditions. Proper design and operation of an airborne Maritime Wide Area Search (MWAS) radar requires an understanding of system performance characteristics and limitations, and furthermore understanding the trades amongst a large number of interdependent system parameters. One of the earliest applications for radar was to search for and find maritime vessels on the open sea.
0 Comments
Leave a Reply. |