Inverse synthetic aperture radar processing using parametric timefrequency estimators Phase I
Abstract
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. The primary objective of this research was aimed at developing an alternative timefrequency approach which is recursiveintime to be applied to the Inverse Synthethic Aperture Radar (ISAR) imaging problem discussed subsequently. Our short term (Phase I) goals were to: 1. Develop an ISAR steppedfrequency waveform (SFWF) radar simulator based on a point scatterer vehicular target model incorporating both translational and rotational motion; 2. Develop a parametric, recursiveintime approach to the ISAR target imaging problem; 3. Apply the standard timefrequency shortterm Fourier transform (STFT) estimator, initially to a synthesized data set; and 4. Initiate the development of the recursive algorithm. 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 timefrequency estimators (STFT, etc.) on our synthesized vehicular data sets during the next phase of funding. 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).more »
 Authors:
 Publication Date:
 Research Org.:
 Lawrence Livermore National Lab., CA (United States)
 Sponsoring Org.:
 USDOE, Washington, DC (United States)
 OSTI Identifier:
 304514
 Report Number(s):
 UCRLID130769
ON: DE98058802; BR: YN0100000
 DOE Contract Number:
 W7405ENG48
 Resource Type:
 Technical Report
 Resource Relation:
 Other Information: PBD: 31 Dec 1997
 Country of Publication:
 United States
 Language:
 English
 Subject:
 44 INSTRUMENTATION, INCLUDING NUCLEAR AND PARTICLE DETECTORS; RADAR; SIGNALS; IMAGES; DATA PROCESSING; SIMULATORS
Citation Formats
Candy, J.V., LLNL. Inverse synthetic aperture radar processing using parametric timefrequency estimators Phase I. United States: N. p., 1997.
Web. doi:10.2172/304514.
Candy, J.V., LLNL. Inverse synthetic aperture radar processing using parametric timefrequency estimators Phase I. United States. doi:10.2172/304514.
Candy, J.V., LLNL. 1997.
"Inverse synthetic aperture radar processing using parametric timefrequency estimators Phase I". United States.
doi:10.2172/304514. https://www.osti.gov/servlets/purl/304514.
@article{osti_304514,
title = {Inverse synthetic aperture radar processing using parametric timefrequency estimators Phase I},
author = {Candy, J.V., LLNL},
abstractNote = {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. The primary objective of this research was aimed at developing an alternative timefrequency approach which is recursiveintime to be applied to the Inverse Synthethic Aperture Radar (ISAR) imaging problem discussed subsequently. Our short term (Phase I) goals were to: 1. Develop an ISAR steppedfrequency waveform (SFWF) radar simulator based on a point scatterer vehicular target model incorporating both translational and rotational motion; 2. Develop a parametric, recursiveintime approach to the ISAR target imaging problem; 3. Apply the standard timefrequency shortterm Fourier transform (STFT) estimator, initially to a synthesized data set; and 4. Initiate the development of the recursive algorithm. 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 timefrequency estimators (STFT, etc.) on our synthesized vehicular data sets during the next phase of funding. 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). 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. Our goals for the continued effort are to: 1. Develop and extend a complex, recursiveintime, time frequency parameter estimator based on the recursive prediction error method (RPEM) using the underlying Gauss Newton algorithms. 2. Apply the complex RPEM algorithm to synthesized ISAR data using the above simulator. 3. Compare the performance of the proposed algorithm to standard timefrequency estimators applied to the same data sets.},
doi = {10.2172/304514},
journal = {},
number = ,
volume = ,
place = {United States},
year = 1997,
month =
}

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