Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review

The purpose of this paper is to survey and assess the state-of-the-art in automatic target recognition for synthetic aperture radar imagery (SAR-ATR). The aim is not to develop an exhaustive survey of the voluminous literature, but rather to capture in one place the various approaches for implementing the SAR-ATR system. This paper is meant to be as self-contained as possible, and it approaches the SAR-ATR problem from a holistic end-to-end perspective. A brief overview for the breadth of the SAR-ATR challenges is conducted. This is couched in terms of a single-channel SAR, and it is extendable to multi-channel SAR systems. Stages pertinent to the basic SAR-ATR system structure are defined, and the motivations of the requirements and constraints on the system constituents are addressed. For each stage in the SAR-ATR processing chain, a taxonomization methodology for surveying the numerous methods published in the open literature is proposed. Carefully selected works from the literature are presented under the taxa proposed. Novel comparisons, discussions, and comments are pinpointed throughout this paper. A two-fold benchmarking scheme for evaluating existing SAR-ATR systems and motivating new system designs is proposed. The scheme is applied to the works surveyed in this paper. Finally, a discussion is presented in which various interrelated issues, such as standard operating conditions, extended operating conditions, and target-model design, are addressed. This paper is a contribution toward fulfilling an objective of end-to-end SAR-ATR system design

Aeronautical Engineering: A continuing bibliography with indexes (supplement 205)

This bibliography lists 517 reports, articles and other documents introduced into the NASA scientific and technical information system in September 1986

NASA Tech Briefs, February 1998

Topics: Test Tools; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Software; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Life Sciences

Unscrambling Nonlinear Dynamics in Synthetic Aperture Radar Imagery

In analyzing single-channel synthetic aperture radar (SAR) imagery, three interrelated questions often arise. First, should one use the detected or the complex-valued image? Second, what is the `best' statistical model? Finally, what constitutes the `best' signal processing methods? This paper addresses these questions from the overarching perspective of the generalized central limit theorem, which underpins nonlinear signal processing. A novel procedure for characterizing the nonlinear dynamics in SAR imagery is proposed. To apply the procedure, three complementary 1-D abstractions for a 2-D SAR chip are introduced. Our analysis is demonstrated on real-world datasets from multiple SAR sensors. The nonlinear dynamics are found to be resolution dependent. As the SAR chip is detected, nonlinear effects are found to be obliterated (i.e., for magnitude-detection) or altered (i.e., for power-detection). In the presence of extended targets (i.e., nonlinear scatterers), it is recommended to use the complex-valued chip rather than the detected one. Furthermore, to exploit the intrinsic nonlinear statistics, it is advised to utilize relevant nonlinear signal analysis techniques

Inversion Methods in Atmospheric Remote Sounding

The mathematical theory of inversion methods is applied to the remote sounding of atmospheric temperature, humidity, and aerosol constituents