Specification, verification, and maintenance of image quality over the lifecycle of an operational airborne SAR begin with the specification for the system itself. Verification of image quality-oriented specification compliance can be enhanced by including a specification requirement that a vendor provide appropriate imagery at the various phases of the system life cycle. The nature and content of the imagery appropriate for each stage of the process depends on the nature of the test, the economics of collection, and the availability of techniques to extract the desired information from the data. At the earliest lifecycle stages, Concept and Technology Development (CTD) and System Development and Demonstration (SDD), the test set could include simulated imagery to demonstrate the mathematical and engineering concepts being implemented thus allowing demonstration of compliance, in part, through simulation. For Initial Operational Test and Evaluation (IOT&E), imagery collected from precisely instrumented test ranges and targets of opportunity consisting of a priori or a posteriori ground-truthed cultural and natural features are of value to the analysis of product quality compliance. Regular monitoring of image quality is possible using operational imagery and automated metrics; more precise measurements can be performed with imagery of instrumented scenes, when available. A survey of image quality measurement techniques is presented along with a discussion of the challenges of managing an airborne SAR program with the scarce resources of time, money, and ground-truthed data. Recommendations are provided that should allow an improvement in the product quality specification and maintenance process with a minimal increase in resource demands on the customer, the vendor, the operational personnel, and the asset itself.
Eastman Kodak Company conducts image quality monitoring of U.S. Government-operated Synthetic Aperture Radar (SAR) sensors. Our quality assurance methodology uses automated metrics in parallel with human analyst scoring of image quality factors to track quality trends in an image chain. A key feature of the program is that analysis is performed periodically on images selected from actual mission data. Historically, tasking the sensors to fly over calibrated test sites on such a regular basis has failed because of contention for collection resources from higher priority jobs. In addition, detected, 8-bit NITF data is often the only image product that is distributed. The scarcity of high radar cross-section (RCS) individual point scatterers as well as the lack of complex data provides challenges to the ability to estimate a key image quality parameter, the impulse response function (IPR). This paper discusses a method to isolate and aggregate signatures of multiple low signal-to-noise ratio IPRs in detected mission imagery. Measures of -3dB and -15dB IPR widths in range and azimuth have been realized along with estimates of far sidelobe levels.
Next generation reconnaissance and Automatic Target Detection/Recognition (ATD/R) performance goals will impose new image quality requirements on integrated SAR hardware and software systems. Signal processing techniques using demonstrated non-parametric autofocus methods such as the Phase Gradient Autofocus algorithm and developments in robust super-resolution signal processing offer the opportunity for reducing overall system cost through utilization of less costly hardware options in integrated system design. Traditional requirements on image quality from integrated hardware-software SAR systems have used image quality metrics based on the characteristics of the overall system impulse response function. An additional class of image quality metrics is available based on the performance of the ATD/R algorithms that are to utilize the imagery. The performance of a given SAR system by these measures is expected to be context-sensitive and dependant on both target and clutter characteristics in a manner not necessarily readily characterizable solely in terms of system impulse response function measures of image quality. A simulation illustration of these issues is presented for a test case in which a range of SAR sensor hardware options are processed through a representative texture metric mechanization. Potential performance dependencies on target and clutter characteristics are reviewed and the efficacy of supplementing impulse response function image quality metrics with additional appropriate predictors of ATD/R performance is reviewed.
A numerical method is proposed to estimate the cumulative probability of detection for a surveillance radar that attempts to detect a target closing in range, within a fixed range window, with a desired level of confidence. In this case, one or more radar scan-target intersections may occur anywhere within the range window depending upon the timing of the radar scan, the timing of the target entry into the window, and the locus of the radar-to-target range along the trajectory. This detection scenario could, for example, arise as a result of a sophisticated search strategy adopted by a surveillance radar utilizing an electrically scanned array to achieve a higher degree of efficiency in radar resource management. Single-scan probabilities of detection within the range window can be measured by observing radar performance during repeated test against a suitable target trajectory. These measurements can then be used within a Monte Carlo-style computer simulation of multiple target trajectories to construct a probability density function from which an estimate of cumulative probability of detection and confidence limits can be derived. This approach enables performance verification results to be used for predicting performance under alternative target trajectory scenarios.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.