Publications

The Advanced Land Imager (ALI) is one of three instruments flown on the first Earth Observing mission (EO-1) under NASA's New Millennium Program (NMP). The primary NMP mission objective is to flight-validate advanced technologies that will enable dramatic improvements in performance, cost, mass and schedule for future, Landsat-like, earth remote sensing instruments. ALI contains a number of innovative features, including all the Category 1 technology demonstrations of the EO-1 mission. These include the basic instrument architecture which employs a push-broom data collection mode, a wide field of view optical design, compact multispectral detector arrays, non-cryogenic HgCdTe for the short wave infrared bands, silicon carbide optics and a multi-level solar calibration technique. The Earth Observing-1 spacecraft was successfully launched on November 21, 2000. During the first sixty days on orbit, several Earth scenes were collected and on-orbit calibration techniques were exercised by the Advanced Land Imager. This paper presents the status of ALI radiometric performance characterization obtained from the data collected during that period.

The Lincoln Near-Earth Asteroid Research (LINEAR) program has applied electro-optical technology developed for Air Force Space Surveillance applications to the problem of discovering near-Earth asteroids (NEAs) and comets. This application is natural due to the commonality between the surveillance of the sky for man-made satellites and the search for near-Earth objects (NEOs). Both require the efficient search of broad swaths of sky to detect faint, moving objects. Currently, the Air Force Ground-based Electro-Optic Deep Space Surveillance (GEODSS) systems, which operate as part of the worldwide U.S. space surveillance network, are being upgraded to state-of-the-art charge-coupled device (CCD) detectors. These detectors are based on recent advances made by MIT Lincoln Laboratory in the fabrication of large format, highly sensitive CCDs. In addition, state-of-the-art data processing algorithms have been developed to employ the new detectors for search operations. In order to address stressing space surveillance requirements, the Lincoln CCDs have a unique combination of features, including large format, high quantum efficiency, frame transfer, high readout rate, and low noise, not found on any commercially available CCD. Systems development for the GEODSS upgrades has been accomplished at the Lincoln Laboratory Experimental Test Site (ETS) located near Socorro, New Mexico, over the past several years. Starting in 1996, the Air Force funded a small effort to demonstrate the effectiveness of the CCD and broad area search technology when applied to the problem of finding asteroids and comets. This program evolved into the current LINEAR program, which is jointly funded by the Air Force Office of Scientific Research and NASA. LINEAR, which started full operations in March of 1998, has discovered through September of 1999, 257 NEAs (of 797 known to date), 11 unusual objects (of 44 known), and 32 comets. Currently, LINEAR is contributing ~70% of the worldwide NEA discovery rate and has single-handedly increased the observations submitted to the Minor Planet Center by a factor of 10. This paper covers the technology used by the program, the operations, and the detailed results of the search efforts.

This report documents the Scan-Scan correlator algorithms for the ASR-9 Processor Augmentation Card (9-PAC) project. The 9-PAC is a processor card that serves as a processing enhancement to the existing ASR-9's post-processor system. It provides increased speed and memory capabilities to the processor, which allows for the introduction of more complex scan-scan correlator algorithms. These more complex algorithms improve the ASR-9's system performance through decreased false alarms, and increased detection of aircraft. The 9-PAC Scan-Scan correlator, also known as the Tracker, consists of three basic processing tasks: initialization, input/output, and the actual Tracker. The Tracker can be broken down further into four main processing functions: report-to track association, report-to-track correlation, track update, and track initiation.