HR: 16:00h
AN: SA14A-01    [Abstracts]
TI: Improved Incoherent Scatter Measurements at Arecibo: Techniques, Analysis, and Applications
AU: * Sulzer, M P
EM: msulzer@naic.edu
AF: Arecibo Observatory, HC 3 Box 53995, Arecibo, PR 00612-9136 United States
AU: Nikoukar, R
EM: nikoukar@uiuc.edu
AF: University of Illinois, Electrical and Computer Engineering 1308 West Main Street, Urbana, IL 61801 United States
AU: Aponte, N
EM: naponte@naic.edu
AF: Arecibo Observatory, HC 3 Box 53995, Arecibo, PR 00612-9136 United States
AU: Fernandez, J
EM: jfernand@naic.edu
AF: Arecibo Observatory, HC 3 Box 53995, Arecibo, PR 00612-9136 United States
AU: Gonzalez, S
EM: sixto@naic.edu
AF: Arecibo Observatory, HC 3 Box 53995, Arecibo, PR 00612-9136 United States
AB: Incoherent scatter radar (ISR) is a mature technique for Ionospheric measurement. Yet there is still the potential to solve important scientific problems through improved measurement capabilities. One approach is to use improvements in radar technology; for example, the National Science Foundation is currently funding the construction of the Advanced Modular Incoherent Scatter Radar (AMISR). Another approach that works at existing facilities, especially at Arecibo with its tremendous sensitivity, is the application of new information handling and processing technology. All stages of the measurement process from the transmission of the powerful radar pulse to the final extraction of the geophysical parameters need to be optimized in an interlocking manner. For F region ion line measurements, the use of better coding techniques allows the minimization of statistical errors while eliminating systematic errors due to the length of the radar pulse. Application of the proper inverse technique is essential for the extraction of error-free profiles. When incoherent scatter was new, not only was the computer power to apply such techniques unavailable, but inverse theory had not advanced to the point where they could be developed. One of the first very good inverse techniques for comparison of data and a physical model, non-linear least squares fitting, has been almost universally applied to ISR data analysis. It is computationally efficient in that a minimal amount of the model space is explored. Yet it suffers from problems due to the accuracy of the partial derivatives, measured in a noisy environment, that direct the minimization. We are now seeing that so-called genetic algorithms can provide better estimates in certain cases. They explore a larger part of the space and take more computer time, and could not have been used in earlier decades. The application of ISR to a scientific problem often requires the use of several radar techniques, for example, the measurement of both the ion and plasma lines, with very high resolution and accuracy. The required flexibility in the hardware is provided by new technology, the digital receiver. The storage space and computing capability necessary for routine high-resolution plasma line measurement is quite large, but less of a problem than in the past. The analysis of such data to determine the molecular ion density in the F1 region or the ion-neutral collision frequency in the E region requires all these new developments as well as accurate measurements of radar characteristics such as the near field gain.
DE: 2419 Ion chemistry and composition (0335)
DE: 2443 Midlatitude ionosphere
DE: 2494 Instruments and techniques
DE: 6929 Ionospheric physics (1240, 2400)
SC: SPA-Aeronomy [SA]
MN: Fall Meeting 2005