Analysis Techniques Applied To Balloon-Borne Mosaic Interferometer And Radiometer Measurements

Abstract Computational techniques developed for the reduction and analysis of interferometer and radiometer data from the Balloon Altitude Mosaic Measurements (BAMM) program are presented. Emphasis is given to the reduction and analysis techniques developed for mosaic detector interferometer measurements. The presentation includes discussion of techniques to quality check, edit and simulate radiance values. Statistical analyses performed on simulated radiance data is described and examples of raw and edited data and statistical parameters are given. A brief discussion of radiometer reduction and analysis techniques is presented which includes data editing; filtering and decimation; statistical parameter determination; autocovariance estimation; and Fourier Power Spectral estimation of radiance.IntroductionThis presentation concerns the digital signal processing techniques developed to analyze and reduce radiometer and interferometer measurements into radiance. The use of inter­ ferometer measurements allowed the determination of the radiance values over any wavelength band(s). These radiance profiles are then statistically analyzed. The initial major concerns in developing the analysis were the magnitude of the error that would be added to the data base,, because of the mathematical limitations of the techniques utilized and com­ puter time. These concerns were minimised by the fact that the noise inherent to the experiments dominated those that would be introduced by the mathematical models. The pro­ cedures and computer coding were developed to minimize the amount of computer time and place some limitation on the computer storage used.Since the analysis required the calculation of many discrete Fourier Transforms, it was essential to develop a fast version of the Fast Fourier Transform. (The Fast Fourier Transform is an algorithm for rapidly calculating Discrete Fourier Transforms.) The routine developed minimizes the time spent deciding which "butterfly" (butterfly refers to a logical procedure used many times in the Fast Fourier Transform technique) to calculate next. Other techniques such as suggested by Morris1 , are available but the one used was judged the fastest given the computer storage limitations.Data characteristicsThe sample rate for the radiometer data base (one sample every .0073 seconds) was such that very little aliasing (ambiguity in deciding at which frequencies the Fourier Power exists) occurred. Further, there was negligible Fourier Power near the Nyquist Frequency (the highest frequency inherent in the Discrete Fourier Transforms).The interferometer measurements consisted of a "scan" every At seconds. Sixteen simul­ taneous interferograms were generated for each scan (only the central 4 detectors were used in a rapid scan mode). Each detector, however, is processed individually. The focal plane consisted of a 4x4 mosaic array of detectors, hence for the two scan rates At, was either .23 seconds or .0575 seconds. A scan consisted of measurements of the interferograms starting at maximum optical retardation and moving to the other extremum. The next scan repeated the process heading in the opposite direction. Limitations in the equipment meant that the time interval between every other scan was constant. The time interval between consecutive scans, however, was a function of the direction. Similarly, the mechanical position corresponding to the zero optical retardation for every other scan was reproducible but differed for the two scan directions.The sample rate for measurements for each scan was high enough to prevent aliasing. At was short enough that changes in the interferometer pattern during a scan could be ignored and further, that only a small amount of aliasing occurred when analyzing a set of scans. When events occurred, however, At was not short enough to assume that there was negligible Fourier Power near the Nyquist Frequency of a set of interferometer scans.