Large-amplitude atmospheric flows past mountain ridges are investigated. The flows are assumed to be steady and two-dimensional. Diffusive and viscous effects are neglected but static compressibility is taken into account.The larger part of the investigation is devoted to the study of waves in the lee of mountain ridges. The major contribution consists in the treatment of the large-amplitude motion. The flows are governed by an equation which turns out to be linear for certain upstream conditions. These conditions impose some restrictions on the wind profile and stratification of the entropy and specific energy far upstream. However, flow patterns representing realistic upstream conditions have been obtained.A comparison between a compressible flow and an incompressible flow with equivalent upstream conditions is included.
Orbit determination and prediction programs are needed to generate ephemerides for the satellite. Orbit determination is from tracking data consisting of angles only, and is based on a modified version of a method by R. E. Briggs and J. W. Slowey of the Smithsonian Institution. Trends in the data due to perturbations from a Keplerian orbit are removed before this process, and estimates of the orbital elements from individual passes are combined statistically to produce refined estimates. Ephemeris calculation is by a semi‐analytic method in which deviations from a Keplerian orbit are obtained by integrating the perturbing forces. The programs to implement these procedures have been written for both the IBM 7090 and the IBM 1620 computers.
Adaptive focusing is an array processing scheme in which the receiver is designed for adaptive detection of localized sources under conditions where the signal field distribution across the array aperture is distorted from that of a plane wave, but is unknown a priori. Complex propagation conditions, including slow medium fluctuations, coupled with source motion render the signal field non-Gaussian. This property is brought into play in the design of the detector as a maximum-likelihood receiver which actually exploits the slowness of the acoustic channel changes. The problem is to detect the signal in a spatially white Gaussian noise field. The receiver utilizes the spatial structure of the signal as it manifests itself in the maximum eigenvalue of the data sample covariance matrix. Temporal stability of the field distribution and signal-to-noise ratio are important parameters. These are incorporated into a Monte Carlo simulation which shows that for stable signals at threshold level in the output of a conventional beamformer degraded by 5 dB, adaptive focusing can perform within a fraction of 1 dB of a hypothetical ideal beamformer for which the signal field is known a priori. Decreased temporal stability coming about as a result of, say, increased source motion necessarily has an adverse affect on performance.
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