A subaperture autofocus algorithm for synthetic aperture radar (SAR) partitions range-compressed phase-history data collected over a full aperture into equal-width subapertures.Application of a one-dimensional Fourier transform to each range bin converts each subaperture data set into a full-scene image (map). Any linear phase difference, or phase ramp, between a pair of subapertures expresses itself as cross-range drift in their maps.A traditional autofocus algorithm fits a polynomial to inferred equal-width phase ramps. If the true phase error function contains significant high-order components, then polynomial regression generates a poor estimate of the phase error functioa Instead of fitting a polynomial, we fit a sinusoidal function through the inferred phase ramps. An example with a degraded SAR image shows how a sinusoidal correction improves image quality.We compare lower bounds on mean squared error (MSE)for polynomial and sinusoidal parameterizations. Sinusoidal parameterization reduces MSE signiticantly for model orders greater than Eve.

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The speed and attenuation of sound in gassy marine sediments in the Mississippi delta area have been measured by means of small (1 to 500 mg) explosive charges buried 30 m below the mud line. The respective values obtained were 800 m/sec and 1.4 dB/kHz-m. Effective gas content was estimated to be approximately 0.06 percent.

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