Military sea basing operations include mooring ships together offshore and transferring cargo and equipment between them. A newly developed Environmental and Ship Motion Forecasting (ESMF) System will facilitate these operations by providing predictions of ship motions in waves. Coherent forecasts of the ship motions are provided through remote sensing of the ambient waves and using these waves as input to a predictive ship motion simulation. Key technologies developed in support of the ESMF system include: a custom-built wave sensing radar; a least squares inverse wave retrieval algorithm; a ship motion model for performing rapid seakeeping simulations; and a robust peer-to-peer system architecture. The ESMF system was tested extensively in a demonstration aboard the R/V Melville with very good results, often achieving correlations of forecast-to-realized signals of better than 80% over 30 minute intervals.

A tomographic scheme is presented that ingests ocean acoustic measurements into an ocean model using data from bottom-mounted hydrophones. The short distances between source-receiver pairs (1-10 km) means arrival times at frequencies of 8-11 kHz are readily detectable and often distinguishable. The influence of ocean surface motion causes considerable variability in acoustic travel times. Techniques are presented for measuring travel times and removing the variability due to surface waves. An assimilation technique is investigated that uses differences in measured and modeled acoustic travel times to impose corrections on the oceanographic model. Equations relating travel time differences to oceanographic variables are derived, and techniques are presented for estimating the acoustic and ocean model error covariance matrices. One test case using a single source-receiver pair shows that the tomographic information can have an impact on constraining the solution of the ocean circulation model but can also introduce biases in the predictions. A second test case utilizes knowledge of a bias in a model-predicted variable to limit grid cells that are impacted by the tomographic data. In this case, using the tomographic data results in significant improvements in the model predictions without introducing any biases.

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This paper compares and contrasts the performance of cylindrical multimode hydrophones that can form first-and second-order cardioids. The basic theory of directional sensors (i.e., pressure-gradient hydrophones of order 0, 1, and 2) is presented along with an analysis of the directivity index as it pertains to first-and second-order cardioids. The theory of cylindrical multimode hydrophones is presented which relates the n=0, 1, and 2 circumferential modes to the pressuregradient having orders 0, 1, and 2. Electronic beam steering of second-order cardioids is also covered. A case study is presented on a cylindrical multimode hydrophone consisting of a radially-poled piezoelectric ring having four segments. Lastly a brief discussion is presented concerning the augmentation of the directivity index resulting from the physical aperture of the hydrophone.