An envelope of two approximations forms a plane wave coherent laser vibrometry calculation set that indicates
mechanisms of measured and simulated spectral "reduction." Path length differences modulate large spot size
continuous wave laser return leading to structural mode sensing (not a random signal issue). Calculations for
sine swept and multi-modal approximations show vibrating rectangular plates constrained on all edges have
return that varies substantially with low frequency vibration modes, providing modal recognition and ID not
available with 1-D modes (strips or bars).
A set of approximate theoretical equations for the Doppler response of monostatic radar signals due to slowly
pivoting objects are derived. The treatment is based on physical models extracted from the mechanical engineering
community. Potential applications include analysis of load-based vehicle classification and detection of biological
movements such as human joint rotations. Several example calculations are presented based on the resulting
theoretical formulas. These examples include Doppler calculations for notional first-order vehicle suspension
models and first-order human joint (arm/leg) rotation models. Each set of example calculations includes two sets of
notional radar parameters in order to provide insight into potential Doppler pivot detection capabilities as a function
of basic radar parameters such as frequency and PRF (pulse repetition frequency).
The physical objective is to create, for a time span of about an hour, an antenna reflector with an equivalent aperture diameter of about 300 kilometers, as shown in the last part of the introduction. To do this with the convex ocean surface requires use of ocean surface waves. The oweda system determines the surface wave source for a given reflectivity (from a floor slide to ship wakes). The most useful part of the oweda system is coordination of highly data intensive post processing issues involved with transient structural analysis. Transient analysis automation tends to hide details and provide too much data. OWEDA performs calculations and accumulate statistics during the analysis of the data so that extra storage is not necessary. The owedaState.c report takes far less space than one time step of data, S(n) equals (Theta) (n) and the operations run in tandem, T(n) equals (Theta) (n). The time complexity analysis shows how loose bounds on some processes can be overcome by tight bounds on others for an overall tight time complexity bound on the algorithm.
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