Two-dimensional angular optical scattering (TAOS) is recorded for several particle shapes and configurations. A lens is used to collect a large solid angle of the light and transform the angular profile into a planar distribution according to the Abbé sine condition. Qualitative agreement is found between experiment and theory for the TAOS from spheroids having the same aspect ratio but different sizes. A distinctive irregular island structure is observed in the TAOS from clusters of Bacillus subtilis spores and polystyrene latex spheres. The density per solid angle of these islands is found to increase with cluster diameter.
The U.S. Army Research Laboratory (ARL) is developing an acoustic target classifier using a backpropagation neural network (BPNN) algorithm. Various techniques for extracting features have been evaluated to improve the confidence level and probability of correct identification. Some techniques used in the past include simple power spectral estimates (PSEs), split-window peak-picking, harmonic line association (HLA), principal component analysis (PCA), wavelet packet analysis,1'2'3'4 and others. In addition, improved results have been obtained when data are combined from other sensors co-located with the acoustic sensor. A three-axis seismic sensor has been configured as part of an acoustic sensor array that ARL uses on typical field experiments, with data collected and sampled simultaneously.The PSE, HLA, and shape statistic feature data are extracted from a group of vehicles and then split into testing and training files. The training file typically consists of 75 percent of the data set, and the performance of the trained neural network is evaluated with the remaining test data. Cross-validation is performed with vehicle data collected at different times of day and under various conditions. Results of the neural network from a few of the feature extraction algorithms under evaluation and from the fusion of the acoustic and seismic sensor data are presented.
Poly(ethylene glycol) [PEG] microparticles were doped with ceramic or latex nanoparticles in order to examine
domain-size and refractive index effects of nanometer-sized guest inclusions on two-dimensional diffraction
patterns. Composite microparticles were examined for different inclusion sizes and polymer/nanoparticle weight
ratios in order to determine the size and number-density threshold of detection for guest nanoparticles within
the polymer host as indicated by fringe distortion in 2-D angular scattering. PEG host particles having a 10
μm (nominal) diameter were formed with three different guest nanoparticles (Al2O3, TiO2, and latex nanospheres
with respective sizes of 46, 29, and 14 nm). For the ceramic nanoparticle inclusions, distortion was observed
at relative guest−host weight fractions of 5−10%. For the 14 nm latex inclusions, no distortion was observed
at any weight fraction. A perturbation method was used to simulate the effect of nanometer-size inclusions
on 2-D optical diffraction from polymer host microparticles and to suggest how the distortions should vary
with inclusion size, refractive index, and number.
A technique has been devised that uses a genetic algorithm (GA) to address the multi-scan assignmentproblem in multitarget tracking. The problem is recast in the form of a scheduling problem, where the GA searches the space of possible orderings of detections, and a greedy heuristic is used to make the associations f o r a particular ordering. The resulting tracker can operate in either batch or continuous mode. In the continuous mode, a single population of hypotheses evolves on afitness landscape that changes with each new scan of data.
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