Polarimetric Enhancements to Electro-Optical Aided Navigation Techniques

Navigation in indoor and urban environments by small unmanned systems is a topic of interest for the Air Force. The Advanced Navigation Technology Center at the Air Force Institute of Technology is continually looking for novel approaches to navigation in GPS deprived environments. Inertial sensors have been coupled with image aided concepts, such as feature tracking, with good results. However, feature density in areas with large, flat, smooth surfaces tends to be low. Polarimetric sensors have been used for surface reconstruction, surface characterization and outdoor navigation. This thesis combines aspects of some of these algorithms along with a realistic, micro-facet polarimetric model and a Kalman filter approach to determine surface structure and platform orientation in an indoor environment. A series of graphical user interfaces were developed to estimate surface material parameters. A more complex simulation software package was used to estimate camera attitude. A physical polarimeter was also designed and built to test the algorithms in a realistic environment. An improvement in attitude estimation of up to 50% was demonstrated

Informational limits in optical polarimetry and vectorial imaging

Light has provided the means to learn and gather information about the physical world throughout history. In a world where science moves to smaller scales and more specialised problems however, the boundaries of current technology are continually challenged, motivating the search for more sophisticated systems providing greater information content, sensitivity and increased dimensionality. Utilising the vectorial nature of light presents a promising avenue by which to meet these growing requirements. Polarisation can, for example, be used to transmit information, or alternatively, changes in polarisation induced by an object allow study of previously neglected material properties, such as birefringence and diattenuation. Central to this thesis is thus the characterisation and exploitation of the opportunities afforded by the electromagnetic (i.e. vectorial) nature of light. To this end the work follows three running themes: quantification of polarisation information; formulation of simple propagation tools for electromagnetic waves; and development of specific polarisation based optical systems. Characterising the informational limits inherent to polarisation based systems reduces to considering the uncertainty present in any observations. Uncertainty can, for example, arise from stochastic variation in the polarisation state being measured, or from random noise perturbations upon detection. Both factors are considered and quantified here. Development of vectorial optical systems does, however, pose significant difficulties in modelling, due to mathematical complexity and computational requirements. A number of new tools are hence developed, as prove applicable to a wide variety of applications. Examples are naturally given. To illustrate the potential of polarisation based systems, specific current topics are discussed; namely the growing demand for data storage, and single molecule studies. It will be shown that polarisation, can not only be used to multiplex information in data pits on optical media, but also to allow full 3D study of single molecules. Factors pertinent to such studies are studied in detail

3d surface reconstruction by combination of photopolarimetry and depth from defocus

Abstract. In this paper we present a novel image-based 3D surface reconstruction technique that incorporates reflectance, polarisation, and defocus information into a variational framework. Our technique is especially suited for the difficult task of 3D reconstruction of rough metallic surfaces. An error functional composed of several error terms related to the measured reflectance and polarisation properties is minimised by means of an iterative scheme in order to obtain a 3D reconstruction of the surface. This iterative algorithm is initialised with the result of depth from defocus analysis. By evaluating the algorithm on synthetic ground truth data, we show that the combined approach strongly improves the accuracy of the surface reconstruction result compared to techniques based on either reflectance or polarisation alone. Furthermore, we report 3D reconstruction results for a raw forged iron surface. A comparison of our method to independently measured ground truth data yields an accuracy of about one third of the pixel resolution.