A method is proposed to fuse the information from two navigation systems whose relative position is unknown, but where there exists an upper limit on how far apart the two systems can be. The proposed information fusion method is applied to a scenario in which a pedestrian is equipped with two foot-mounted zero-velocity-aided inertial navigation systems; one system on each foot. The performance of the method is studied using experimental data. The results show that the method has the capability to significantly improve the navigation performance when compared to using two uncoupled foot-mounted systems. / <p>QC 20121221</p>

Microcirculation plays an essential and functional role in the human body and reflects people’s physical status with microscopic detail. For peripheral microcirculation, nail-fold microscopy is a convenient and non-invasive tool since the capillaries in the nail-fold are well arranged and parallel to the skin, which is advantageous for microscopic visualization. Further, nail-fold capillaroscopy information is widely useful. In diagnosis, various diseases such as systemic lupus erythematosus and cardiac diseases can be detected and predicted at an early stage with capillaroscopic patterns and capillary blood velocity. For medical experiments, capillaroscopic information can be used to monitor drug effects and other medical treatments. Though nail-fold capillaroscopy is of significant convenience, it is not widely used. Currently, there is no commercial product with those functions due to the limitations of the equipment, such as microscope resolution and lens magnification. Besides, there is no concrete standard for measurement procedures or objective rules for quantitive data analysis. This thesis proposes a reliable system estimating nail-fold capillary blood flow velocity. It is tested and applied to the microscope from Optilia. In this work, various image and video processing methods are discussed in detail and tested in practice. Taking computational load and equipment limitations into consideration, the system applies frame enhancement and video stabilization. It uses dual-window and correlation methods to estimate the velocity of red blood cells in nail-fold capillaries. In order to test the reliability of the system, the obtained results are compared with the outcome of direct observation. It turns out that the chosen methods employed in the system provide rational results within 5 pixel bias.

The Synthetic Aperture Radar (SAR) algorithm processes multiple radar returns from the target space to generate a single high-resolution image. Targets moving through the target space during the capture sequence will appear distorted on the final image. In addition, there is no velocity information that is calculated as part of the processing. The objective of this thesis is to develop techniques to determine the azimuth and range velocities of moving objects in the target space in the early stages of SAR processing. The typical SAR processing steps are Range Compressed, Range Doppler, and final image generation. The range velocity of a target can be determined after the Range Compression stage, and the azimuth velocity can be determined after the Range Doppler image is created. Calculating the velocity of a target without performing all the steps of the SAR process allows such information can be obtained quicker than the final image. This work is done as part of Cal Poly’s SAR Automatic Target Recognition (ATR) project, sponsored by Raytheon Space and Airborne Systems Division and headed by Professor John Saghri. The simulations performed as part of this thesis are done in a MATLAB simulation environment implementing a two-dimension SAR target space, first introduced in Brian Zaharris’ thesis. This work has expanded on this environment by introducing point target azimuth and range velocity detection.