Improving spatial resolution is a crucial issue in medical ultrasound. One of the improving methods is the post-processing of the received ultrasound RF signal. In the present paper, we propose a design method for a noise-robust broadband filter based on the singular value decomposition of the received RF signal. To design a noise-robust filter, we propose a logical method to determine the optimal truncated order of singular values, which was validated by applying the filter to noise-contaminated signals. Furthermore, the proposed filter applied to the wire phantom resulted in a better axial resolution than that obtained without the filter and with our previously designed Wiener filter.

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In Japan, "i-Construction" is promoted to improve the productivity of the construction industries by utilizing Information and Communication Technology (ICT). In particular, estimation of sediment volume at construction sites is highly demanded, for example, in order to pre-order the number of trucks correctly. In current construction sites, the sediment volume is calculated based on conventional terrain measurement methods by using special survey instruments such as a total station. These kinds of methods, however, need a lot of time and manpower. In this paper, we propose a method that estimates sediment volume more easily from three-dimensional (3D) pointcloud data obtained by only sensors installed on a backhoe. Our system is consisted of a LiDAR for 3D shape measurement and a tracking sensor for movement measurement by visual odometry. To obtain dense point clouds, the LiDAR of our system is rotative on a pan-tilt (PT) unit, whose relative relationship between both coordinate systems of LiDAR and the PT unit is estimated beforehand by our calibration method. At construction sites, the backhoe mounting our sensing system measures a ground surface from multiple viewpoints during movement, and a batch of 3D pointclouds of a wide range is integrated by a registration technique. From the whole pointcloud, the sediment volume on the ground can be estimated. In an outdoor experiment, we validated effectiveness of our proposed method by evaluating the accuracy of the estimation results.

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