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Coherent Change Detection (CCD) detects micro changes in a scene using phase coherence of SAR images before and after a change. It is difficult for conventional CCD method to distinguish low coherence interference region from objective change region because of a single detection scale. Multi-band SAR target detection in a multiscale way develops variable coherent representation according to the diversity of electromagnetic wave penetration, target structure, and change magnitude. In this paper, a multi-band CCD method is proposed. Firstly, the CCD images of every band were acquired; secondly, the detected scene was classified on the basis of coherent representation of targets in each single band using improved Expectation-Maximization (EM) algorithm; thirdly, the objective change class in each single band was selected by a few supervised samples; lastly, multi-band fusion CCD image was acquired by the use of Dempster-Shafer (DS) evidence theory. This multi-band CCD result can eliminate low coherent interference in each single band and decrease false alarm probability. The method is validated by L- and P-band repeat-pass SAR images acquired before and after change. Results and index parameters demonstrate the validity and correctness of the proposed method.

The Coherent Change Detection (CCD) measures the phase difference in repeat passes in SAR images and is a powerful technique for detecting minute changes between two synthetic aperture radar images taken at different times. Nevertheless, the CCD has two problems. These are the high false-alarm rates and threshold selection. To deal with these problems using the likelihood change, this study makes two improvements. First, the model parameters are optimized by the maximum likelihood method and more accurate and robust parameters are obtained by using the sliding window in the neighborhood operations. Second, the automatic change in the threshold method is proposed based on the histogram characteristics of different data. The processing of real data suggests that the proposed method is effective in detecting minute changes.

Geometric positioning accuracy is an important technical indicator for Synthetic Aperture Radar (SAR) in the geomatics domain. Airborne SAR is an important trend in SAR technology due to its advantages of high flexibility, high resolution, and low cost. Motion error and undulating terrain are the major sources of airborne SAR geometric positioning. In this paper, we consider the SAR imaging principle and imaging geometry to carefully examine the mechanism of geometric positioning error caused by the coupling of motion error and terrain fluctuation. Therefore, we propose a fast geometric precision correction method and verify the validity and effectiveness of the proposed method based on simulation results and experimental data.

In order to improve tracking performance of the approach, a new adaptive tracking algorithm of group maneuvering targets was presented. In the estimation of group centroid kinematic state, the deviation between the prediction value and estimation value of centroid speed was used to adjust the covariance matrix of process noise based on modified current statistical model, and a fading factor of strong tracking filter was used to adjust the state-estimation error covariance adaptively. In the estimation of group extension state, the prediction parameter of extension was calculated by using a fuzzy reasoning method, which had taken the deviation between the prediction value and estimation value of the corresponding elliptical area and the change ratio of deviation as the input of the fuzzy controller. Lastly, a method to judge split-off maneuvering of group targets was offered. Simulation results show that, compared with the existing methods, the proposed algorithm can obtain a better adaptive tracking performance in maneuvering scenarios, and detect the split-off maneuvering effectively. [ABSTRACT FROM AUTHOR]

Three-dimensionally controlled cell-assembly technique makes fabricating tissues and organs in vitro to be possible. However, for real tissues and organs with complex structure and various cells, fabricating tissues and organs in vitro need a technique that could assemble and locate multi cells and materials precisely in the space. Facing the needs of multi-cell assembly, we designed a mixer nozzle and the matching pulse switching circuit which based on the single-nozzle cell assembly system, and developed a multi-cell-assembly system. We also carried out some assembly experiments with this system using materials that were similar to the multi-component extracellular matrix materials. The results demonstrated that the system could assemble various cells and materials into three-dimensional inhomogeneous structures precisely.

Since there is a clinical need for the tissue-engineered vascular graft (TEVG), fabricating the vascular scaffold individually appears to be necessary. In this work, we have developed the traditional tubular scaffold and branch vascular scaffold utilizing low-temperature deposition manufacturing (LDM) technology. Then different tubular scaffolds were fabricated by changing the processing parameters, and the morphological properties of the scaffolds were assessed. The scaffolds reproduced the structure of 3D vascular model accurately. Wall thickness of the scaffold increased with the increase of velocity ratio (V(L)/V(s)) and nozzle temperature, and both the micropore size and wall roughness were positively correlated with the nozzle temperature. However, the porosity was barely affected by the nozzle temperature. This approach, fabricating vascular scaffold with special structure and appearance features via LDM technology, is potential for the individual fabrication of vascular scaffold.