We present an automated implemented and computationally efficient method for smoothly morphing of point set surface. In the issue, corresponding between the surfaces is difficult for point set surface without any topological information. To overcome this, the method is guided by registration and warp functions, then the intermediate surfaces are constructed depend on only the local geometric information expressed by the point locations in 3D space. To reduce the distortion of the intermediate shapes, the distance metric between points is defined, and the algorithm optimally matches the points in the two models. The automated method provides the animator with a technique that can be used to create a set of models forming a smooth transition between pairs of a given sequence of keyframe models. The advantage of the new approach is that the capability of morphing between objects having a different topological without any intervene of animators.

UAVs are widely used for all-weather, round-the-clock security inspections in urban and industrial areas. However, pure visible-light systems fail at night or in adverse weather conditions, while pure infrared methods are limited by thermal noise, low spatial resolutions, and high false alarm rates. Multispectral images render the task of object detection highly reliable and robust by providing complementary target feature information. This study suggests a frequency-based cross-attention transformer (FCAT) for multispectral object detection as a solution to this issue. This approach collects cross-modal complementary characteristics, effectively learns and integrates global contextual information via the cross-attention mechanism, and greatly increases multispectral object detection accuracy. At the same time, spatial-domain features are mapped to the frequency domain via the Fourier transform, and the scaled dot product attention is estimated via element-wise product operations, which break through the limitation of traditional spatial-domain matrix multiplication and effectively reduce the computational cost of the model. Additionally, this study independently builds a multi-scene multi-time climate visible–infrared dataset (OPVM-VIRD), which contains 20,025 target instances, to address the issue of the lack of all-weather cross-spectral data in object detection tasks from the perspective of UAVs. Experimental findings from the OPVM-VIRD, M3FD, and FLIR datasets demonstrate that our proposed approach outperforms prevailing state-of-the-art multispectral object detection algorithms on public benchmarks, while the FCAT model achieves an mAP50 score of 94.7% on our custom-built dataset—10.8% higher than ICAF. At the same time, the number of FCAT parameters is 85.26 M, which is significantly lower than that of mainstream models, such as ICAF. Therefore, the FCAT is a change detection strategy with strong model generalization abilities, and it has important application value in the all-day and all-weather security patrol of cities and industrial parks carried out by UAVs.

In order to solve the problem that the air-to-ground data transfer rate is much lower than the radar data rate, the onboard system is commonly used for storing the airborne radar data. However, there are two main problems in the data storage using the traditional file management method. The first is that the frequent data updating of the file allocation table (FAT) and the file directory table (FDT) cause a high frequency of address jumps among the discontinuous areas, which leads to a long response time. The second is that the updating frequencies of the FAT, the FDT and the data region are seriously inconsistent, which results in uneven wear of the three areas. To solve these two problems, a file management method, which optimizes the data writing in the three areas of the FAT, the FDT and the data region, is proposed in this study. An actual measurement is carried out on a data storage system of the airborne radar using the proposed file management method. The result shows that the proposed method significantly reduces the updating frequency of FAT and FDT, and achieves the wear levelling of file area and data region.

This paper presents crucial techniques for the realization of frequency modulated continuous wave synthetic aperture radar (FMCW SAR). To begin with, the principle of FMCW SAR is reviewed in detail, then digital unit is focused to present. The digital unit includes real-time signal processor, mass data storage. Real-time imaging algorithm and its mapping to digital signal processor (DSP) as well as the SAR video formation are also proposed. Finally, beneficial results of the flight trial are presented to show the performance of the FMCW SAR system.