A novel method to realise a single-feed circularly polarised (CP) microstrip antenna with wide beamwidth and axial-ratio (AR) beamwidth is investigated. Two diagonal metal walls are put at the diagonal sides of the microstrip antenna. The diagonal metal walls can excite the orthogonal radiation fields with the same amplitude and 90°phase difference on the radiating patch for CP with wide beamwidth and AR beamwidth. Some parameters which effect on the performances of the antenna are studied. The simulated and measured results of the reflection coefficients, radiation patterns and AR radiation patterns are presented. The 3-dB beamwidths of the right-hand CP (RHCP) radiation patterns in the xoz-plane and the yoz-plane are 105°and 157°, respectively. The 3-dB AR beamwidths of the RHCP radiation patterns in the xoz-plane and yoz-plane are 100°and 155°, respectively. Good CP characteristics of the new structure antenna have been obtained in the whole operating frequency band.
The Support Vector Data Description (SVDD) method for anomaly detection in hyperspectral imagery solved the problem of large numbers of false alarm in general detection methods based on statistical theory due to the Gaussian and homogeneous assumptions of background, but the background samples are selected randomly in SVDD. The active learning provides an effective sample selection method, therefore this paper presents Active Learning Support Vector Data Description (ALSVDD) method which is used to detect anomalies in hyperspectral imagery combing with neighboring clustering segmentation. ALSVDD method uses optimized minimal hypersphere to express the background tightly and distinguish function to detect anomalous pixels, which takes full advantage of the spatial and spectral information of the hyperspectral imagery. The method reduces the number of samples that is needed in the process of the algorithm and avoids the interference of possible anomalies in background. The experiments on the simulation data and AVIRIS data show the validity, efficiency and practicability of the proposed method which greatly reduces the computation complexity and false alarm rate in detecting anomalies in hyperspectral imagery.
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