High resolution wide swath (HRWS) imaging and ground moving target indication (GMTI) are similar in terms of system architecture and are based on a multi-channel system in the azimuth direction. However, in order to achieve their respective performance requirements, the HRWS SAR requires a lower pulse repetition frequency (PRF), and the GMTI system requires a relatively higher PRF. In consideration of this contradiction, parameters of the moving target are introduced into the reconstructed filtering vector constructed by each signal reconstruction algorithm, so that the HRWS imaging of the moving target can be realized. In this paper, considering the characteristics of the Relax algorithm, a motion-adapted signal reconstruction algorithm is proposed, and the iterative process of the new method is described in detail. This method can perform GMTI on moving targets with a lower PRF without changing the PRF of the HRWS SAR system. By the simulation of point target echo and comparing with the traditional signal reconstruction algorithms, the reliability and effectiveness of the new method are verified.
The wood grade used for Chinese zither panels is primarily determined through an artificial experience method, and the number of related practitioners is decreasing annually. In this study, a method using an improved BP neural network is proposed to assess the wood grade for Chinese zither panels. Abnormal spectral samples were first removed based on the Mahalanobis distance method. Normalization and Savitzky Golay second derivatization were applied to the remaining data set. According to the spectral peak, the spectral data were divided into three bands, which were applied to the model proposed in this paper, and the most critical spectral region for judging the wood grade of Chinese zither panels was obtained. Through principal component analysis, the appropriate feature variables were selected and applied to the experimental model for an analysis to reduce the calculated amount in the experiment. When the number of principal components was 6, the classification accuracy of unknown samples was 96.7%. Compared with the PLS model, the proposed model is more robust and accurate and has fewer losses. The experimental results indicated that the proposed method effectively identifies the wood grade used in Chinese zither panels.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.