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Yun Z.,China Petroleum Pipeline Engineering Corporation | Guan Z.,Soda Plant and Shandong Haihua Co. | Li W.,ASIT Co.
Proceedings of the 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2016 | Year: 2016

Non-uniform pulse repetition interval (PRI) provides radar system strong electronic counter-countermeasures (ECCM) ability under electronic countermeasure (ECM) environment. For synthetic aperture radar (SAR) system, the effectiveness caused by non-uniform pulse repetition interval (PRI) on SAR imaging and deception jamming has not yet been illustrated comprehensively. And like the other radar systems, the non-uniformly sampled SAR data should not be processed in the traditional way. Analysis of imaging, countermeasures resistance and reconstruction algorithm for non-uniform PRI SAR data is discussed in this paper. © 2016 IEEE.

Yu X.-T.,ASIT Co. | Zhang L.,ASIT Co. | Chen G.-F.,Chinese People's Liberation Army | Zhou F.,ASIT Co. | Xu Z.-S.,ASIT Co.
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | Year: 2010

There exits a large error in accelerometer static model when using linear approximate model to identify it. Support vector regression (SVR) has good regression performance, especially in small-sample, nonlinear and high-dimensional feature space. So a new model identification method based on SVR is proposed to identify the accelerometer static model. Particle swarm optimization (PSO) algorithm is adopted to optimize the parameters of SVR, which cost less time compared with the trial-and-error method. The 12-position static rolling test of Quartz flexure accelerometer is made using precision optical dividing head. The experiment results demonstrate that the identification accuracy of static model by the proposed method is approximately more than double the one by the least square method.

Yu X.-T.,ASIT Co. | Zhang L.,ASIT Co. | Guo L.-R.,ASIT Co. | Zhou F.,ASIT Co. | Yu H.,ASIT Co.
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | Year: 2011

Environment temperature is an important factor for the precision of accelerometer. The mechanism of temperature's influence on bias and the scale factor of accelerometer is analyzed. An identification method for the temperature model of bias and scale factor of quartz flexure accelerometer is proposed which is based on least squares wavelet support vector regression (LS-WSVR). The experiments under different temperature conditions were conducted to verify the good regression performance of the proposed LS-WSVR, and the experimental data was used as the training data of LS-WSVR. The experiments of temperature with fixation point were conducted, and the experiment results show that the accuracy of accelerometer compensated with LS-WSVR model is better than that of using least square model or having no compensation.

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