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Xu Z.,University of Adelaide | Xu Z.,Radar and Avionics Institute of AVIC | Kaufmann T.,University of Adelaide | Fumeaux C.,University of Adelaide
IEEE Microwave and Wireless Components Letters | Year: 2014

A shielded stripline structure made from textile materials is introduced as a wearable flexible transmission line for broadband operation. The stripline with a total height of 3.2 mm consists of a foam substrate and silver fabric conductors. For shielding purpose, the structure is truncated on its sides at a total width of 20 mm using embroidered via walls made from conductive thread. The impedance bandwidth and propagation characteristics are investigated through simulation and experiment, demonstrating that the textile stripline can work efficiently and reliably from dc to 8 GHz. Moreover, it is shown that the textile stripline is robust in terms of propagation characteristics, as even when bent up to 90° and 180° it can maintain consistent propagation properties in the whole operation band. A further advantage of the structure is the simple fabrication, arising from the low sensitivity of the structure to width and height tolerances, as well as to the accuracy of the feeding method. Finally, it is shown that the low-loss radio frequency foam substrate material can be replaced with low-cost clothing felt without significant detrimental impact on the efficiency. © 2001-2012 IEEE. Source

Luoding J.W.,Radar and Avionics Institute of AVIC
IET Conference Publications | Year: 2013

One kind of CFAR named VI-CA/OS-CFAR and based on variable test statistics is proposed in this paper. By calculating two variable test statistics including normalized square deviation and mean ratio real-timely, current clutter environment is judged automatically and different kinds of CFAR detectors are selected. Theoretical analysis and verification results by flight data shows that this detector has good performance and robustness in homogeneous clutter, multiple jamming targets or clutter edge environment faced by GMTI in actual use. Source

Liu M.,Zhejiang University | Qi D.,Zhejiang University | Zhang S.,Zhejiang University | Qiu M.,University of Kentucky | Zheng S.,Radar and Avionics Institute of AVIC
Neurocomputing | Year: 2011

This paper is concerned with the problem of multi-sensor optimal H∞ fusion filtering for a class of discrete-time stochastic intelligent systems with missing measurements and time delays. This discrete-time intelligent system model, which is composed of a linear dynamic system and a bounded static nonlinear operator, presents a unified description of delayed or non-delayed intelligent systems composed of neural networks and Takagi and Sugeno (T-S) fuzzy models, Lur'e systems, and linear systems. The missing measurements from multi-sensors are described by a binary switching sequence that obeys a conditional probability distribution. We aim to design both centralized and distributed fusion filters such that, for all possible missing observations, the fusion error is globally asymptotically stable in the mean square, and the prescribed H∞ performance constraint is satisfied. By employing the Lyapunov-Krasovskii functional method with the stochastic analysis approach, several delay-independent criteria, which are in the form of linear matrix inequalities (LMIs), are established to ensure the existence of the desired multi-sensor H∞ fusion filters. An optimization problem is subsequently formulated by optimizing the H∞ filtering performances, which is described as the eigenvalue problem (EVP). Finally, simulation examples are provided to illustrate the design procedure and expected performance. © 2011 Elsevier B.V. Source

Li X.,Xidian University | Feng D.,Xidian University | Liu H.-W.,Xidian University | Luo D.,Radar and Avionics Institute of AVIC
IEEE Transactions on Aerospace and Electronic Systems | Year: 2014

In this paper, we address the dimension-reduced space-time adaptive processing (STAP) techniques for ground clutter suppression in airborne radar from the viewpoint of approximation theory. The weights in the optimum STAP technique can be naturally expressible as the weight matrix. An efficient dimension-reduced space-time adaptive clutter suppression (STACS) algorithm based on lower-rank approximation to weight matrix is established, which finds a set of space-time separable filters to approximate the optimum STAP processor. By exploiting a lower-rank approximation to weight matrix, we make the quadratic cost function used in the classical optimum STAP processor be converted into a biquadratic cost function. To seek a minimum point of the biquadratic cost function, this paper develops an efficient multistage bi-iterative algorithm and the corresponding multistage dimension-reduced technique with a modular structure, where each stage finds an orthogonal component for approximating to the weight matrix. The effectiveness of the STACS algorithm is tested via several experiments. © 1965-2011 IEEE. Source

Wang X.,Nanjing University of Aeronautics and Astronautics | Pan M.,Nanjing University of Aeronautics and Astronautics | Jiang X.,Radar and Avionics Institute of AVIC | Liang Z.,China Institute of Metrology
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | Year: 2011

LFM (linear frequency modulated) signal is broadly used in radar system due to its good time-frequency concentration ability. However, radar range measurement precision and distinguishing ability tightly relies on the linearity of LFM signal. In order to simulate LFM radar echoes precisely, linearity calibration has to be carried out for the LFM signals produced by radar target simulator. This paper proposes a novel LFM signal linearity calibration method based on wavelet transformation for radar target simulator. The method has been verified with mass lab data acquired from different radar target simulators, and the calibration accuracy is better than 0.1%, which proves the effectiveness of the method. Source

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