Li Yu-Hui, Ouang Shan, Jin Liang-Nian, Liao Gui-Sheng. Target Shape Imaging Algorithm with an Envelope of Ellipses for UWB-TW Pulse Radars[J]. Journal of Electronics & Information Technology, 2014, 36(7): 1532-1537. doi: 10.3724/SP.J.1146.2013.01419
Citation:
Li Yu-Hui, Ouang Shan, Jin Liang-Nian, Liao Gui-Sheng. Target Shape Imaging Algorithm with an Envelope of Ellipses for UWB-TW Pulse Radars[J]. Journal of Electronics & Information Technology, 2014, 36(7): 1532-1537. doi: 10.3724/SP.J.1146.2013.01419
Li Yu-Hui, Ouang Shan, Jin Liang-Nian, Liao Gui-Sheng. Target Shape Imaging Algorithm with an Envelope of Ellipses for UWB-TW Pulse Radars[J]. Journal of Electronics & Information Technology, 2014, 36(7): 1532-1537. doi: 10.3724/SP.J.1146.2013.01419
Citation:
Li Yu-Hui, Ouang Shan, Jin Liang-Nian, Liao Gui-Sheng. Target Shape Imaging Algorithm with an Envelope of Ellipses for UWB-TW Pulse Radars[J]. Journal of Electronics & Information Technology, 2014, 36(7): 1532-1537. doi: 10.3724/SP.J.1146.2013.01419
The target shape imaging algorithms receive great attention in applications of Ultra WideBand Through Wall (UWB-TW) radar, because it overcomes the shortcomings of real-time imaging and image quality in traditional Back Projection (BP) imaging algorithms. The classical SEABED and Envelope algorithms are typical target shape imaging algorithms, which have still some defects such as poor anti-noise capability and imaging accuracy. This paper presents a target shape imaging algorithm with the envelope of ellipses for the bistatic UWB-TW radar. The ellipse model regarding a target boundary is established by analyzing the geometry relationship between the target boundary and the coordinates of antennas. With this model, the target boundary can be expressed as a boundary of a union and an intersection set of these ellipses to achieve the target shape imaging, which derives from their mapping relationship. The results of numerical simulations and experiments show that the proposed algorithm can improve the imaging accuracy and the capability of anti-noise, leading to the better performance of through-wall imaging.