Performance analysis on improved PDA AI for moving target tracking |
| |
| Authors: | HUANG Yang fan LI Zheng zhou and TANG Ju |
| |
| Institution: | Communication Engineering College of Chongqing University, Chongqing 400044, P. R. China;Communication Engineering College of Chongqing University, Chongqing 400044, P. R. China;Communication Engineering College of Chongqing University, Chongqing 400044, P. R. China;Chongqing University of Arts and Sciences , Chongqing 610209, P. R. China |
| |
| Abstract: | Aim at the problem that the EO imaging tracking system is inconsistent with the model of probabilistic data association with amplitude information (PDA AI), which supposes that the greater the amplitude value is, the greater the probability of being the tracked target will be, a modified PDA AI (MPDA AI) is presented . Based on the fact that the amplitude and the motion of the interested target are consistent in a short period, the MPDA AI models the amplitude information and the motion information of the target as well as their consistency with Markov stationary signal to analyze the association procedure of motion and amplitude. The lower bounds of Cramer Rao estimation error for PDA AI and MPDA AI are calculated and discussed in detail. The theoretical analysis and experimental results show that estimating the target motion with the MPDA AI will be more accurate and more reliable than estimating with the original PDA AI. |
| |
| Keywords: | dim small target tracking probabilistic data association filter amplitude information Cramer Rao lower bound |
|
| 点击此处可从《保鲜与加工》浏览原始摘要信息 |
| 点击此处可从《保鲜与加工》下载免费的PDF全文 |
|
