%0 Journal Article
%T Cramér-Rao lower bounds for stochastic-bias discrete-time system with incomplete measurements<br>不完全量测下随机有偏离散系统的Cramér-Rao下界
%A LIU Rui
%A QI Guo-qing
%A CHEN Li
%A SHENG An-dong
%A <br>刘锐
%A 戚国庆
%A 陈黎
%A 盛安冬
%J 控制理论与应用
%D 2010
%I 
%X A modified recursive Cramér-Rao lower bound(CRLB) of the statistical estimation error variance is derived for the state estimation with incomplete and stochastic-biased measurement sequences. Firstly, a mathematical model of the discrete-time system with incomplete and stochastic-biased measurements is built; and then, the enumeration CRLB and the statistical CRLB are derived, respectively. The proposed statistical CRLB is a lower bound of the enumeration CRLB, but its calculation complexity is far lower than that of the enumeration CRLB. Simulation is performed in an optical-electrical tracking system with pre-specified detection probability and biased occurrence probability.
%K 状态估计
%K 不完全量测
%K 随机有偏
%K Cramér-Rao下界
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=7C9CB9191551047987A49B14CF9B1B4B&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=DF92D298D3FF1E6E&sid=8B6586F75D2B256A&eid=796A97DD793AE4A8&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=12