Knowledge-aided Bayesian Rao and Wald tests for Radar Adaptive Detection in Heterogeneous Environment

摘要：

We resort to a Bayesian framework and design knowledge-aided (KA) Rao and Wald tests for radar adaptive detection based on the partially homogeneous model, which outperform their conventional counterparts in heterogeneous environment. Meanwhile, the coincidence of the proposed detectors is proved.

关键词： Knowledge-aided Radar adaptive detection Bayesian Rao test Wald test

作者: Yu Zhou Lin-rang Zhang

作者单位: National Lab. of Radar Signal Processing, Xidian University, Xi’an, China Mail address: National Lab. of Radar Signal Processing, Xidian University, 2 Taibai Rd., Xian Shaanxi 710071, China

会议类型: 国际会议

会议名称: 2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)

会议地点: 成都

会议语种:英文

页码: 481-484

在线出版日期: 2011-10-24（万方平台首次上网日期，不代表论文的发表时间）