摘要
复杂环境下多站多目标无源交叉定位存在虚假定位点问题,随着测向站数目和目标数目的增加,虚假点数量急剧增加,正确关联的难度增大。针对这一难题,提出了2种基于冗余信息的虚假点消除算法。通过有选择性地利用方位角或时差冗余信息进行数据关联,从而保证了在一定测向数据正确关联率的基础上,能够有效避免完全采用所有测向站的方位数据直接进行关联带来运算量大的问题。仿真证明了2种算法的有效性。基于时差冗余信息的虚假点消除算法由于利用了额外的时差冗余信息,在时差测量误差小于0.5 ms的情况下,其正确关联率均高于基于角度冗余信息的虚假点消除算法,更适用于时差测量精度较高、目标间距较小,而测向误差较大的场合。
The ghost problem exists in multi-DF station multi-target passive cross-location under complicated environment.The number of ghost is increased rapidly and the correct association is more difficult along with the increasing DF station and target.Aimed at this problem,two algorithms of eliminating ghost based on redundant information are presented.By associating data with azimuth angle or TDOA redundant information selectively,high computation burden can be avoided effectively when associating directly with azimuth angle data of all DF stations,based on ensuring certain association probability.Computer simulations show that these two algorithms are effective.Because of using additional TDOA redundant information,the correct association probability of eliminating ghost algorithm based on TDOA redundant information is higher than that of eliminating ghost algorithm based on azimuth angle redundant information when the TDOA error is lower than 0.5ms.The eliminating ghost algorithm based on TDOA redundant information is more adapted to the occasion with high TDOA precision、low space between targets,and big DF error.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2011年第1期46-50,共5页
Journal of Air Force Engineering University(Natural Science Edition)
基金
国家"863"计划资助项目(2007AA111008A1)
安徽省自然科学基金资助项目(070412053)
