摘要
精确无源移动目标定位是隧道、矿井巷道等复杂地下空间人员安全、灾后及时施救的关键技术之一。提出一种基于TOA/DOA参数估计的隧道高分辨率无源移动目标定位方法。鉴于隧道巷道内静物回波信号的多径较多且衰落严重,基于特征值分解的零陷设计思路给出适合低信噪比条件下的最小范数强干扰抑制方法,抑制直达波和静物回波多径干扰信号,检测接收移动目标反射波;同时,为了克服隧道内的纳秒级密集多径和背景噪声,提出基于互高阶谱的RMCHS参数估计算法(Root Min-norm based on Cross High-order Specture,RMCHS),在低信噪比条件下进行高分辨率的TOA/DOA参数估计,从而实现基于TOA/DOA参数估计的隧道高分辨率无源移动目标定位。仿真实验表明,提出的强干扰抑制方法和RMCHS算法在隧道/巷道环境下有很强的鲁棒性,显著优于比较算法,减小了噪声和纳秒级密集多径对算法性能的影响。
The accurate passive moving target localization is one of the key technologies for the safety and rescue of the people in a complex underground space, such as tunnels, and mine roadways. In this paper, the method based on TOA/ DOA parameter estimation for high resolution passive mobile target localization is proposed. Because of the echo-mul- tipath of still object and the serious fading in tunnel, the strong minimum norm interference suppression method is pro- posed based on the zero limit of eigenvalue decomposition under the condition of low SNR. This suppresses the direct wave and the echo-multipath interference of still object and detects the reflected wave of moving targets. Meanwhile, the RMCHS （Root Min-norm based on Cross High-order Spectra） algorithm is proposed to overcome nanosecond dense multipath and background noise in the tunnel. The RMCHS algorithm can be used to estimate the TOA/DOA parameters with high resolution at low SNR, so the high resolution passive moving target localization based on TOA/ DOA parameter estimation is achieved. Simulation results show that the proposed strong interference suppression meth- od and the RMCHS algorithm have strong robustness in tunnel. The proposed method is significantly better in compari-son with the traditional algorithm. The influence of noise and nanosecond dense multipath on the performance of the al- gorithm is reduced.
作者
张晓光
孙彦景
霍羽
王刚
高芳
ZHANG Xiaoguang;SUN Yanjing;HUO Yu;WANG Gang;GAO Fang(School of Information and Control Engineering,China University of Mining and Technology,Xuzhou 221116,China)
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2018年第7期1965-1972,共8页
Journal of China Coal Society
基金
国家自然科学基金资助项目(51804304)
江苏省自然科学基金青年资助项目(BK20160264
BK20151148)
关键词
隧道
移动目标
无源定位
干扰抑制
TOA/DOA参数估计
tunnel
moving target
passive localization
interference suppression
TOA/DOA parameter esti-mation
