基于最小二乘联合算法的无人机定位  

Unmanned Aerial Vehicle Positioning Based on Least Square Joint Algorithm

作　　者：吴云训 WU Yunxun(Guangzhou Urban Renewal Planning Institute,Guangzhou Guangdong 510045,China)

机构地区：[1]广州市城市更新规划研究院,广东广州510045

出　　处：《北京测绘》2020年第11期1588-1591,共4页Beijing Surveying and Mapping

摘　　要：在MIMO双基地雷达基本理论基础上,运用最小二乘法将波达角度(DOA)和时间差(TDOA)相联合,得到一种新的无人机定位算法。通过matlab仿真分析,得到如下认识:(1)基于最小二乘联合算法的算法性能优于TDOA独立算法,前者较后者的坐标精度提升约34%;(2)无人机与基线间的距离越大,定位误差越大,随着σ的不断增大,误差也逐渐增大,但增长幅度越来越缓;(3)阵列数目越大,位置误差越小,当阵列为3时,误差较大,且较为波动,当误差为4~6时,位置误差相差较小,建议实际应用时,阵列数应≥4。Based on the basic theory of MIMO bistatic radar,a new UAV positioning algorithm is obtained by combining DOA and TDOA with the least square method.Through the MATLAB simulation analysis,we can get the following knowledge:(1)the algorithm performance based on the least square joint algorithm is better than the TDOA independent algorithm,the former's coordinate accuracy is about 34% higher than the latter;(2)the larger the distance between the UAV and the baseline,the larger the positioning error,with the increasing of σ,the error is gradually increasing,but the increasing range is more and more slow;(3)the larger the number of arrays,the bit The smaller the setting error is,the larger the error is when the array is 3,and the more fluctuant it is.When the error is 4~6,the smaller the difference is.It is suggested that the number of arrays should be≥4 in practical application.

关 键 词：无人机 最小二乘法 波达角度估计(DOA) 波达时间差估计(TDOA) 定位算法 误差 

分 类 号：P231[天文地球—摄影测量与遥感]