基于最小二乘融合估计的双星时频差定位  

Geo-location Using Dual-satellite′s TDOA and FDOA Data by Least Square Fusion Estimation

作　　者：彭华峰[1] 夏畅雄[1] 曹金坤[1] 

机构地区：[1]西南电子电信技术研究所,成都610041

出　　处：《电讯技术》2012年第4期435-439,共5页Telecommunication Engineering

摘　　要：针对单参考站条件下具有测量误差和星历误差时定位精度不高的特点,提出了一种基于多次观测数据的最小二乘融合估计定位算法,该算法无需增加观测条件即可有效提高辐射源定位精度。分析了测量误差、星历误差对单参考站单次定位及融合定位精度的影响,推导了测量误差、星历误差对定位误差的传递公式,提出了含星历误差影响的最小二乘融合估计加权算法。通过Monte-Carlo仿真验证了误差分析结果和定位算法,并比较了加权最小二乘估计定位和单次定位的性能。仿真试验表明:在相同观测精度条件下,加权最小二乘融合定位可极大地提高辐射源定位精度,最大提高10倍以上。Aiming at the problem of geo - location with only one reference station, which has feature of low posi- tion precision when there are measurement error and ephemeris error, a Least Square（LS） estimation method is proposed here by fusing multi - time＇s observation, by which the location accuracy can be greatly improved with- out increasing the observation conditions. In condition of one reference station, when measurement error and ephemeris error are added, the one observation geo - location method and multi - observation geo - location method are studied. The influence of observation error and ephemeris error is analysed： The equation of error transfer from observation error and ephemeris error to geo - location error is derived. A weighted algorithm for LS estimation geo - location is proposed and compared with the one observation geo - location algorithm. By Monte - Carlo simulation, the analysis conclusion and weighted LS estimation geo - location algorithm are proved, and also the performance of one - observation and multi - observation algorithm is compared. Simulation result shows that the weighted I_S multi - observation geo - location estimator can greatly improve the location precision. The best result shows that multi - observation algorithm can be 10 times better than one - observation geo - location algorithm.

关 键 词：双星 时差频差 定位 估计 数据融合 

分 类 号：TN971[电子电信—信号与信息处理]