观测站存在位置误差条件下基于MDS的多站时差定位算法

为了降低无源定位中观测站站址误差对定位精度产生的不良影响，论文提出了一种基于多维尺度分析的多站无源时差定位解析算法。算法建立了存在站址误差时关于目标位置的线性方程组，推导了方程误差与时差测量误差和站址误差之间的关系式，将误差的统计特性融入到新的加权矩阵之中，使用加权最小二乘方法对目标位置进行了求解。仿真实验表明，算法对于小测量误差具有无偏性，其定位精度能够达到克拉美罗下界，相对于Ho K C的解析算法具有更好的稳健性。 

Multidimensional scaling-based algorithm of passive source localization using multiple receivers from TDOA measurements with erroneous receiver positions

Receiver position error is known to degrade the passive source localization accuracy significantly. To deal with this problem, a new time difference of arrival based closed-form algorithm using multiple receivers with position errors is introduced, which exploits the multidimensional scaling (MDS) analysis. The linear equations related to the target position are constructed. The relation between the equation errors and the TDOA as well as the receiver position measurement errors is deduced. The weighted LS method is used to solve the target position, in which the weighting matrix includes the statistical character of the measurement errors. Simulation demonstrates that the proposed method has unbiasedness for small measurement errors. It can also achieves an accuracy close to the Cramer-Rao low bound and is more robust to larger errors than the method by Ho K C.