传感器误差情况下的线性校正TOA定位算法

传统定位方法一般是在假设传感器位置信息准确已知的前提下进行的。然而在实际情形中,传感器位置信息往往含有随机误差,这些误差会严重影响目标的定位精度。针对这一问题,提出了一种存在传感器误差情况下的线性校正TOA定位算法。首先将非线性TOA定位方程组转化为一组关于目标位置的伪线性方程,利用加权最小二乘估计进行初始求解;然后在此基础上把伪线性方程组转化为关于估计偏差的求解问题,进而对初始解进行线性校正。在测量误差充分小的情况下分析了该算法的有效性。仿真结果表明该算法具有较好的定位性能。

Linear-correction TOA localization algorithm with sensor location errors

Conventional location algorithms are based on the postulation that the sensor locations are exactly known. However, in practical situations, the sensor positions generally include random errors, which can considerably reduce the source localization accuracy. To tackle this problem, a new time of arrival (TOA) positioning algorithm based on the linear-correction technique is proposed. The proposed algorithm firstly reorganizes the nonlinear TOA equations into pseudo-linear ones and the initial target position estimation is obtained by using weighted least squares estimatets. Then a linear-correction technique is used to correct the initial position estimate. The effectiveness of the proposed method is theoretically analyzed under sufficiently small noise postulation. Simulation study validates the good performance of the proposed algorithm.