机载平台对固定目标时差定位的精度改善方法

Methods for Precision Improvement of TDOA Location for Fixed Target by Airborne Platforms

针对高度粗略已知的地面固定目标三机时差定位问题,为提高定位精度,分别从不同的数据融合角度出发,提出了两种实用、可行的数据融合策略。首先,在传统时差定位求解算法—Chan算法的基础上,考虑将当前时刻和当前时刻之前的目标位置估计值进行融合,给出了一种简化的加权最小二乘算法(Simplified Weighted Least Square,SWLS)的定位融合方法。然后,根据跟踪滤波的思想,考虑将当前时刻和当前时刻之前的时差观测量进行融合,给出了采用扩展卡尔曼滤波(Extended Kalman Filter,EKF)的定位融合策略。通过数值仿真,验证了所提出了两种定位融合策略在提高定位精度方面的有效性。

For the problem of Time Difference of Arrival （TDOA） location by three airborne platforms for a ground fixed target with roughly known height, to improve the location precision, two practical and feasible data fusion methods were presented respectively from different views of data fusion. Firstly, based on the traditional solving algorithm of TDOA location--Chaffs algorithm, the integration of target position estimations in the current moment and previous moments was considered, and then one method of data fusion for TDOA location by utilizing a simplified weighted least square algorithm was proposed. Later, according to the idea of tracking filters, the integration of observed TDOA values in the current moment and previous moments was considered, and then the other method of data fusion for TDOA location by employing the extended Kalman filter was proposed. The effectiveness of the presented data fusion methods in the respect of improving location precision was validated through numerical simulations.