多源二维测角信息的三维动态目标跟踪定位算法

Tracking and Locating Algorithm of 3-Dimensional Moving Targets Using 2-Dimensional Angular Measurements from Multiple Passive Sensors

针对纯角度非线性估计法对量测方程进行线性化处理后的运动要素估计出现发散或偏置现象等问题,提出了基于多源二维测角信息的三维动态目标跟踪定位算法.利用最大似然估计法对多基站提供的角度量测信息进行融合处理,由此获得的量测方程经伪线性化后的均方等效误差期望值最小,从而实现了目标运动要素无偏估计.通过仿真表明,利用所提算法获得的位置跟踪误差曲线能快速、准确地逼近Cramer-Rao下界,比扩展的卡尔曼滤波器的收敛速度快,精度高,跟踪精度可提高50%.

The target motion analysis （TMA） is a nonlinear estimation problem because of the nonlinearity of its measure equation, and the pseudo linear equation derived from the measure equation will result in biased or divergent solutions. The authors present an efficient and nearly unbiased algorithm for biostatic bearlngs-only target locating based on measured angles. The simulation results show that compared with the extended Kalman filter, the error curve of the root mean square of the position estimated by the proposed algorithm approaches the Cramer-Rao low bound （CRLB） more efficiently for Gaussian noise, and the precision is approximately improved by 50%.