光电跟踪系统的一类非线性滤波器

传统的光电跟踪系统通过测量目标的斜距离、俯仰角和偏航角来获取目标运动参数。针对附加角速度测量的一类新的光电跟踪系统,充分考虑传感器测量噪声的相关特性,基于非线性估计理论设计了目标跟踪滤波器。首先利用嵌套条件方法推导了转换测量误差前两阶矩的一致性估计,然后采用序贯采样卡尔曼滤波器（SUKF）对解耦后的转换测量进行序贯处理,最后从理论上分析了跟踪滤波器的稳定性并给出了跟踪系统的Cramer-Rao下界（CRLB）。Monte-Carlo仿真表明：滤波器估计误差均方差（RMSE）已逼近非线性跟踪系统的CRLB。

Abstract：

Generally tradition optic-electric tracking systems can obtain target motion parameters by measuring distance,elevation angle and yaw angle of targets.A target tracking filter taking correlated measurement noises into account was designed for optic-electric tracking systems with angle velocity measurements based on nonlinear estimation theory.Firstly,the consistent first two moments estimate of the converted measurement errors were derived by nested conditioning method;then the converted measurements were sequentially processed according to Sequential Unscented Kalman Filter （SUKF）;Finally the stability of the filter was analyzed theoretically and the Cramer-Rao Low Bound （CRLB） of the nonlinear tracking systems was proposed.Monte-Carlo simulation results show that the Root Mean Square of Estimate Error （RMSE） of the filter is closed to the CRLB of the nonlinear tracking systems.

A Class of Nonlinear Filter for Optic-electric Tracking System

Generally tradition optic-electric tracking systems can obtain target motion parameters by measuring distance,elevation angle and yaw angle of targets.A target tracking filter taking correlated measurement noises into account was designed for optic-electric tracking systems with angle velocity measurements based on nonlinear estimation theory.Firstly,the consistent first two moments estimate of the converted measurement errors were derived by nested conditioning method;then the converted measurements were sequentially processed according to Sequential Unscented Kalman Filter （SUKF）;Finally the stability of the filter was analyzed theoretically and the Cramer-Rao Low Bound （CRLB） of the nonlinear tracking systems was proposed.Monte-Carlo simulation results show that the Root Mean Square of Estimate Error （RMSE） of the filter is closed to the CRLB of the nonlinear tracking systems.