摘要
针对运动单传感器系统误差配准问题进行了研究，提出了一种基于位置未知固定目标的单传感器实时系统误差配准算法。算法利用传感器对固定目标的两时刻量测值，构建包含传感器系统误差的等效系统状态及其状态方程与量测方程，并基于扩展卡尔曼滤波技术实现了利用位置未知的固定目标对传感器系统误差的实时精确滤波估计。蒙特卡洛仿真结果验证了算法的有效性，具有对系统误差的稳定估计性能、快速的滤波收敛能力、较高的系统误差配准精度以及较强的工程实用性。
The moving single sensor registration algorithm using unknown location fixed target was problem was researched, and a real-time bias registration presented in this paper. Based on two times＇ measurements of the target, the registration algorithm constructed an equivalent state concluding sensor bias, the corresponding dynamic equation and measurement equation. Then, based on the extended Kalman filter, the algorithm achieved a real-time exact estimation of the single sensor bias. Finally, the Monte-Carlo simulation result adequately illustrated the validity of the presented algorithm, and showed that the algorithm had a steady estimation performance, fast convergence capability, exact registration precision and favorable engineering practicability.
出处
《海军航空工程学院学报》
2010年第6期617-620,共4页
Journal of Naval Aeronautical and Astronautical University
基金
国家自然科学基金资助项目(60801049)
关键词
系统误差
扩展卡尔曼滤波
误差配准
传感器组网
sensor bias
extended Kalman filter
sensor registration
sensors networking
