摘要
为对原始雷达数据进行空间配准,对原始的实时质量控制方法(real time quality control,RTQC)进行了研究。在传统的RTQC算法的基础上,加入Kalman滤波,用于对随机误差进行处理,得出雷达测量的固定误差。对Kalman算法进行改进,改进了传统的Kalman滤波算法,通过对量测噪声方差矩阵和模型噪声方差矩阵进行实时估计,减少了Kalman滤波对于方差矩阵先验知识的要求,提高了Kalman滤波的自适应性,并初步分析了算法的有效性。与实际数据的对比实验结果表明了该方法的有效性。
On the RTQC-algorithm（real time quality control） is researched to do the space registration of original radar data.The RTQC-algorithm is improved by using the Kalman-filtering process to deal with the random error,and to get the system error of the radar system.The Kalman filtering process is improved by calculating the measurement error covariance matrix and process error covariance matrix adaptively,the request of the knowledge of the error is deduced.A better adaptation of Kalman filtering is provided and the ef-fectiveness of the algorithm is analyzed.The experiment of the real data show the effective result of this algorithm.
出处
《计算机工程与设计》
CSCD
北大核心
2009年第24期5733-5735,共3页
Computer Engineering and Design
基金
国家863高技术研究发展计划基金项目(2006AA12A104)
