CAJ | 학술논문

GPS动态数据处理中广泛应用卡尔曼滤波，经典Kalman滤波认为预报误差是白噪声，服从零均值的正态分布，并利用动态噪声协方差矩阵来控制它对当前信息的影响，但实际测量定位中难以保证观测对象的规则运动，因而容易出现模型误差。针对G PS动态定位的这一问题，探讨了在实际应用中存在模型误差时的卡尔曼滤波，介绍了一种自适应Kalman滤波算法，该法顾及了载体机动加速及接收机发生周跳时的影响，减少了滤波发散的机会。
GPS동태수거처리중엄범응용잡이만려파，경전Kalman려파인위예보오차시백조성，복종령균치적정태분포，병이용동태조성협방차구진래공제타대당전신식적영향，단실제측량정위중난이보증관측대상적규칙운동，인이용역출현모형오차。침대G PS동태정위적저일문제，탐토료재실제응용중존재모형오차시적잡이만려파，개소료일충자괄응Kalman려파산법，해법고급료재체궤동가속급접수궤발생주도시적영향，감소료려파발산적궤회。
Kalman filtering have extension application in GPS kinetic data procession . classic Kalman filtering deems that predict bias is w hite noises w hich obey zero mean value normal school ,and controls current information effect by dynamic noise variance matrices . In fact ,it is impossible keep normal moving and so it is very easy come forth error .This pa-per discusses on the Kalman filtering that have errors in apply and introduces a new adaptive-ly Kalman filtering approach ,considering body rand accelerate and circle slips effect and the chance of divergence deduced .