基于改进SRCKF的固定单站无源定位算法

Fixed Observer Passive Location Algorithm Based on Improved Square-root Cubature Kalman Filter

针对平方根容积卡尔曼滤波(SRCKF)算法精确性和实时性存在的不足,以固定单站无源定位系统为研究对象,提出基于改进SRCKF的固定单站无源定位算法。该算法对SRCKF算法时间更新环节进行线性简化,能避免计算容积点带来的加权近似误差,减少运算量提高效率;引入迭代思想,对量测更新环节进行迭代运算,充分利用量测信息,降低估计误差。仿真结果表明,该算法能有效提高滤波估计精度和运算时效。

Aiming at the lack of accuracy and real time of square root cubature Kalman filter algorithm,a fixed single observer passive location algorithm based on improved SRCKF was proposed,which taking the fixed single station passive location system as the research object.The SRCKF time update link was linearly simplified to avoid calculating volume points,reduced the amount of calculation and improve efficiency;the iterative idea was introduced to carry out iterative operation on the measurement update link,which made full use of the measurement information and reduced the estimation error.Simulations showed that the algorithm could effectively improve the filtering estimation accuracy and operation efficiency.