运动单站长基线干涉仪自校正定位方法

A Single Moving Observer Auto-Calibrated Localization Method Using LBI

针对单站测向定位中多通道干涉仪系统复杂且易受通道幅相不一致性影响等问题,研究利用运动单站上的单个长基线干涉仪(LBI)测量的模糊相位差(PD),联合估计辐射源位置和相位差偏差,实现自校正定位。针对该问题的高度非线性,提出一种距离和偏差联合参数化增量高斯和滤波(RBJP-AGMF)算法,然后利用初始相位差得到一组方位角,采用距离与偏差联合参数化方法获得一组高斯和滤波初始值。使用增量扩展卡尔曼滤波器(AEKF)组进行递推计算,并分析了定位误差的克拉美-罗下限(CRLB)。仿真结果表明该方法运算量较小,定位性能可接近CRLB。

Due to the complexity and amplitude-phase inconsistency of the multi-channel interferometers, a single moving observer auto-calibrated localization method using ambiguous phase differences （ PD ） of a single long baseline interferometer （LBI） is proposed to jointly estimate position and PD biases. To solve the high nonlinearity, a range and bias joint parameterization-augmented Gaussian mixture filter （RBJP-AGMF） localization algorithm is advanced. The initial phase difference measurement is used to get a set of initial azimuths, then the range and bias joint parameterization method is used to attain Gaussian mixtures. The position and bias are recursively estimated by the augmented extended Kalman filter （AEKF） bank. The Cramer-Rao lower bound （CRLB） is also derived. Simulation results show that this method has small computational effort and can attain the CRLB.