去相关无偏转换量测的解耦算法  

Decoupled Algorithm of Decorrelated Unbiased Converted Measurements

作　　者：盛琥 汪海兵 曲成华[2] 方青[2] 靳俊峰[2] SHENG Hu;WANG Haibin;QU Chenghua;FANG Qing;JIN Junfeng(Jianghuai Advance Technology Center,Hefei 230000,China;No.38 Research Institute of CETC,Hefei 230031,China;Electronic Countermeasure School of NUDT,Hefei 230037,China)

机构地区：[1]江淮前沿技术协同创新中心,安徽合肥230000 [2]中国电子科技集团第38研究所,安徽合肥230031 [3]国防科技大学电子对抗学院,安徽合肥230037

出　　处：《探测与控制学报》2024年第6期86-91,共6页Journal of Detection & Control

基　　金：江淮前沿技术协同创新中心追梦基金课题(2023-ZM01K010)。

摘　　要：转换量测(CMKF)卡尔曼滤波能较好处理极/球坐标系内观测模型与直角坐标系内状态模型的不兼容问题,在实际中得到推广。在低信噪比环境下,由于方位误差余弦的非线性,转换量测样本分布和协方差阵估计不匹配,导致径向估计误差变大。针对低信噪比条件下的非线性滤波问题,提出度量非线性影响的失配因子指标,采用基于视线坐标系的解耦去相关无偏转换量测(DUCM)模型,在径向上引入加权方位,改善失配因子,提高估计精度。理论分析和仿真证明:这种基于视线坐标系的解耦处理能显著提高径向估计精度,适用于其他转换量测方法,有较好普适性。As a classical nonlinear filtering algorithm,converted measurement Kalman filter(CMKF)is commonly employed to address the problem of target tracking when the measurements are in polar or spherical coordinates.Under the circumstance of low SNR,the mismatch between converted measurement distribution and covariance matrix estimate will degrade radial estimation because of azimuth cosine nonlinearity.To solve nonlinear filtering problem with low SNR measurements,a mismatch factor was proposed to evaluate nonlinear influence,a decorrelated unbiased converted measurement(DUCM)model based on line-of-sight coordinate was developed,the weighted azimuth was introduced along visual axis to improve mismatch and down-range accuracy.Theoretic analysis and simulation verified that this decouple operation could improve radial estimation significantly,which could be applied to other converted measurement approaches.

关 键 词：视线坐标系 非线性滤波 去相关无偏转换量测 解耦算法 

分 类 号：TP953[自动化与计算机技术]