Decoupled Algorithm of Decorrelated Unbiased Converted Measurements
As a classical nonlinear filtering algorithm,converted measurement Kalman filter(CMKF)is com-monly employed to address the problem of target tracking when the measurements are in polar or spherical coor-dinates.Under the circumstance of low SNR,the mismatch between converted measurement distribution and co-variance 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.
line of sight coordinatenonlinear filteringdecorrelated unbiased conversion measurementdecou-pled algorithm
万方数据
维普
