BLUE filter with fused range estimation

Abstract

The non-linear filter is subject to divergence for close-range target tracking; an adaptive best linear unbiased estimation (BLUE) filter with fused range estimation is presented. After proposing the notion of predicted range, the weighted estimation of the predicted and measured ranges is used in the converted measurement model to track the target. The adaptive BLUE filtering parameters with Rayleigh range measurement are derived. Simulation results show the adaptive BLUE filter exhibits better robustness and accuracy with modest computational burden.

Keywords

• filtering theory
• target tracking
• fused range estimation
• predicted range
• weighted estimation
• predicted measured ranges
• converted measurement model
• rayleigh range measurement
• adaptive blue filter
• nonlinear filter
• close-range target tracking
• adaptive best linear unbiased estimation filter