Study on Virtual-observation Kalman Filter Algorithm of Multi-radar Networking

Abstract

Abstract: Under the circumstances of tracking targets in multi-radar networking (MRN), measure-value in polar coordinates of the networked radar (NR) has the nonlinear relation with state-value of targets tracking coordinates, which does not satisfy linear requirement of Kalman filter algorithm (KFA) application. Virtualizing the tracking coordinates of MRN as the measure coordinates of KFA was introduced. As a result, original nonlinear relation was simplified as a linear form. By means of modeling virtual observation noise and constructing the initialization strategy, KFA could solve state estimation problem in MRN. Simulation analysis and real data verification demonstrate that virtual-observation KFA (VOKFA) has quick computation velocity, high precision and good stability, which is very suitable for engineering application of data fusion in MRN.

Key words: radar network, virtual observation, coordinate transformation, error statistical characteristic, initialization strategy

CLC Number:

TN95

Zhao Wenbo, Ding Hailong, Qu Chenghua, Mo Jun. Study on Virtual-observation Kalman Filter Algorithm of Multi-radar Networking[J]. Journal of System Simulation, 2015, 27(4): 851-858.

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