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

Authors

Wenbo Zhao, 1. Amy Officer Academy of PLA, Hefei 230031, China;;
Hailong Ding, 1. Amy Officer Academy of PLA, Hefei 230031, China;;
Chenghua Qu, 2. No. 38 Research Department of CETC, Hefei 230088, China;
Mo Jun, 2. No. 38 Research Department of CETC, Hefei 230088, China;

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.

Recommended Citation

Zhao, Wenbo; Ding, Hailong; Qu, Chenghua; and Jun, Mo (2020) "Study on Virtual-observation Kalman Filter Algorithm of Multi-radar Networking," Journal of System Simulation: Vol. 27: Iss. 4, Article 25.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss4/25

First Page

851

Revised Date

2014-06-11

DOI Link

https://doi.org/

Last Page

858

CLC

TN95

Recommended Citation

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.