Static/dynamic distributed interacting multiple model fusion algorithms for multiplatform multisensor tracking
Zhen Ding · Optical Engineering · 1997
Zhen DingLang HongWright State UniversityDepartment of Electrical EngineeringDayton, Ohio 45435E-mail: [email protected]. Static and dynamic distributed interacting multiple model(IMM) fusion algorithms for multiplatform multisensor tracking are devel-oped. Each platform contains a model set, which may or may not be thesame as that of other platforms. An interacting multiple model filtering isperformed on each platform. An equivalent platform model and anequivalent global model are constructed. To save the bandwidth of aninterplatform communication datalink, only combined IMM tracks are al-lowed to communicate. Taking advantage of the equivalent models, bothstatic and dynamic fusion algorithms have very decent and comparableresults. But simulations show that the computation complexity for thedynamic fusion algorithm is far lower than that of the static fusion algo-rithm. Both algorithms benefit from multiple models and distributed track-ing.