STATIC DYNAMIC DISTRIBUTED INTERACTING MULTIPLE MODEL FUSION ALGORITHMS FOR MULTIPLATFORM MULTISENSOR TRACKING/

Static and dynamic distributed interacting multiple model (IMM) fusion algorithms for multiplatform multisensor tracking are developed. Each platform contains a model set, which may or may not be the same as th at of other platforms. An interacting multiple model filtering is perf ormed on each platform. An equivalent platform model and an equivalent global model are constructed. To save the bandwidth of an interplatfo rm communication datalink, only combined IMM tracks are allowed to com municate. Taking advantage of the equivalent models, both static and d ynamic fusion algorithms have very decent and comparable results. But simulations show that the computation complexity for the dynamic fusio n algorithm is far lower than that of the static fusion algorithm. Bot h algorithms benefit from multiple models and distributed tracking. (C ) 1997 Society of Photo-Optical instrumentation Engineer.