Spatial Kalman Filters and Spatial-Temporal Kalman Filters

The classic Kalman theory is established on time continuous observation. Using on the spatial-temporal duality, Spatial Kalman Filters (SKF) is introduced based on spatial continuity. Further, an improved SKF named Spatial-Temporal Kalman Filters (STKF), which is based on time and spatial distribution, is proposed. It is suitable for applications in open fields, such as multi-sensors information merging. Our simulation analysis shows that STKF achieves the same filtering accuracy comparing as the centralized multi-sensor fusion (CMSF) algorithm, further, STKF requires much less computation complexity than CMSF.