Content area
Abstract
In recent years, multisensor Kalman filter fusion have received significant attention for both military and non-military applications. But in fusion center the data size may be too large to be processed immediately. In 1976 [1], a data compression method for multisensor Kalman filter fusion was brought forward firstly. In that case, the data are compressed in the fusion center to improve the computational efficiency. But the measurement data have to be transformed to a common coordinate system. Obviously, this result is too limited to be applied. In this paper, two new methods are proposed to deal with the more common situations and their arithmetic equivalence to uncompressed processing is proved.