Analysis of suboptimal Kalman tracking algorithms

The standard Kalman filter has been applied extensively to the tracking of nonmaneuvering targets. Although the filter tracks such targets accurately, it creates a heavy computational burden. A study is made of several suboptimal Kalman filtering schemes which require less computational effort than the standard Kalman filter while yielding nearly optimal performance during both transient and steady-state filtering. It is shown by simulation results and by analysis that the suboptimal filters are viable alternatives to the standard Kalman filter