  The three-dimensional CMKF-U with only position measurements is extended to
solve the nonlinear tracking problem with range-rate measurements in this
paper. A pseudo measurement is constructed by the product of range and
range-rate measurements to reduce the high nonlinearity of the range-rate
measurements with respect to the target state; then the mean and covariance of
the converted measurement errors are derived by the measurement conditioned
method, showing better consistency than the transitional nested conditioning
method; finally, the sequential filter was used to process the converted
position and range-rate measurements sequentially to reduce the approximation
error in the second-order EKF. Monte Carlo simulations show that the
performance of the new tracking algorithm is better than the traditional one
based on CMKF-D.
