Research of Miss Distance Parameters Estimation Based on Data Fusion of Doppler Frequency and Range

A method of miss distance parameters estimation by utilizing simultaneously Doppler frequency and range information is proposed. According to the noise covariance of measured data, the proposed method first deals with Doppler frequency and range information of echo through the non-linear weighted data fusion, and establishes the corresponding cost function of least squares process, then utilizes the nonlinear optimization method to solve the miss distance parameters. The improvement of estimation performance of the proposed method, compared with the single observable measurement, Doppler frequency or range information, is illustrated by the theoretical derivation of Cramr-Rao Lower Bound (CRLB). Meanwhile, numerical calculation of CRLB is used to analyze the estimation performance. Finally, the computer simulation verifies the validity of the method.