An Improved Airborne Passive Location Tracking Algorithm Using the Rate-of-change of Phase Difference

In order to solve the problem that it is difficult to acquire high precision angular velocity parameter in airborne passive location based on spatial-frequency domain information, this paper utilizes phase difference rate-of-changes augmentation to angular velocity, and constructs a new passive location measure model by two dimensions interferometer layout. The passive location of air target is realized. For the negative error covariance matrix possibly induces instability in the Unscented Kalman Filter (UKF), the square root UKF is introduced and improved. The Simplex Spherical distribution Unscented Transform (SSUT) is used to sigma sampling. The calculated amount of filtering is reduced by cutting down the number of sampling point. The simulation results show that the position and velocity tracking error of the new measure model decrease under the lower condition of parameters measurement. When the stable tracking effect can be reached, the algorithm efficiency can be enhanced by adopting improved square root UKF.