Research on Data Fusion Optimizing Filtering Algorithm for SOPLAT System

Most currently existing algorithms used in SOPLAT (single observer passive location and tracking) system usually select single parameter measurement set which concludes only a little measured information, which means that they do not consider and make full use of spatial and temporal information as well as frequency range information which can be measured synchronously by modern electronic detecting equipment. In order to overcome this drawback, a new fusion optimization filtering algorithm for SOPLAT system is presented, this algorithm can fully utilize the redundant information coming from many sensors, which includes TOA, DOA and Doppler frequency measurements, etc. The proposed method improves further the location & tracking accuracy, reliability and defensive operational capability of the system by using data fusion technology. As a demonstration to evaluate the method described in this paper, two simulation examples are presented which indicate the effectiveness and feasibility of this filtering algorithm, and the results show that this method has better accuracy and convergence rate than conventional algorithms.