A Fusion Localization Method Based on Target Measurement Error Feature Complementarity and Its Application

In the multi-radar networking system, aiming at the problem of locating long-distance targets synergistically with difficulty and low accuracy, a dual-station joint positioning method based on the target measurement error feature complementarity is proposed. For dual-station joint positioning, by constructing the target positioning error distribution model and using the complementarity of spatial measurement errors of the same long-distance target, the area with high probability of target existence can be obtained. Then, based on the target distance information, the midpoint of the intersection between the target positioning sphere and the positioning tangent plane can be solved to acquire the target’s optimal positioning result. The simulation demonstrates that this method greatly improves the positioning accuracy of target in azimuth direction. Compared with the traditional the dynamic weighted fusion(DWF) algorithm and the filter-based dynamic weighted fusion(FBDWF) algorithm, it not only effectively eliminates the influence of systematic error in the azimuth direction, but also has low computational complexity. Furthermore, for the application scenarios of multi-radar collaborative positioning and multi-sensor data compression filtering in centralized information fusion, it is recommended that using radar with higher ranging accuracy and the lengths of baseline between radars are 20–100 km.