Fusion of Localization Estimates in Multistatic Passive Radar
Jamie H. Huang, Graeme Edward Smith · 2019
In multistatic passive radar, target location estimates from both multilateration and array-based localization methods would be available. Based on insights from the comparative analysis of the methods as a function of geometry, a method of selecting the best target location estimate is proposed. The Kalman filter is used to fuse the localization estimates. Experimental verification is achieved using data collected from a target that was simultaneously detected using three different illuminators of opportunity. The filtered estimates have an accuracy within 100 m for a target at a receiver range of 6 km.