Joint Pulse Association, Sorting, and Localization of Pulse Radar Signals With Cluster Reconnaissance

A significant challenge in cluster collaborative reconnaissance is achieving pulse association between disparate reconnaissance units. However, traditional time-of-arrival (TOA) histogram methods struggle to attain high accuracy in radar pulse association when reconnaissance units are distant, the pulse repetition frequency of the radar signal is high, or the emitter's position is suboptimal. Furthermore, these methods are sensitive to the division of the TOA histogram. To address these issues, we propose a pulse association method for cluster reconnaissance that treats the association, sorting, and localization of radar signals as a unified problem, aiming to solve them collectively. In addition, we introduce the concept of a fuzzy generation set to resolve ambiguities in localization. Simulation results demonstrate that our proposed method significantly enhances the accuracy of pulse association while also achieving high sorting accuracy and localization precision. Under conditions with a TOA error of 50 ns, a site error of 10 m, and a pulse drop rate of 0.2, our proposed method achieves an estimation accuracy exceeding 90% for the emitters count, with pulse association and sorting accuracies greater than 95%, and a localization root-mean-square error of less than 1%.