多传感器多目标被动跟踪的 “鬼点” 形成条件

To explore the formation mechanism of ghost nodes in multi-sensor multi-target passive tracking, a method based on set theory is applied to establish a mathematical model for multi-sensor multi-target passive tracking. The method defines bearing measurements as different point sets and targets as the intersections of them. Using the model, the formation conditions of ghost nodes are obtained for three typical scenarios. It is found that the length of sensors’ observation baseline, distribution characteristics, and number of sensors are important factors affecting the generation probability of ghost nodes. Three groups of illustrative simulations are conducted to further verify the above factors’ practical effects on the likelihood of ghost nodes being traced. The results indicate reducing the length of sensors’ observation baseline appropriately, increasing the spatial layout complexity of the sensor network relative to the target group, and using more sensors for observation have a certain positive effect on suppressing the generation of ghost nodes when solving the multi-sensor multi-target passive tracking problem.