The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithm for dualaircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar’s radiation area. The problem is formulated as a Markov decision process(MDP) by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneuvering target. The problem of passive detection discussed in this paperpting searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithm for dualaircraft flight path planning is. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar’s radiation area. The problem is formulated as a Markov decision process (MDP) by using the fuzzy theory to make a generalization of the state space and defining the transition functions Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneuvering target.