The key problem of task allocation in many applications of WSANs such as intelligent minefield is how to obtain the node-target assignment to achieve the maximum task effectiveness of the whole system. Since the performance of sensors and weapons and targets' capability of avoidance detection are very variable, different sensor/weapon-target allocations lead to different probabilities of acquisition and killing. The Sensor/Weapon-Target Assignment model considering the probability of detection and killing for the application of intelligent minefield is proposed and an application of Multi-Scale Quantum Harmonic Oscillator Algorithm was implemented to solve the assignment problem for Sensor/Weapon-Target Assignment. The results show that the scheme is suitable for Sensor/Weapon-Target Assignment problem in the application of intelligent minefield. This scheme can be promoted to large-scale assignment problems.