基于动态贝叶斯的反舰导弹弹型识别

Bomb Recognition of Anti-Ship Missiles Based on Dynamic Bayesian

摘要:

使用反舰导弹对舰艇进行饱和攻击是当前对舰攻击的主要方式。首先,提出了动态贝叶斯网络(DBN)的理论及算法；其次,根据反舰导弹的高度、速度、过载、机动方式等弹道特性和 RCS、雷达频率等导弹自身特性,建立了对反舰导弹进行弹型识别的 DBN模型；最后,通过仿真算例验证了 DBN模型的有效性,这为实际解决反舰导弹 进行弹型识别的问题,提供了一种思路。

Abstract:

Saturation attack using anti-ship missile is an important tactical method in high-tech war against warship andcan increase missiles penetration probability. The basic idea and the inference algorithm of dynamic Bayesian network(DBN) were given in this paper firstly. After analyzing the height, velocity, overload, maneuver manner of the ballistic tra.jectory characteristic, the model of DBN was given in consider of the RCS, radar frequency of the missile itself. Simulationresults proved the correctness of the proposed model, and the proposed method put forward a new way for the anti-ship rec.ognition.