Sensor-weapon joint management based on improved genetic algorithm

In the modern combat operation, the fixed combination of sensors and weapons are divided into separate parts, allowing better sensors to match with better weapons. As a result, the shooting effectiveness of weapons can be improved. In order to maximum the benefit of the combat operation, the optimization problem to describe operational effectiveness of sensors and weapons is established. Furthermore the method to solve this problem is studied. The method is an improved genetic algorithm, whose parent populations are divided into three components, by adjusting the proportion of each component, the searching area can be dynamically changed (ds-GA). The simulation results show that ds-GA is a suitable method which could solve the sensor-weapon joint management problem in a short time.

1 Introduction

With the development of science and technology, the conventional combat mode has changed. Networking the operational nodes and sharing the battlefield information can improve operational effectiveness, which becomes the trend of building method for operational architecture. In the modern combat operation, separating sensors and weapons allows better sensors to guide better weapons; as a result, the shooting effectiveness of weapons can be improved. However, recent researches have focused on the independent sensor management and Weapon-Target Assignment (WT A), the research of management strategy for both sensors and weapons is rare, it needs a further study.