基于信噪比优化的中段传感器预指派模型  

Midcourse sensor pre-assignment model based on SNR optimization

作　　者：杨媛媛[1] 盛卫东[1] 安玮[1] 张寅生[1] 江丹[1] 

机构地区：[1]国防科技大学电子科学与工程学院,湖南长沙410073

出　　处：《航天电子对抗》2016年第3期23-26,41,共5页Aerospace Electronic Warfare

摘　　要：结合中低轨中段弹道目标连续跟踪这一特殊应用背景,从跟踪相机交接的再捕获确认到稳定跟踪的全程角度出发,提出了一种基于信噪比和跟踪精度联合优化的新的传感器预指派模型。并采用通过对粒子降维处理和位置矢量更新的实值粒子群优化算法,对所提模型的性能进行分析和比较。仿真实验表明,该模型的调度性能较之前的优化目标函数及二进制粒子群优化算法,更贴近导弹中段飞行情况的实际且性能有所改进,因而是一种更高效的调度模型。Based on a special application background of continual midcourse object tracking, a novel sensor pre assignment model based on SNR optimization combined the GDOP optimization model is proposed according to the whole course from the capture affirmance to the stable tracking. Furthermore, real-number particle swarm optimization is adopted that through dimensionality reduction and position vector improvement, and the proposed model is analyzed and compared in detail. The simulation results show that the optimization model is a more efficient algorithm compared with the optimized objective function and binary particle swarm optimization algorithm.

关 键 词：信噪比优化 多传感器管理 实值粒子群优化 目标连续跟踪 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TN953[自动化与计算机技术—控制科学与工程]