摘要
在集中式多雷达跟踪系统中,经常存在雷达的观测信息维数不一致的情况。为了能正确对所有雷达观测数据进行融合,系统需要首先对维数不匹配的观测数据进行处理。目前,通常采用降维的方法处理数据维数不匹配问题。由于在降维处理过程中,需要丢失目标的高度信息,因此,系统会产生一定的动态误差。当目标的俯仰角度比较大时,系统的跟踪精度必然会下降。针对降维方法的缺点,本文采用升维的方法对数据维数不匹配进行处理,并对这两种方法在不同情况下的跟踪精度进行了仿真分析。
In one centralized multi-radar tracking system, there are always different radars, which may have different observation-dimension. In order to correctly fusion all data of radars, the system must take some measures to make suer that all data have uniform dimension. At present, reducing dimension is often used to deal with the problem. Because of the loss of the height information of target in the process of reducing dimension, the system may produce some dynamic error. If the pitching angle of target is relatively large, the tracking precise of the system must be reduced. In this paper, one increasing dimension method is introduced, which can be used to remedy the defect of reducing dimension method. At last, a Monte Carlo simulation is used to analyze the tracking precision of the two methods.
出处
《系统仿真学报》
CAS
CSCD
2003年第6期845-848,共4页
Journal of System Simulation
基金
全国优秀博士论文作者专项资金资助项目(200036)
高校骨干教师资金资助项目(3240)
关键词
信息融合
多雷达
数据压缩
数据维数
data fusion
multi-radar
data compress
data dimension
