摘要
本文针对高杂波密集环境下边跟边扫雷达实时警戒系统中的数据初始互联问题,提出了一种新的自适应有限记忆法。该方法利用雷达的检测概率和接收机的虚警率,结合所记忆的有限个周期的点迹数估计出可能起始航迹的数目;然后,通过自适应地调整互联相关域的大小及正规化残差平方和阀值,保留可能性较大的量测序列,抑制假航迹。算法分析和仿真结果表明,将雷达的动态检测信息和有限周期的量测相结合,能较好地解决实时系统中的数据初始互联问题。
A new approach, which combines the radar＇s dynamic information and several scans＇ measurements to deal with the data initial association problem in high clutter environment of tracking-while-scanning systems, is proposed. First, the dynamic initial track numbers are estimated by using the measurements＇ number in the sliding window, the target detection probability and the receiver＇s noise sampling information. Then the estimated initial track numbers are adopted to adjust the initial correlation region and the normalized residual square threshold adaptively. Therefore, lots of false initial trajectories are suppressed. Simulation results demonstrate that our approach can solve the real time data initial association problem better than logic-based method.
出处
《光电工程》
CAS
CSCD
北大核心
2010年第9期1-7,共7页
Opto-Electronic Engineering
关键词
初始互联
有限记忆法
边跟边扫雷达
initial association
limited memory algorithm
tracking-while-scanning radar
