.png){kind=icon}
返回
Data association and geolocation for electronic support systems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compeleceng.2012.08.001.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Data association (DA) in highly sensitive electronic support (ES) systems is nontrivial when closely-spaced, low probability-of-intercept (LPI) emitters, in cluttered radio-frequency (RF) environments, are sought. A practical processing framework for these situations is presented in this paper. Joint probabilistic data association (JPDA) is used to handle the multitarget tracking (MTT) problem in frequency-augmented direction-of-arrival versus time coordinates (i.e. 'signal' space). It is shown that the JPDA update has a pleasantly simple form when processing a serial stream of time-stamped measurements. A Bayesian M-out-of-N track confidence model is derived using the beta distribution and used to 'integrate' automatic track management functions (i.e. JIPDA). A maximum-likelihood expectation-maximisation (ML-EM) algorithm is also derived and applied to perform bearing-only target-motion-analysis (TMA) in geographic coordinates for confirmed JIPDA tracks. The application of EM compensates for previous measurement-to-signal-track assignment errors and decreases the deleterious influence of spurious measurements, due to clutter or other emitters, without combinatorial complexity. (C) 2012 Elsevier Ltd. All rights reserved.
Keyword:
PROBABILISTIC DATA ASSOCIATION
BEARINGS-ONLY TRACKING
TARGET TRACKING
RADAR
PERFORMANCE
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.9
论文数:
6.7K
被引数:
1.3W
机构
引用论文
.png){kind=icon}
PROPHYLACTIC TREATMENT OF ACQUIRED VON WILLEBRAND DISEASE IN NON-HUMAN PRIMATES WITH VGA039, AN ANTI-PROTEIN S MONOCLONAL ANTIBODY使用抗蛋白S单克隆抗体VGA039对非人灵长类动物进行获得性冯·维勒布兰德氏病的预防性治疗
PREAI
分享收藏
查看更多内容