Interacting Multiple Model Algorithm Used In Multi-Sensor Fusion System
In recent years, along with the development of information fusion technique, surveillance and tracking systems have relied more and more on the Multi-Sensor Systems (MSS), which is comprised of multiple sensors working in a coordinated way to provide more accurate and reliable state estimates of targets than isolated sensors. In these systems, fusion usually plays a critical role in combining information. There are many fusion techniques, and most of them fall into two categories—measurement fusion and track fusion, depending on what kind of information is to be shared among sensors. Some researchers have shown that the use of multiple sensor data can sometimes degrade performance when a single model filter (e.g., the Kalman filter) is used. In this paper we consider a distributed track fusion system, in which use interacting multiple model (IMM) filter, educe a distributed multiple sensors IMM fusion algorithm and investigate in more detail how the performance of the IMM is affected when it is used with multiple sensors.
IMM information fusion Kalman state estimate
Zhang Guang-yuan Wang Fu-jun Wei Zhen-sheng
Department of Optics and Electronics,Ordnance Engineering College,Shijiazhuang 050003,China
国际会议
西安
英文
2007-08-16（万方平台首次上网日期，不代表论文的发表时间）