Information fusion technology has been in existence for several decades. At the beginning, this technology was mainly applied in military. The main reason is that at that time, the sensor was still a very expensive instrument. Military might be the only consumer who required superior performance without considering the cost.
In recent years, the application background of multi-sensor information fusion technology has undergone great changes. We have found that many civilian systems also have multi-sensor systems, such as unmanned vehicle and intelligent robot systems. Moreover, we have noticed that these systems have become a major part where the multi-sensor information fusion technology could be used, and they usually contain great research value. In these new application systems, multi-sensor information fusion technology also faces many new research issues. This is what the researchers are interested in this research field recently. We have discovered that there are many areas in which multi-sensor information fusion technology is worth investigating further.
Our special issue was consisted of 30 papers, including the latest research results of the multi-sensor information fusion technology.
In general, these research papers were mainly divided into two parts: one is theoretical research results, and the other is the application-oriented issues. The topic discussed in theoretical research involves in-depth research on methods and theories, and it proposes new methods. The related papers mainly included three aspects: (1) a new fusion method based on the Kalman filter, including the study of various nonlinear Kalman filters, such as CKF, UKF, etc.; (2) a method based on DS evidence theory; (3) new methods for images, including video tracking, expression recognition, etc. On the other hand, we are also delighted to see that there are many papers involving solutions for various applications, which also have extremely high reading and reference value.