supported by the National Natural Science Foundation of China(61271296)
Particle filters have been widely used in nonlinear/non- Gaussian Bayesian state estimation problems. However, efficient distribution of the limited number of particles (n state space remains a critical issue in desi...
supported by the National Natural Science Foundation of China (61102166);the Scientific Research Foundation of Naval Aeronautical and Astronautical University for Young Scholars (HY2012)
Based on the target scatterer density, the range-spread target detection of high-resolution radar is addressed in additive non-Gaussian clutter, which is modeled as a spherically invariant random vector. Firstly, for ...
supported by the National Defense Advanced Research Foundation of China (51407020304DZ0223).
To validate the potential space-time adaptive processing (STAP) algorithms for airborne bistatic radar clutter suppression under nonstationary and non-Gaussian clutter environments, a statistically non-Gaussian, spa...
the National Natural Science Foundation of China (60572038).
When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competitio...
This project was supported by the National Natural Science Foundation of China (50405017) .
For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to ...