A FUSION ALGORITHM WITH SYNCHRONOUS AND ASYNCHRONOUS MEASUREMENTS FOR ACTIVE AND PASSIVE RADAR SYSTEMS

In a collaborative detection system composed of active radar and passive radars, the arrival times of measurements from active and passive radars are not necessarily the same. However, traditional methods usually assume that the arrival times of measurements from these heterogeneous nodes are either synchronous or asynchronous, but do not consider both cases simultaneously. In this paper, a cubature Kalman filter (CKF) based fusion algorithm is proposed to deal with the aforementioned issue. Under this fusion algorithm, the measurements of active and passive radars are pre-processed and then filtered by the CKF, then the filtering results are sent to the fusion center, which determines whether the measurements of active radar and passive radar are synchronous or asynchronous through the timing sequence. Sequential fusion is used for asynchronous measurements and global fusion is used for synchronous measurements to form a state estimation of the target. The simulation results show that compared with the active radar systems, the active and passive radar systems can significantly improve the target angular tracking performance, radial velocity and acceleration tracking accuracy.