Efficient radar data processing algorithm for dense cluttered environment

摘要

The most challenge of early warning balloon-borne radar (EWBR) is how to tracking small slow-moving targets. Because of the low detect velocity threshold, there are large numbers of uncertain measurements, such as reports from the ground traffic vehicles and reports from the clouds. Therefore, the data processing is very difficult to process the dense clutter measurements. An efficient data processing algorithm for the early warning balloon-borne radar is presented. The proposed algorithm combines a clutter map technique with a track-oriented multiple hypothesis tracking (TOMHT) method. Clutter map is used to reduce clutter and supply prior environment knowledge to MHT which can improve target tracking performance by adaptive parameter control. The algorithm's real time performance is proved by real radar application. The results indicate that the algorithm can reduce considerable false track rate and improve tracking performance.