Detection of an Unknown Number of Targets in Heavy Cluster

This paper deals with detection of unknown quantity of lower observable targets in heavy clutter. A track before detect (TBD) algorithm based on Hough Transform and expanded trellis is proposed in this paper. First, a standard Hough Transform algorithm and a method of minimum distance are used to get the candidate tracks. And then each candidate track forms an expanded trellis which is applied to filter clutters further. In order to reduce false alarms, the mean power of all the measurements on each candidate track is calculated respectively to be as a threshold value. The number of the targets is conformed by a strategy of outliers eliminating and their tracks are extracted successfully at last. Experimental results indicate that the proposed algorithm not only meet the real time challenge, but also be capable of detecting multiple targets without the assumptions of an upper bound to the number of the targets.