A novel sliding window detection method for distributed targets

With the continuous improvement of radar resolution, a higher detection performance requirement is put forward for distributed targets. However, the existing algorithms have not yet formed a detection performance evaluation theory. In this paper, a novel sliding window detection method for distributed targets is presented. Firstly, the two-dimensional sliding window is designed to achieve the optimal matching for the specified target with any navigation direction based on the prior information, i.e., RCS, target size and radar resolution. Then, the target units within the sliding window are processed by means of the criterion, and thus to avoid the detection performance loss caused by the artificial construction of extended detection factor. Finally, by mining the detection performance relationship between the distributed target and that of a single resolution unit, a new quantitative evaluation method with regard to high-resolution radar is designed from the perspective of the given system false alarm index, where the detection probability of distributed target on the premise of satisfying the false alarm performance can be greatly improved. The proposed algorithm does not need to design the complex extended detection factor, which provides a new way for robust detection and performance evaluation for distributed targets.