A Novel Subspace Segmentation Processing Method for Radar Hybrid Integration Detection

A high-speed maneuvering target will bring serious range migration (RM) and Doppler frequency migration (DFM) under long integration, thereby affecting the effective radar monitoring of the target. To achieve improved accumulation performance with low complexity, a subspace hybrid integration method (SHI) based on parameter space division and subspace movement has been proposed. However, the exhaustive traversal of all subspaces to find the optimal solution results in a significant waste of computational resources. Addressing this issue, we propose bisection processing subspace hybrid integration (BPSHI) to further reduce computational expenses while maintaining the benefits of the SHI method. BPSHI evenly divides each dimension parameter interval to establish a subspace. After the SM operation, it evaluates the HI outcomes across all subspaces and elects the most favorable one to progress into the subsequent iteration phase. Fuse the HI results on all subspaces in each iteration process, and the accurate motion parameters of each order of the target can be obtained. Compared with the SHI algorithm, simulations are provided that the proposed BPSHI method can achieve optimal computational cost under similar detection performance.