COMPUTATIONALLY EFFICIENT COHERENT INTEGRATION ALGORITHM BASED ON DBO FOR WEAK MANEUVERING TARGET

In addressing the challenges of compensating for distance migration and Doppler frequency migration during long-time coherent integration, the generalized Radon-Fourier transform (GRFT) requires a multi-dimensional, joint parameter search to accurately detect the motion parameters of moving targets. However, this necessitates a geometric increase in computational complexity as the order of the echo signal model rises. To mitigate this, this paper proposes an optimization of the GRFT integration process based on the Dung Beetle Optimizer (DBO). This optimization technique swiftly fine-tunes the objective function parameters, thereby reducing both computational time and load to satisfy the requirements of real-time signal processing applications. The effectiveness of the proposed method is validated through simulation experiments and compared to Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), which shows that the proposed method can efficiently obtain the integration results with low computational burden.