Optimal Search Strategy of Low-Altitude Target for Airborne Phased Array Radar Using Digital Elevation Model

Abstract

The search for low-altitude targets becomes a more challenging task for airborne phased array radar, due to the limited system resources and serious ground clutter. In this paper, an optimal search strategy using the digital elevation model (DEM) is proposed to allow for fast and high-probability search for low-altitude targets. First, a clutter-free detection region is formed by introducing the DEM. Compared with the traditional methods, the detection probability of the lowaltitude targets can be improved. Second, the search problem is transformed into a constrained multi-objective optimization problem. The proposed strategy can simultaneously minimize the search time and maximize the target detection probability. Finally, two intelligent evolutionary algorithms are compared to verify the proposed strategy, and the proposed strategy is also testified by utilizing a real DEM data of Dujiangyan, Sichuan, China. Simulated results indicate that the proposed optimal search framework improves the detection probability and reduces time cost for low-altitude targets.

Estimating Scattering Coefficient in a Large and Complex Terrain through Multifactor Association

“…Oreshkina et al [23] proposed a method to optimize the azimuthal sampling interval of digital topographic maps for radar ground clutter simulations. Luo et al [24] proposed an optimal searching strategy based on DEMs to suppress ground clutter and achieve a fast and high-probability search for low-altitude targets. Kim et al [25] proposed a method for synthesizing clutter based on an empirical model by creating and accumulating clutter block by block to predict clutter in unexplored environments and operational conditions.…”