An Extended Robust Chance-Constrained Power Allocation Scheme for Multiple Target Localization of Digital Array Radar in Strong Clutter Environments

Abstract

The traditional power allocation method for multi-target localization adopts the Robust Chance Constrained Power Allocation Scheme (RCC-PA), which does not consider the strong clutter characteristics in the current radar detection environment. However, how to reasonably allocate the power required for the radar to locate the target in the strong clutter is a fundamental challenge for improving the combat capability of the radar. Since Simultaneous Multi-beam Digital Array Radar (SM-DAR) can provide high-resolution information on targets in strong clutter, this paper extends the RCC-PA scheme to strong clutter and introduce an extended target model suitable for high-resolution SM-DAR. At the same time, the Gamma distribution is used to reflect the statistical characteristics of the Radar Cross Section (RCS) so that the extended RCC-PA scheme (ERCC-PA) can be suitable for all the scatterers whose RCS belong to Gamma distribution families. In the ERCC-PA scheme, the Strong Clutter Information Reduction Factor (SCIRF) of the extended target is first derived. Then, a Gamma Chance-constraint Programming Model (Γ-CCP model) is constructed to optimize the power allocation for locating multiple extended targets in strong clutter. The extended dichotomy method for power allocation is also given. Theoretical analysis shows that the power of multi-target localization in strong clutter can still be reasonably allocated under the target with multi-measurement characteristics. In addition, the power distribution of multi-target localization in the strong clutter is negatively correlated with the shape parameter of the Gamma distribution. Specifically, the larger the shape parameter characterizes the larger individual strong scatterer, resulting in the SM-DAR requiring less positioning power. The experimental results verify the theoretical analysis and show that the ERCC-PA scheme can improve the utilization of power compared with the benchmark and has the advantage of robustness to the fluctuation of the target RCS.

Keywords

• multi-target localization
• Strong Clutter Information Reduction Factor (SCIRF)
• Extended Robust Chance-Constrained Power Allocation (ERCC-PA)
• Gamma Chance-constraint Programming (Γ-CCP)
• Radar Cross Section (RCS)
• extended target